bluuebunny/crossref_metadata_2025 huggingface dataset:
Patient-Derived Lung Tumoroids—An Emerging Technology in Drug Development and Precision Medicine
Authors: Lê Hélène , Seitlinger Joseph , Lindner Véronique , Olland Anne , Falcoz Pierre-Emmanuel , Benkirane-Jessel Nadia , Quéméneur Eric
Published: July 2022

Synthetic 3D multicellular systems derived from patient tumors, or tumoroids, have been developed to complete the cancer research arsenal and overcome the limits of current preclinical models. They aim to represent the molecular and structural heterogeneity of the tumor micro-environment, and its complex network of interactions, with greater accuracy. They are more predictive of clinical outcomes, of adverse events, and of resistance mechanisms. Thus, they increase the success rate of drug development, and help clinicians in their decision-making process. Lung cancer remains amongst the deadliest of diseases, and still requires intensive research. In this review, we analyze the merits and drawbacks of the current preclinical models used in lung cancer research, and the position of tumoroids. The introduction of immune cells and healthy regulatory cells in autologous tumoroid models has enabled their application to most recent therapeutic concepts. The possibility of deriving tumoroids from primary tumors within reasonable time has opened a direct approach to patient-specific features, supporting their future role in precision medicine.
Simultaneous Bilateral Frontal and Bilateral Cerebellar Transcranial Direct Current Stimulation in Treatment-Resistant Depression—Clinical Effects and Electrical Field Modelling of a Novel Electrodes Montage
Authors: D’Urso Giordano , Dini Michelangelo , Bonato Marta , Gallucci Silvia , Parazzini Marta , Maiorana Natale , Bortolomasi Marco , Priori Alberto , Ferrucci Roberta
Published: July 2022

Depressive disorders are one of the leading causes of disability worldwide. Transcranial direct current stimulation (tDCS) is a safe, simple, non-invasive brain stimulation technique showing considerable effectiveness in improving depressive symptoms. Most studies to date have applied anodal tDCS to the left dorsolateral prefrontal cortex (DLPFC), in line with the hypothesis that depressed patients exhibit relative hypoactivity in the left DLPFC compared to the right. Considering the emerging role of the cerebellum in emotional processes, we aimed to study the effect of combining bilateral cerebellar tDCS with the commonly used bifrontal stimulation in patients with severe depression. This open-label pilot study entailed the simultaneous administration of bilateral cerebellar (anode over the left cerebellum, cathode over the right cerebellum) and bilateral frontal (anode over the left DLPFC, cathode over the right DLPFC) tDCS to patients (N = 12) with treatment-resistant depression. The 21-item Hamilton Depression Rating Scale (HDRS) and Beck’s Depression Inventory-II (BDI-II) were selected as outcome measures. Electric fields distribution originating from this novel electrode montage was obtained by a computational method applied to a realistic human head model. We observed a 30% reduction of both clinician-rated and self-reported severity of depressive symptoms after only five days (10 sessions) of treatment. Younger age was associated with greater clinical improvement. Adverse events were similar to those of the conventional electrodes montage. The modelling studies demonstrated that the electric fields generated by each pair of electrodes are primarily distributed in the cortical areas under the electrodes. In conclusion, the cerebellum could represent a promising adjunctive target for tDCS interventions in patients with TRD, particularly for younger patients.
Wear Behaviour of Polymer-Infiltrated Network Ceramics, Lithium Disilicate and Cubic Zirconia against Enamel in a Bruxism-Simulated Scenario
Authors: Baldi Andrea , Carossa Massimo , Comba Allegra , Alovisi Mario , Femiano Felice , Pasqualini Damiano , Berutti Elio , Scotti Nicola
Published: July 2022

The present study aimed to evaluate the wear rate of polymer-infiltrated network composites and ceramics against enamel in a bruxism-simulated scenario. Ninety-six (n = 96) molars were divided into six groups (n = 16) according to their occlusal material: group 1—a polymer-infiltrated network ceramic (PINC); group 2—a second polymer-infiltrated network ceramic (PINC2); group 3—nanohybrid resin-based composite (CO); group 4—cubic zirconia (ZR); group 5—lithium disilicate (LS); and group 6—sound enamel (EN). A laser scanner was used to digitalize all of the occlusal surfaces before and after a fatigue test, which was conducted with a chewing simulator set at 80 N and semicircular movement in order to simulate bruxist movement and loads. Statistical analysis of volume loss was performed with a one-way ANOVA and post hoc Bonferroni test. ZR had significantly inferior wear to PINC (p ≤ 0.01) and CO (p = 0.04). LS wore the antagonist enamel significantly more than PINC, CO, PINC2 and EN (p ≤ 0.01). On the other hand, ZR wore the antagonist enamel significantly more than CO (p ≤ 0.01) and PINC2 (p = 0.05). In conclusion, PINCs better preserved antagonist enamel at the expense of a higher wear of their own. LS causes significantly higher enamel wear compared with PINCs. ZR caused significantly higher enamel wear compared with CO and PINC2, but it was wear-resistant.
A Review of EMG-, FMG-, and EIT-Based Biosensors and Relevant Human–Machine Interactivities and Biomedical Applications
Authors: Zheng Zhuo , Wu Zinan , Zhao Runkun , Ni Yinghui , Jing Xutian , Gao Shuo
Published: July 2022

