bluuebunny/crossref_metadata_2025 huggingface dataset:
The effect of exercise intention on exercise behavior in the post-epidemic era: The moderator role of openness personality and the mediated role of exercise-induced feeling
Authors: Ma Qi-Shuai , Yao Shu-Jun , Jia Hua-Rui
Published: December 2022

Objective

Based on the theory of planned behavior, this study introduced personality traits and exercise-induced feelings and other third variables, aiming to explore the mechanism of personality traits and exercise-induced feelings between exercise intention and exercise behavior, and explore the internal mechanism of promoting exercise behavior of junior high school students.

Methods

This research adopts the Exercise Intention Questionnaire, Simple Big Five Personality Scale, Exercise-induced Feeling Inventory and Exercise Rating Scale, from the three cities of Anhui province 1,166 junior high school students selected from the group psychological measurement, and uses the SPSS23.0 and Process plug-in exercise intention in exercise behavior analysis of the direct and indirect effect.

Results

The results showed that: (1) Exercise intention significantly positively predicted exercise behavior (β = 0.265, t = 4.261, p < 0.01). (2) The moderating effect of openness personality between exercise intention and exercise behavior was significant (β = 0.093, t = 4.431, p < 0.01). (3) Exercise-induced feelings has a significant mediating effect on the relationship between exercise intention and exercise behavior regulated by openness personality.

Conclusion

Exercise intention can effectively predict exercise behavior, and the prediction level is affected by openness personality, and the moderating effect of openness personality is partially realized through the mediating variable of exercise-induced feelings.
Can cultural tourism experience enhance cultural confidence? The evidence from Qingyuan Mountain
Authors: Lin Jian , Kang Yanxin , Hong Liping , Huang Yijun
Published: December 2022

A questionnaire survey was conducted among 600 visitors to the region using Qingyuan Mountain, a 5A picturesque location in Quanzhou City, Fujian Province, as the research site. A total of 489 valid questionnaires were received. The links between cultural involvement, cultural experience, cultural identity, cultural confidence, and cultural loyalty were experimentally examined using a structural equation modeling technique. The results showed that cultural experience was a mediating factor in the processes of the influence of cultural involvement on cultural identity and the influence of cultural involvement on cultural confidence, but the influence of cultural involvement on cultural identity and the influence of cultural involvement on cultural confidence were not supported. The study accordingly condenses theoretical contributions to academia and management insights for businesses.
How culturally unique are pandemic effects? Evaluating cultural similarities and differences in effects of age, biological sex, and political beliefs on COVID impacts
Authors: Conway Lucian Gideon , Woodard Shailee R. , Zubrod Alivia , Tiburcio Marcela , Martínez-Vélez Nora Angélica , Sorgente Angela , Lanz Margherita , Serido Joyce , Vosylis Rimantas , Fonseca Gabriela , Lep Žan , Li Lijun , Zupančič Maja , Crespo Carla , Relvas Ana Paula , Papageorgiou Kostas A. , Gianniou Foteini-Maria , Truhan Tayler , Mojtahedi Dara , Hull Sophie , Lilley Caroline , Canning Derry , Ulukök Esra , Akın Adnan , Massaccesi Claudia , Chiappini Emilio , Paracampo Riccardo , Korb Sebastian , Szaflarski Magdalena , Touré Almamy Amara , Camara Lansana Mady , Magassouba Aboubacar Sidiki , Doumbouya Abdoulaye , Mutlu Melis , Bozkurt Zeynep Nergiz , Grotkowski Karolina , Przepiórka Aneta M. , Corral-Frías Nadia Saraí , Watson David , Corona Espinosa Alejandro , Lucas Marc Yancy , Paleari Francesca Giorgia , Tchalova Kristina , Gregory Amy J. P. , Azrieli Talya , Bartz Jennifer A. , Farmer Harry , Goldberg Simon B. , Rosenkranz Melissa A. , Pickett Jennifer , Mackelprang Jessica L. , Graves Janessa M. , Orr Catherine , Balmores-Paulino Rozel
Published: December 2022