Wearables developed for human body signal detection receive increasing attention in the current decade. Compared to implantable sensors, wearables are more focused on body motion detection, which can support human–machine interaction (HMI) and biomedical applications. In wearables, electromyography (EMG)-, force myography (FMG)-, and electrical impedance tomography (EIT)-based body information monitoring technologies are broadly presented. In the literature, all of them have been adopted for many similar application scenarios, which easily confuses researchers when they start to explore the area. Hence, in this article, we review the three technologies in detail, from basics including working principles, device architectures, interpretation algorithms, application examples, merits and drawbacks, to state-of-the-art works, challenges remaining to be solved and the outlook of the field. We believe the content in this paper could help readers create a whole image of designing and applying the three technologies in relevant scenarios.
Identifying Non-Math Students from Brain MRIs with an Ensemble Classifier Based on Subspace-Enhanced Contrastive Learning
Authors: Liu Shuhui , Zhang Yupei , Peng Jiajie , Wang Tao , Shang Xuequn
Published: July 2022

In current research processes, mathematical learning has significantly impacted the brain’s plasticity and cognitive functions. While biochemical changes in brain have been investigated by magnetic resonance spectroscopy, our study attempts to identify non-math students by using magnetic resonance imaging scans (MRIs). The proposed method crops the left middle front gyrus (MFG) region from the MRI, resulting in a multi-instance classification problem. Then, subspace enhanced contrastive learning is employed on all instances to learn robust deep features, followed by an ensemble classifier based on multiple-layer-perceptron models for student identification. The experiments were conducted on 123 MRIs taken from 72 math students and 51 non-math students. The proposed method arrived at an accuracy of 73.7% for image classification and 91.8% for student classification. Results show the proposed workflow successfully identifies the students who lack mathematical education by using MRI data. This study provides insights into the impact of mathematical education on brain development from structural imaging.
Neuroanatomical Correlates of Semantic Features of Narrative Speech in Semantic and Logopenic Variants of Primary Progressive Aphasia
Authors: Quaranta Davide , Di Tella Sonia , Marra Camillo , Gaudino Simona , L’Abbate Federica , Silveri Maria Caterina
Published: July 2022

The semantic variant of a primary progressive aphasia (svPPA) is characterized by progressive disruption of semantic knowledge. This study aimed to compare the semantic features of words produced during a narrative speech in svPPA and the logopenic variant of PPA (lvPPA) and to explore their neuroanatomical correlates. Six patients with svPPA and sixteen with lvPPA underwent narrative speech tasks. For all the content words, a semantic depth index (SDI) was determined based on the taxonomic structure of a large lexical database. Study participants underwent an MRI examination. Cortical thickness measures were extracted according to the Desikan atlas. Correlations were computed between SDI and the thickness of cortical regions. Mean SDI was lower for svPPA than for lvPPA. Correlation analyses showed a positive association between the SDI and the cortical thickness of the bilateral temporal pole, parahippocampal and entorhinal cortices, and left middle and superior temporal cortices. Disruption of semantic knowledge observed in svPPA leads to the production of generic terms in narrative speech, and the SDI may be useful for quantifying the level of semantic impairment. The measure was associated with the cortical thickness of brain regions associated with semantic memory.
Push-Out Test and Hysteretic Performance Study of Semi-Rigid Shear Keys with the Triple-Folded Web of Flange
Authors: Wang Zhenshan , Qin Huaqian , Yang Yong , Liu Yunhe , Guo Hongchao , Wang Hongchen
Published: July 2022

The PBL (Perfobond Leiste) shear connector has the advantages of high bearing capacity and strong constraint ability; however, the traditional PBL shear connector has strong and weak axis problems, and its stiffness is large, resulting in weak deformation ability. To this end, this paper proposes a new type of flange triple-web shear key and obtains the new shear key’s mechanical properties and failure mechanism through the push-out test. The results show that the failure mode of the new shear key is the deformation of the steel plate on the web and the edge of the opening, which has a high bearing capacity, outstanding deformation ability, and good integrity with concrete, showing obvious semi-rigid characteristics. Through numerical analysis, the effects of flange width, web height, and steel plate thickness on the mechanical properties of shear keys are obtained. Based on the fitting analysis method, the calculation formula of shear key bearing capacity is proposed. Finally, the horizontal seismic performance of the shear key is numerically simulated. It is found that the hysteretic curve of the shear key is full and shows good energy dissipation capacity.
Substance Detection and Identification Using Frequency Doubling of the THz Broadband Pulse
Authors: Trofimov Vyacheslav A. , Varentsova Svetlana A. , Yang Yongqiang , Cai Zihao
Published: July 2022

We propose and discuss an effective tool for substance detection and identification using a broadband THz pulse that is based on frequency conversion near the substance absorption frequencies. With this aim, we analyze the evolution of spectral intensities at the doubled absorption frequencies in order to prove their similarity to those at which the absorption of THz pulse energy occurs. This analysis is provided for both artificial THz signals and the real signals reflected from the substances under consideration. We demonstrate the feasibility of the proposed approach in the detection and identification of substances with an inhomogeneous surface, which is the most difficult case for practice, by using the method of spectral dynamic analysis and integral correlation criteria.
Exploring Change in Children’s and Art Therapists’ Behavior during ‘Images of Self’, an Art Therapy Program for Children Diagnosed with Autism Spectrum Disorders: A Repeated Case Study Design
Authors: Schweizer Celine , Knorth Erik J. , Van Yperen Tom A. , Spreen Marinus
Published: July 2022

(1) Background: ‘Images of Self’ (IOS) is a recently developed and evaluated art therapy program of 15 sessions to reduce difficulties in ‘sense of self’, ‘emotion regulation’, ‘flexibility’, and ‘social behavior’ of children diagnosed with Autism Spectrum Disorders (ASD). In this paper, it is explored whether change in the child’s behaviors corresponds to the therapist’s actions during IOS and 15 weeks later. (2) Method: In a repeated case study design, twelve children and seven therapists participated. Art therapists monitored their own and the children’s behavior by applying two observation instruments: the OAT (Observation of a child with autism in Art Therapy) and EAT (Evaluation of Art Therapist’s behavior when working with a child with autism). Child behaviors during art making were—individually and as a group—compared with therapist’s actions at three moments during the program. (3) Results: Ten of twelve children showed a substantial or moderate positive behavior change considering all OAT subscales at the end of the program and 15 weeks after treatment. Improvement of ‘social behavior’ stood out. Halfway treatment art therapists most prominently showed support of ‘emotion regulation’, ‘flexibility’, and ‘social behavior’. Clear one-on-one relationships between changes in children’s behavior and actions of therapists could not be identified. (4) Conclusion: The study provides new insights in the AT treatment process by monitoring children’s and therapists’ behavior. The art making itself and the art therapy triangle (child, art making, therapist) offer opportunities to improve verbal and nonverbal communication skills of the child.
Family Dysfunctional Interactive Patterns and Alexithymia in Adolescent Patients with Restrictive Eating Disorders
Authors: Coci Chiara , Provenzi Livio , De Giorgis Valentina , Borgatti Renato , Chiappedi Matteo , Mensi Martina Maria ,   on behalf of the Mondino Foundation Eating Disorders Clinical and Research Group
Published: July 2022

Adolescents diagnosed with Restrictive Eating Disorders (REDs) are at risk for alexithymia. REDs patients’ families show dysfunctional interactive patterns, and childhood family environment influences alexithymia development. We aimed to assess the relationship between family dysfunctional interactive patterns and patients’ alexithymia in a sample of adolescents diagnosed with REDs. Forty-five patients and their parents were enrolled. They participated in the clinical version of the Lausanne Triadic Play (LTPc), a standardized observational procedure to assess family functioning. We used the self-report questionnaire Toronto Alexithymia Scale (TAS-20) to assess patients’ alexithymia. The TAS-20 provides a multi-factorial measure of patients’ alexithymia: Difficulty in Identifying Feelings, DIF; Difficulty in Describing Feelings, DDF; Externally-oriented Thinking, EOT) and a total (TOT) score. DDF and EOT scores were significantly higher than DIF score. Patients’ families showed dysfunctional interactive patterns, with a predominance of collusive alliance. Patients from families characterized by collusive alliance had higher TOT scores compared to counterparts from families exhibiting a different interactive dysfunctional pattern. In families characterized by a collusive triadic alliance, the dysfunctional interactive pattern was linked with the risk of alexithymia in patients with REDs. Assessment of family relationships should be included in the routine consultation with adolescent patients affected by REDs.
Deformation-Driven Processing of CNTs/PEEK Composites towards Wear and Tribology Applications
Authors: Cui Yan , Li Chong , Li Zenglou , Yao Xiaojie , Hao Wenbo , Xing Songling , Xie Yuming , Meng Xiangchen , Wan Long , Huang Yongxian
Published: July 2022

Despite wide applications in mechanical transmission components, sparked with extraordinary wear resistance, polymeric composites face the challenges of reinforcement agglomeration. In this work, deformation-driven processing was proposed to prepare carbon nanotube (CNTs)-reinforced poly-ether-ether-ketone (PEEK) matrix composites with enhancement in wear resistance. Severe plastic deformation contributed to the homogeneous dispersion of the reinforcements without undesirable agglomeration. Low frictional heat input ensured the structural integrity of CNTs. The coefficient of friction and wear rate of 3.0 wt.% CNTs/PEEK were, respectively, 7.32% and 6.71% lower than those of pure PEEK. This strategy provides a high-efficiency approach to preparing high wear-resistance polymeric composites, attributed to its self-heating, low-cost, and high-performance characteristics.
Transcriptome Dynamics of an Oyster Larval Response to a Conspecific Cue-Mediated Settlement Induction in the Pacific Oyster Crassostrea gigas
Authors: Sedanza Mary , Alshaweesh Jalal , Gao Yi-Li , Yoshida Asami , Kim Hee-Jin , Yamaguchi Kenichi , Satuito Cyril
Published: July 2022