Despite being bio-epidemiological phenomena, the causes and effects of pandemics are culturally influenced in ways that go beyond national boundaries. However, they are often studied in isolated pockets, and this fact makes it difficult to parse the unique influence of specific cultural psychologies. To help fill in this gap, the present study applies existing cultural theories via linear mixed modeling to test the influence of unique cultural factors in a multi-national sample (that moves beyond Western nations) on the effects of age, biological sex, and political beliefs on pandemic outcomes that include adverse financial impacts, adverse resource impacts, adverse psychological impacts, and the health impacts of COVID. Our study spanned 19 nations (participant N = 14,133) and involved translations into 9 languages. Linear mixed models revealed similarities across cultures, with both young persons and women reporting worse outcomes from COVID across the multi-national sample. However, these effects were generally qualified by culture-specific variance, and overall more evidence emerged for effects unique to each culture than effects similar across cultures. Follow-up analyses suggested this cultural variability was consistent with models of pre-existing inequalities and socioecological stressors exacerbating the effects of the pandemic. Collectively, this evidence highlights the importance of developing culturally flexible models for understanding the cross-cultural nature of pandemic psychology beyond typical WEIRD approaches.
Correlation of safety behavior, handover quality, and risk perception: A cross-sectional study among Chinese psychiatric nurses
Authors: Liu Yakun , Teng Weiyu , Chen Chen , Zou Guiyuan
Published: December 2022

Background

Nurses’ safety behaviors played an important role in patients’ safety goal realization, and it varies from person to person. However, less research has explored the safety behavior level of psychiatric nurses and its influencing factors. Thus, this research aimed to assess the level of safety behavior and explore whether risk perception mediated the relationship between handover quality and safety behavior among psychiatric nurses.

Methods

A total of 186 registered psychiatric nurses in a Chinese hospital were recruited for this study, through the convenience sampling method. Handover quality, risk perception, and safety behavior were measured. Hayes’ PROCESS macro was used to evaluate the mediation of risk perception between handover quality and safety behavior.

Results

Scores of psychiatric nurses’ safety behaviors were (47.98 ± 7.45), and handover quality and risk perception could predict the variance of nurses’ safety behaviors. Risk perception could partially mediate between handover quality and nurses’ safety behaviors, and the value of the mediating effect was 49.17%.

Conclusion

Psychiatric nurses’ safety behaviors have a large promotion space. Therefore, healthcare professionals should endeavor to improve the handover quality of psychiatric nurses and decrease their risk perception, thereby promoting nurses’ safety behaviors.
Goal planning in mental health service delivery: A systematic integrative review
Authors: Stewart Victoria , McMillan Sara S. , Hu Jie , Ng Ricki , El-Den Sarira , O’Reilly Claire , Wheeler Amanda J.
Published: December 2022

Introduction

Goal planning is routinely employed in mental health service delivery to identify priorities for treatment and support the achievement and evaluation of outcomes. Previous systematic reviews of the literature have focused on the use of goal planning in a range of physical and cognitive disability settings, but there is a lack of information regarding how goal planning is used in mental healthcare.

Aims

This systematic integrative review aimed to understand the types of goals, effectiveness of goal planning, the experience of goal planning and barriers and facilitators to effective goal planning in mental healthcare settings.

Methods

Five databases were systematically searched using key terms related to mental health AND goal planning. The search was supplemented through citation chaining. Due to the heterogeneity of the studies, a narrative synthesis approach to data analysis was undertaken.

Results

Fifty-four studies were identified through the search of the literature following the PRISMA guidelines. Data was systematically extracted and thematically organized. There was a high level of heterogeneity among the studies, originating from a range of countries and with diverse characteristics and focus. Four themes emerged from the data analysis and included: (i) goal planning as a central aspect of interventions; (ii) types of goals planned; (iii) factors that influenced goal planning and/or attainment; and (iv) collaboration and concordance in goal planning.