The molecular mechanisms underlying the conspecific cue-mediated larval settlement in Crassostrea gigas is not yet fully understood. In this study, we described and compared the transcriptomes of competent pediveligers (Pedi) and conspecific cue-induced postlarvae (PL). A total of 2383 candidate transcripts were identified: 740 upregulated and 1643 downregulated transcripts, after settlement. Gene Ontology analysis revealed active chitin binding, calcium ion binding, and extracellular region processes in both stages. Results showed that the differential expression trend of six candidate transcripts were consistent between the quantitative real-time PCR and transcriptome data. The differential transcript expression related to shell formation showed closely linked dynamics with a gene regulatory network that may involve the interplay of various hormone receptors, neurotransmitters, and neuropeptide receptors working together in a concerted way in the Pedi and PL stages. Our results highlight the transcriptome dynamics underlying the settlement of oysters on conspecific adult shells and demonstrate the potential use of this cue as an attractant for wild and hatchery-grown oyster larval attachment on artificial substrates. It also suggests the possible involvement of an ecdysone signal pathway that may be linked to a neuroendocrine-biomineralization crosstalk in C. gigas settlement.
Estimation of Blooming Start with the Adaptation of the Unified Model for Three Apricot Cultivars (Prunus armeniaca L.) Based on Long-Term Observations in Hungary (1994–2020)
Authors: Mesterházy Ildikó , Raffai Péter , Szalay László , Bozó László , Ladányi Márta
Published: July 2022

The aim of our research was to adapt Chuine’s unified model to estimate the beginning of blooming of three apricot cultivars (‘Ceglédi bíborkajszi’, ‘Gönci magyar kajszi’, and ‘Rózsakajszi C.1406’) in Hungary in the time period 1994–2020. The unified model is based on the collection of chilling and forcing units. The complexity of the model lies in the high number of parameters necessary to run it. Following the work of other researchers, we reduced the number of relevant model parameters (MP) to six. In order to estimate the six MPs, we used a simulated annealing optimization method (known for being effective in avoiding getting stuck in local minima). From the results, we determined the local optimum of six MPs, and the global optimum parameter vector for three apricot cultivars. With these global optimum parameter vectors, the beginning of blooming could be estimated with a root-mean-square error (RMSE) of less than 2.5 days, using the knowledge of the daily mean temperature in the time period 1994–2020.
Postpartum Assessment of the Correlation between Serum Hormone Levels of Estradiol, Progesterone, Prolactin and ß-HCG and Blood Pressure Measurements in Pre-Eclampsia Patients
Authors: Kasoha Mariz , Takacs Zoltan , Dumé Jacob , Findeklee Sebastian , Gerlinger Christoph , Sima Romina-Marina , Ples Liana , Solomayer Erich-Franz , Haj Hamoud Bashar
Published: July 2022

Background: Preeclampsia is a pregnancy-related hypertensive disease. Aberrant hormone levels have been implicated in blood pressure disorders. This study investigated the association of postpartum maternal serum hormone levels of estradiol, progesterone, prolactin, and ß-HCG with poorer PE-related complications including arterial hypertension. Methods: Thirty patient women with preeclampsia, and twenty women with uncomplicated pregnancy were included in this study. Serum levels of estradiol, progesterone, prolactin, and ß-HCG were determined immediately after delivery, and on the first and third postpartum days by means of ECLIA. Results: Compared with normal pregnancy cases, preeclampsia cases had higher serum levels of ß-HCG levels on Day-0 (319%), of progesterone on Day-0 (207%) and Day-1 (178%), and of estradiol on Day-1 (187%) and Day-3 (185%). Increased prolactin levels were positively associated with disease severity and estradiol and progesterone levels were decreased in poorer preeclampsia features including disease onset and IUGR diagnosis. No significant correlation between different hormone levels and blood pressure measurements was reported. Conclusions: This study is the first that detected postpartum maternal serum hormone levels and their correlation with blood pressure measurements in preeclampsia. We believe that the persistent arterial hypertension in the puerperium in preeclampsia as well as poorer disease specifications are most likely not of hormonal origin. Larger, well-defined prospective studies are recommended.
Attention-Shared Multi-Agent Actor–Critic-Based Deep Reinforcement Learning Approach for Mobile Charging Dynamic Scheduling in Wireless Rechargeable Sensor Networks
Authors: Jiang Chengpeng , Wang Ziyang , Chen Shuai , Li Jinglin , Wang Haoran , Xiang Jinwei , Xiao Wendong
Published: July 2022

The breakthrough of wireless energy transmission (WET) technology has greatly promoted the wireless rechargeable sensor networks (WRSNs). A promising method to overcome the energy constraint problem in WRSNs is mobile charging by employing a mobile charger to charge sensors via WET. Recently, more and more studies have been conducted for mobile charging scheduling under dynamic charging environments, ignoring the consideration of the joint charging sequence scheduling and charging ratio control (JSSRC) optimal design. This paper will propose a novel attention-shared multi-agent actor–critic-based deep reinforcement learning approach for JSSRC (AMADRL-JSSRC). In AMADRL-JSSRC, we employ two heterogeneous agents named charging sequence scheduler and charging ratio controller with an independent actor network and critic network. Meanwhile, we design the reward function for them, respectively, by considering the tour length and the number of dead sensors. The AMADRL-JSSRC trains decentralized policies in multi-agent environments, using a centralized computing critic network to share an attention mechanism, and it selects relevant policy information for each agent at every charging decision. Simulation results demonstrate that the proposed AMADRL-JSSRC can efficiently prolong the lifetime of the network and reduce the number of death sensors compared with the baseline algorithms.
Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory
Authors: Lv Ying , Zhang Bofeng , Zou Guobing , Yue Xiaodong , Xu Zhikang , Li Haiyan
Published: July 2022

Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertainty may lead to models with unreliable and suboptimal classification results for the target domain task. However, most previous works focus on reducing the gap in data distribution between the source and target domains. They do not consider the uncertainty of source domain data about the target domain task and cannot apply the uncertainty to learn an adaptive classifier. Aimed at this problem, we revisit the domain adaptation from source domain data uncertainty based on evidence theory and thereby devise an adaptive classifier with the uncertainty measure. Based on evidence theory, we first design an evidence net to estimate the uncertainty of source domain data about the target domain task. Second, we design a general loss function with the uncertainty measure for the adaptive classifier and extend the loss function to support vector machine. Finally, numerical experiments on simulation datasets and real-world applications are given to comprehensively demonstrate the effectiveness of the adaptive classifier with the uncertainty measure.
Impact of Perceptions of Air Pollution and Noise on Subjective Well-Being and Health
Authors: Herrera Carolina , Cabrera-Barona Pablo
Published: July 2022

With a growing interest in the study of urban life and health, evidence indicates that the quality of the environment in which we live can have implications for our subjective well-being and health. This study assesses the potential impacts of perceptions of visual air pollution, olfactory air pollution, and noise pollution on self-perceived health, self-perceived happiness, and satisfaction with life, through the calculation of ordinal logistic regressions, using the information of an online survey carried out in Quito, Ecuador. We found that perceptions of unpleasant odors and noise pollution influence self-perceived health, self-perceived happiness, and satisfaction with life. The obtained results may support the incorporation of citizens’ perspectives to better understand environmental pollution and to enrich local planning for urban sustainability.
Mathematical Modeling of Physical Capital Diffusion Using a Spatial Solow Model: Application to Smuggling in Venezuela
Authors: González-Parra Gilberto , Chen-Charpentier Benito , Arenas Abraham J. , Díaz-Rodríguez Miguel
Published: July 2022

This study proposes a mathematical modeling approach for the physical capital diffusion through the borders of countries. Physical capital is considered a crucial variable for the economic growth of a nation. Here, we use an extension of the economic Solow model to describe how smuggling affects the economic growth of countries. In particular, we focus on the situation in Venezuela from 2012 to 2015. In this regard, we rely on a nonconcave production function instead of the classical Cobb–Douglas production function. Moreover, we investigate the effect of different physical capital fluxes on economic growth. The physical capital diffusion through the borders of a country is modeled based on a parabolic partial differential equation describing the dynamics of physical capital and boundary conditions of the Neumann type. Smuggling is present at numerous borders between countries and may include fuel, machinery, and food. This smuggling through the borders places challenges on a particular country’s economy. The smuggling problem usually is related to a non-official exchange rate different from the official rate or subsidies. We study the effect of smuggling on the physical capital of a country using an extended Solow model. Numerical simulations are obtained using an explicit finite difference scheme describing how the physical capital diffusion through the border of a country affects its economic growth. The study of physical capital is a paramount aspect of the economic growth of several countries. The results show that when boundary conditions of Neumann type are different from zero, the dynamics of the physical capital differ from the classical economic behavior observed in the classical spatial Solow model without physical capital flux through the borders of countries. In particular, the numerical results show that the physical capital of a country decreases faster as the flux increases on the boundaries. Thus, we can conclude that avoiding smuggling through the frontiers is a crucial factor affecting economic growth.
Nontechnological Online Challenges Faced by Health Professions Students during COVID-19: A Questionnaire Study
Authors: Alshamsi Abdulmalik Khalid , Masters Ken
Published: July 2022

COVID-19 forced universities to shift to online learning (emergency remote teaching (ERT)). This study aimed at identifying the nontechnological challenges that faced Sultan Qaboos University medical and biomedical sciences students during the pandemic. This was a survey-based, cross-sectional study aimed at identifying nontechnological challenges using Likert scale, multiple-choice, and open-ended questions. Students participated voluntarily and gave their consent; anonymity was maintained and all data were encrypted. The response rate was 17.95% (n = 131) with no statistically significant difference based on gender or majors (p-value > 0.05). Of the sample, 102 (77.9%) were stressed by exam location uncertainty, 96 (73.3%) felt easily distracted, 98 (74.8%) suffered physical health issues, and 89 (67.9%) struggled with time management. The main barriers were lack of motivation (92 (70.2%)), instruction/information overload (78 (59.5%)), and poor communication with teachers (74 (56.5%)). Furthermore, 57 (43.5%) said their prayer time was affected, and 65 (49.6%) had difficulties studying during Ramadan. The most important qualitative findings were poor communication and lack of motivation, which were reflected in student comments. While ERT had positive aspects, it precipitated many nontechnological challenges that highlight the inapplicability of ERT as a method of online learning for long-term e-learning initiatives. Challenges must be considered by the faculty to provide the best learning experience for students in the future.
Three Stressed Systems: Health Sciences Faculty Members Navigating Academia, Healthcare, and Family Life during the Pandemic
Authors: Naidoo Keshrie , Kaplan Sarah , Roberts Callie Jordan , Plummer Laura
Published: July 2022