Conclusion

This review found some support for the use of goal planning to improve outcomes in mental healthcare although there was no identified standardized approach to the use of goal planning. Individualized, recovery-oriented and collaborative goal planning was recommended but not always used in practice. Further research to understanding the most appropriate skills and training needed to support collaborative and effective goal planning is needed.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42020220595].
Safety and feasibility of performing robotic ureteroureterostomy and robotic pyeloplasty in infants
Authors: Suarez Arbelaez Maria Camila , Ghattas Yasmine , Raymo Adele , Isern Samantha , Alam Alireza , Nassau Daniel E. , Castellan Miguel
Published: December 2022

Introduction

Open surgery is considered the standard of care for pediatric urological procedures. Nonetheless, Robotic Assisted Laparoscopic Surgeries (RALS) have become increasingly popular in pediatrics as they allow for quicker recovery times, lower narcotic use, better cosmesis, and better intraoperative visibility. However, there are concerns regarding the usefulness of RALS in the infant population, as operating on smaller patients limits mobility of the robotic arms and can result in arm collisions.

Objective

The aim of this study was to compare the clinical and postoperative outcomes of infants undergoing robotic vs open pyeloplasty or ureteroureterostomy.

Materials and Methods

Retrospective study conducted between 2012 to 2022, 114 infants who underwent pyeloplasty (81 open pyeloplasty and 33 robotic pyeloplasty) and 21 who underwent ureteroureterostomy (9 open ureteroureterostomy and 12 robotic ureteroureterostomy) were included.

Results

Mean age at surgery in the pyeloplasty cohort was 4.81 ± 3.1 months in the open group, and 6.24 ± 2.6 months in the robotic group (p=0.13), and in the ureteroureterostomy cohort was 7.67 ± 3.16 months in the open group and 7.58 ± 2.75 months in the robotic group (p=0.95). Operative time was found to be shorter in robotic pyeloplasty and robotic ureteroureterostomy, when compared to the open approaches. Postoperative complications, its severity, and the surgical success were comparable among the pyeloplasty and ureteroureterostomy groups. Only 1(3%) complication related to the robotic technique was reported in the pyeloplasty cohort. The length of hospital stay was found to be similar between the ureteroureterostomy groups, while in the pyeloplasty cohort the robotic group showed a significant shorter hospital stay than the open group. Overall, the mean follow-up was greater than 12 months.

Conclusion

Our results demonstrated that robotic pyeloplasty and ureteroureterostomy performed in infants are feasible, safe, and durable procedures, with an additional benefit of reducing duration of operative time and hospital stay.
A fogszuvasodás előfordulása gyermekeknél - Pathfinder vizsgálatok Magyarországon 30 éven át
Authors: Szőke Judit , Petersen Poul Erik
Published: December 2022