The purpose of this study was to explore the impact of the COVID-19 pandemic on the academic productivity of health sciences faculty members in one graduate school in the United States. Thirty-two faculty members completed an electronic survey comparing academic productivity in the year prior to the pandemic to a year during the pandemic. In total, 90.7% of respondents agreed or strongly agreed that time dedicated to teaching increased, and 81.2% agreed or strongly agreed that they prioritized teaching over research during the pandemic. Participants presented an average of 2.72 peer-reviewed papers at an academic conference the year before and 1.47 during the pandemic, with females more adversely affected than males. Journal submissions with survey participants as the first or last authors decreased during the pandemic. Twelve faculty members including genetic counseling, nursing, occupational therapy, physical therapy, and speech and language pathology participated in one-to-one interviews. Three themes emerged from qualitative data analysis: stressed systems, balancing act, and meaningful connection. Faculty members were faced with an external locus of control during the pandemic and noted a lack of autonomy and pressure to help students graduate on time and maintain the quality of teaching while dealing with uncertainty in both their professional and personal lives. The pandemic disproportionately impacted women and junior faculty members as connectedness and mentorship declined. Collaboration and research mentorship must be prioritized moving forward to continue to advance healthcare and health sciences education.
Cluster Analysis of the EU-27 Countries in Light of the Guiding Principles of the European Green Deal, with Particular Emphasis on Poland
Authors: Rybak Aurelia , Rybak Aleksandra , Joostberens Jarosław , Kolev Spas D.
Published: July 2022

The article presents a cluster analysis of the EU-27 countries. The clusters were built to identify groups of countries similar to each other in relation to the set of Eurostat indicators from the Climate Change Drivers and Environment and Energy sections. During the research, tools of spatial information systems were used, such as cluster analysis, diagram maps, rasterization and the TSA method. ARIMA prediction models were also used. The research aims to verify our hypotheses. Particular attention was paid to Poland; therefore, it was verified whether the composition of the country’s energy mix translated into excessive emissions of pollutants in relation to other EU countries. Furthermore, the level of integration of energy markets in the European Union and its changes over time were examined. The authors also proposed a methodology to create detailed energy and climate strategies for designated clusters. The results of the presented research are particularly important in light of recent events in Ukraine.
Modeling the Next Decade of Energy Sustainability: A Case of a Developing Country
Authors: Adeyemi-Kayode Temitope , Misra Sanjay , Orovwode Hope , Adoghe Anthony
Published: July 2022

The development of any country is closely related to its ability to provide access to electricity for productive labor. Many countries in sub-Saharan Africa have low electrification rates for commercial, industrial and residential consumers. This study focuses on Nigeria, which has one of the largest populations and economies in sub-Saharan Africa. Although Nigeria possesses abundant renewable energy resources that can increase electricity generation, it has suffered a significant setback in electricity generation. However, for Nigeria to become one of the leading industrialized countries by 2030, access to clean, reliable, and sustainable energy sources is vital (Vision 20: 2030). This study assesses the possibility of Nigeria developing and transitioning to the use of various energy sources. Additionally, this study evaluates greenhouse gas (GHG) mitigation plans and future trends in energy sustainability through multi-criteria decision analysis (MCDA), considering the technical, social, economic, and environmental dimensions of the sustainability structure. A total of twelve (12) sustainability indexes were taken into consideration; these consist of two (2) technical, three (3) social, three (3) environmental, and four (4) economic indicators. A scenario-based software called Long-range Energy Alternative Plan (LEAP) was used to integrate the analysis criteria and forecast a sustainable energy generation mix for the future. It considered three scenarios, namely: the business as usual scenario (BAU); renewables, natural gas and biomass scenario (RNB); and renewables and coal scenario (REC). It was concluded that the renewables, natural gas, and biomass scenario (RNB) is the best scenario to solve Nigeria’s energy problem based on the aim of the study.
On Hourly Forecasting Heating Energy Consumption of HVAC with Recurrent Neural Networks
Authors: Metsä-Eerola Iivo , Pulkkinen Jukka , Niemitalo Olli , Koskela Olli
Published: July 2022

Optimizing the heating, ventilation, and air conditioning (HVAC) system to minimize district heating usage in large groups of managed buildings is of the utmost important, and it requires a machine learning (ML) model to predict the energy consumption. An industrial use case to reach large building groups is restricted to using normal operational data in the modeling, and this is one reason for the low utilization of ML in HVAC optimization. We present a methodology to select the best-fitting ML model on the basis of both Bayesian optimization of black-box models for defining hyperparameters and a fivefold cross-validation for the assessment of each model’s predictive performance. The methodology was tested in one case study using normal operational data, and the model was applied to analyze the energy savings in two different practical scenarios. The software for the modeling is published on GitHub. The results were promising in terms of predicting the energy consumption, and one of the scenarios also showed energy saving potential. According to our research, the GitHub software for the modeling is a good candidate for predicting the energy consumption in large building groups, but further research is needed to explore its scalability for several buildings.
Criticalities of the Outdoor Infrared Inspection of Photovoltaic Modules by Means of Drones
Authors: Vergura Silvano
Published: July 2022

Photovoltaic plants are helping to reduce CO2 emissions, but the energy performance of photovoltaic systems must remain high throughout their operational life. Supervision and monitoring are mandatory for large photovoltaic plants because failures can cause high power losses due to the large number of photovoltaic modules. Infrared analysis is effective and reliable in detecting anomalies or failures in photovoltaic modules, but it is time-consuming and expensive when the infrared inspection of large photovoltaic plants is manual. Nowadays, the diffusion of unmanned aerial vehicles equipped with infrared cameras can support the fast supervision of photovoltaic plants. Nevertheless, the use of drones is regulated by international and national rules; consequently, it is not always possible to use a drone, or its utilization is limited based on geographic areas and/or authorizations. Moreover, infrared analysis requires additional requirements when done by drone, because the mutual position between the photovoltaic modules and the infrared camera affects the goodness of the infrared acquisition. This article discusses these critical issues, directs the reader to official, national, and geographic maps for drones, and suggests technical solutions for some specific issues not considered in the technical specification for the outdoor infrared thermography of photovoltaic modules. In particular, the paper proposes a systematic procedure for the legal and effective infrared inspection of photovoltaic modules by means of a drone and proposes improvements for some issues not discussed in the international rules: the correction of infrared images with respect to the view angle, the impact of a mid-wave and long-wave infrared sensor on the acquired image, and the impact of air transmittance.
Selecting and Testing of Cement-Bonded Magnetite and Chalcopyrite as Oxygen Carrier for Chemical-Looping Combustion
Authors: Li Mengjun , Zheng Teng , Mei Daofeng , Wang Baowen , Ma Jingjing
Published: July 2022

Combining iron and copper ores can generate an oxygen carrier that has a synergic effect of high temperature resistance and high reactivity. In this work, typical cements available in the market were studied as binders to bind magnetite and chalcopyrite to develop a suitable oxygen carrier for chemical-looping combustion (CLC). A first selection step suggested that an aluminate cement, namely CA70, could favor the generation of oxygen carrier particles having good crushing strength, good particle yield, and high reactivity. The CA70-bonded oxygen carrier was then subjected to cyclic tests with CH4, CO, and H2 in reduction and in air oxidation at temperatures of 850, 900, and 950 °C with gas concentrations of 5, 10, 15, and 20% in a batch-fluidized bed reactor. The increase in temperature promoted the fuel conversion. At 950 °C, the conversions of CH4 and CO reached up to 80.4% and 99.2%, respectively. During more than 30 cycles, the oxygen carrier kept a similar reactivity to the fresh carrier and maintained its composition and physical properties. The oxygen transport capacity was maintained at 21–23%, and the phases were CuO, Fe2O3, Al2O3, and minor CaS. In the used sample, some grains were observed, but the morphology was not greatly changed. Agglomeration was absent during all the cycles, except for the deep reduction with H2.
A Scoping Review on Environmental, Economic, and Social Impacts of the Gasification Processes
Authors: Barahmand Zahir , Eikeland Marianne S.
Published: July 2022

In recent years, computer-based simulations have been used to enhance production processes, and sustainable industrial strategies are increasingly being considered in the manufacturing industry. In order to evaluate the performance of a gasification process, the Life Cycle Thinking (LCT) technique gathers relevant impact assessment tools to offer quantitative indications across different domains. Following the PRISMA guidelines, the present paper undertakes a scoping review of gasification processes’ environmental, economic, and social impacts to reveal how LCT approaches coping with sustainability. This report categorizes the examined studies on the gasification process (from 2017 to 2022) through the lens of LCT, discussing the challenges and opportunities. These studies have investigated a variety of biomass feedstock, assessment strategies and tools, geographical span, bioproducts, and databases. The results show that among LCT approaches, by far, the highest interest belonged to life cycle assessment (LCA), followed by life cycle cost (LCC). Only a few studies have addressed exergetic life cycle assessment (ELCA), life cycle energy assessment (LCEA), social impact assessment (SIA), consequential life cycle assessment (CLCA), and water footprint (WLCA). SimaPro® (PRé Consultants, Netherlands), GaBi® (sphere, USA), and OpenLCA (GreenDelta, Germany) demonstrated the greatest contribution. Uncertainty analysis (Monte Carlo approach and sensitivity analysis) was conducted in almost half of the investigations. Most importantly, the results confirm that it is challenging or impossible to compare the environmental impacts of the gasification process with other alternatives since the results may differ based on the methodology, criteria, or presumptions. While gasification performed well in mitigating negative environmental consequences, it is not always the greatest solution compared to other technologies.
Epidrugs: Toward Understanding and Treating Diverse Diseases
Authors: Umehara Takashi
Published: July 2022