Ismeretes, hogy az utóbbi évtizedekben lényegesen javult az európai gyermekek orális egészsége, mind a tej-, minda maradó fogak vonatkozásában csökkent a caries előfordulása. Ugyanakkor néhány kelet- és közép-európai országbanmég mindig óriási teher a szájüregi betegségek nagy száma.Jelen közlemény célja a hazai 5–6 és 12 éves gyermekek caries előfordulásának ismertetése, a fogszuvasodás trendjénekhosszú távon, 30 éven át történő nyomon követése a hazai pathfinder vizsgálatok tükrében. Az egymást követőreprezentatív keresztmetszeti vizsgálatokat 1985 és 1917 között (1991, 1996, 2001, 2018, 2013) a WHO pathfindermethodology szerint végeztük. Az epidemiológiai adatgyűjtés vizuális klinikai vizsgálatokkal történt.Ezen időszak alatt az 5–6 éves ép fogú gyerekek aránya 30%-ról 2017-ben 43,8%-ra nőtt, a vidéki helyszíneken mindigalacsonyabb értékekkel. 2017-ben a városi érték 49,9%, a vidéki pedig 34,6% (p < 0,001), a dmft országos átlagértéke3,5. A tej frontfogak caries előfordulása az évek során kissé csökkent, legutóbb 21,6% volt. A 12 évesek caries frekvenciájaés intenzitása folyamatosan csökkenő trendet mutat, az 1985-ben mért 92,5%-ról 55,3%-ra, illetve 5,0 DMFT-ről2,3-ra javult (p < 0,001). Jelentős eredmény, hogy az ép fogazattal rendelkező gyerekek aránya 7,5%-ról 44,7%-ra nőtt.Azonban az utóbbi évtizedben a javulás intenzitása lassult, s egyidejűleg a D komponens értékének növekedése figyelhetőmeg. A Significant Caries Index (SIC index) értéke 5–6 éveseknél 8,43, 12 éveseknél 5,23. Az eredmények azt tükrözik,hogy országosan változatlanul nagy területi különbségek vannak a városi és a hátrányosabb helyzetben lévő vidékigyerekek orális egészségi állapotában. A care index 30%-os ellátottsági szintet jelez, tehát nagy a kezelési szükséglet.A legutóbbi adatok alapján megállapítható, hogy Magyarország az 5–6 évesek vonatkozásában a WHO/FDI 2000-rekitűzött globális céljait sem érte még el. A 12 éveseknél a globális célkitűzések megvalósultak ugyan, de az európaiaknem. Irreálisnak tűnik, hogy hazánk megfeleljen a 2020-as WHO/FDI/IADR elvárásoknak. Sürgető népegészségügyifeladat országos komplex prevenciós programok szervezése, konkrét fogászati célkitűzések, módszerek és feladatokmegjelölésével. Élvezzen prioritást a széles körű minőségi szájápolás, a fluoridok effektív alkalmazása és az iskolafogászatrevitalizálása.
A Platelet Rich Fibrin szerepe a fogászatban és a maxillofaciális sebészetben
Authors: Major Martin , Trimmel Bálint , Polyák Melinda , Kovács Dávid , Szabó György
Published: December 2022

A PRF (Platelet Rich Fibrin) előállításának módszerét 2000-ben dolgozták ki, a trombocyta koncentrátumok második generációjához tartozik. Számos klinikai vizsgálat igazolta hatékonyságát, kombinálva különböző csontpótló anyagokkal.Elkészítéséhez a páciens saját vérét, alvadásgátló hozzáadása nélkül a kidolgozott protokoll szerint centrifugálják. A fo- lyamateredményeként leukocytákban és trombocytákban gazdag fibrin-alvadék nyerhető, mely extracelluláris mátrixként szolgál. A fehérvérsejtek és vérlemezkék növekedési faktorai lassan (2–3 hét) szabadulnak fel, így kedvezően befolyásolják a sebgyógyulást. A szerzők áttekintik a főbb irodalmi adatokat, és beszámolnak a PRF fogászati, dentoalveoláris és maxilofaciális sebészeti alkalmazásának lehetőségeiről (implantológia, csontpótlás, dentoalveoláris sebészet, parodontológia, arcüregzárás, sinus elevatio, osteonecrosis, endodontia).
Activation Fine-Tuning of Convolutional Neural Networks for Improved Input Attribution Based on Class Activation Maps
Authors: Han Sungmin , Lee Jeonghyun , Lee Sangkyun
Published: December 2022