Epigenomic modifications are unique in the type and amount of chemical modification at each chromosomal location, can vary from cell to cell, and can be externally modulated by small molecules. In recent years, genome-wide epigenomic modifications have been revealed, and rapid progress has been made in the identification of proteins responsible for epigenomic modifications and in the development of compounds that regulate them. This Special Issue on “Epidrugs: Toward Understanding and Treating Diverse Diseases” aims to provide insights into various aspects of the biology and development of epigenome-regulating compounds.
Shrubification along Pipeline Corridors in Permafrost Regions
Authors: Jin Xiaoying , Jin Huijun , Yang Xue , Wang Wenhui , Huang Shuai , Zhang Shengrong , Yang Suiqiao , Li Xiaoying , Wang Hongwei , He Ruixia , Li Yan , Li Xinze , Li Xinyu
Published: July 2022

Pipeline corridors have been rapidly increasing in length and density because of the ever growing demand for crude oil and natural gas resources in hydrocarbon-rich permafrost regions. Pipeline engineering activities have significant implications for the permafrost environment in cold regions. Along these pipeline corridors, the shrubification in the right-of-way (ROW) has been extensively observed during vegetation recovery. However, the hydrothermal mechanisms of this ROW shrubification have seldom been studied and thus remain poorly understood. This paper reviews more than 112 articles mainly published from 2000 to 2022 and focuses on the hydrothermal mechanisms of shrubification associated with environmental changes induced by the rapidly degrading permafrost from pipeline construction and around the operating pipelines under a warming climate. First, the shrubification from pipeline construction and operation and the ensuing vegetation clearance are featured. Then, key permafrost-related ROW shrubification mechanisms (e.g., from the perspectives of warmer soil, soil moisture, soil type, soil nutrients, topography and landscapes, and snow cover) are discussed. Other key influencing factors on these hydrothermal and other mechanisms are hierarchically documented as well. In the end, future research priorities are identified and proposed. We call for prioritizing more systematic and in-depth investigations and surveys, laboratory testing, long-term field monitoring, and numerical modeling studies of the ROW shrubification along oil and gas pipelines in permafrost regions, such as in boreal and arctic zones, as well as in alpine and high-plateau regions. This review can improve our understanding of shrubification mechanisms under pipeline disturbances and climate changes and help to better manage the ecological environment along pipeline corridors in permafrost regions.
Assessing the Effects of Plant Roots on Soil Water Infiltration Using Dyes and Hydrus-1D
Authors: Wang Haofei , Zhu Xiai , Zakari Sissou , Chen Chunfeng , Liu Wenjie , Jiang Xiao-Jin
Published: July 2022

Forestry eco-hydrology is closely related to root architecture, and soil water infiltration has been always associated with root architecture. In this study, dye infiltration experiments and HYDRUS-1D were used to quantify the effects of different root architectures on the dynamics of soil water infiltration, volumetric water content, and soil water pressure head. The results provide evidence that root channels acted as preferential flow paths for water infiltration and percolation into the soil. Maize fibrous roots, rubber trees fine roots, and Spartina alterniflora smooth roots easily penetrated the plough layer of an agriculture site, the hard soil layer of a forest site, and the alternating sandy and mud layers of an intertidal zone, respectively. The initial and final infiltration rates were significantly different between the rooted and rootless soil profiles. The root-induced infiltration events lowered the propagation time of the wetting front across the rooted soil profile by 33%–113% than the rootless soil (p < 0.05), and the volumetric water content of the saturation zone of the rooted soil profile increased by 12%–19% relative to the rootless soil (p < 0.05). Furthermore, the soil water pressure head increased from negative (i.e., unsaturated) to positive (i.e., saturated) in the saturated soil. This change was more pronounced in the maize fibrous roots soil profile, but less pronounced in the rubber fine roots’ soil profiles or the S. alterniflora smooth roots. The results indicate that the downward movement, volumetric water content, and soil water pressure head were higher in soil profiles having plant roots than the rootless soil, and the degree of roots effects depended on roots architectures, soil hardness, and soil layer configuration. The findings provide evidence that root channels can act as preferential flow paths for water infiltration and percolation into the soil.
Tribological Analysis of Jute/Coir Polyester Composites Filled with Eggshell Powder (ESP) or Nanoclay (NC) Using Grey Rational Method
Authors: Karuppiah Ganesan , Kuttalam Kailasanathan Chidambara , Ayrilmis Nadir , Nagarajan Rajini , Devi M. P. Indira , Palanisamy Sivasubramanian , Santulli Carlo
Published: July 2022

The wear performance of jute/coir unsaturated polyester composites, filled with eggshell powder (ESP) and nanoclay (NC), were examined, concentrating on two measured parameters, coefficient of friction (COF) and wear rate (WR). To assess the possibilities of this material, a Taguchi study, based on grey relational analysis (GRA), was carried out, based on three testing parameters of the wear performance, load (10, 20, and 30 N), speed (100, 150, and 200 rpm), and sliding distance (30, 40, and 50 m). The material showed promising characteristics especially at high load, low speed, and high sliding distance. When comparing the respective influence of the three different parameters, the speed proved to be the most critical, this suggested the possible application of the biocomposite only for very low values of it. On the other hand, it was also elucidated that the presence and interfacial adhesion of the two fillers considerably hindered the formation of ploughing during wear test, despite the fact that degradation might be continuous and critical as far as loading progresses.