Model induction is one of the most popular methods to extract information to better understand AI’s decisions by estimating the contribution of input features for a class of interest. However, we found a potential issue: most model induction methods, especially those that compute class activation maps, rely on arbitrary thresholding to mute some of their computed attribution scores, which can cause the severe quality degradation of model induction. Therefore, we propose a new threshold fine-tuning (TFT) procedure to enhance the quality of input attribution based on model induction. Our TFT replaces arbitrary thresholding with an iterative procedure to find the optimal cut-off threshold value of input attribution scores using a new quality metric. Furthermore, to remove the burden of computing optimal threshold values on a per-input basis, we suggest an activation fine-tuning (AFT) framework using a tuner network attached to the original convolutional neural network (CNN), retraining the tuner-attached network with auxiliary data produced by TFT. The purpose of the tuner network is to make the activations of the original CNN less noisy and thus better suited for computing input attribution scores based on class activation maps from the activations. In our experiments, we show that the per-input optimal thresholding of attribution scores using TFT can significantly improve the quality of input attribution, and CNNs fine-tuned with our AFT can be used to produce improved input attribution matching the quality of TFT-tuned input attribution without requiring costly per-input threshold optimization.
Numerical Simulation of Heat Transfer Performance of a Dimpled Tubular Heat Exchanger
Authors: Wang Zunce , Wang Yimin , Zhang Jinglong , Li Sen , Xu Yan
Published: December 2022

The processing of dimple on the outer wall of tube will produce corresponding protrusion dimple on the inner wall. The turbulent flow and heat transfer performance of a tubular heat exchanger containing a dimpled inner tube is studied numerically. The results show that the main reason for the enhancement of heat transfer ability of the dimple is the flow vortex in the concave dimple and the shock to the wall induced by the protrusion dimple. Compared with the smooth wall of the tube, the maximum enhancement of heat transfer was 1.94 times in concave dimple and 2.74 times in protrusion dimple. By comparing the heat transfer performance, flow resistance, and comprehensive heat transfer factor of the tube and shell of different sizes of exchange heat pipe, it is determined that the combination of inner and outer wall dimple size of 10–15 mm is a structure with better comprehensive heat transfer performance.
Identification and Validation of Cuproptosis-Related LncRNA Signatures in the Prognosis and Immunotherapy of Clear Cell Renal Cell Carcinoma Using Machine Learning
Authors: Bai Zhixun , Lu Jing , Chen Anjian , Zheng Xiang , Wu Mingsong , Tan Zhouke , Xie Jian
Published: December 2022

(1) Objective: We aimed to mine cuproptosis-related LncRNAs with prognostic value and construct a corresponding prognostic model using machine learning. External validation of the model was performed in the ICGC database and in multiple renal cancer cell lines via qPCR. (2) Methods: TCGA and ICGC cohorts related to renal clear cell carcinoma were included. GO and KEGG analyses were conducted to determine the biological significance of differentially expressed cuproptosis-related LncRNAs (CRLRs). Machine learning (LASSO), Kaplan–Meier, and Cox analyses were conducted to determine the prognostic genes. The tumor microenvironment and tumor mutation load were further studied. TIDE and IC50 were used to evaluate the response to immunotherapy, a risk model of LncRNAs related to the cuproptosis genes was established, and the ability of this model was verified in an external independent ICGC cohort. LncRNAs were identified in normal HK-2 cells and verified in four renal cell lines via qPCR. (3) Results: We obtained 280 CRLRs and identified 66 LncRNAs included in the TCGA-KIRC cohort. Then, three hub LncRNAs (AC026401.3, FOXD2−AS1, and LASTR), which were over-expressed in the four ccRCC cell lines compared with the human renal cortex proximal tubule epithelial cell line HK-2, were identified. In the ICGC database, the expression of FOXD2-AS1 and LASTR was consistent with the qPCR and TCGA-KIRC. The results also indicated that patients with low-risk ccRCC—stratified by tumor-node metastasis stage, sex, and tumor grade—had significantly better overall survival than those with high-risk ccRCC. The predictive algorithm showed that, according to the three CRLR models, the low-risk group was more sensitive to nine target drugs (A.443654, A.770041, ABT.888, AG.014699, AMG.706, ATRA, AP.24534, axitinib, and AZ628), based on the estimated half-maximal inhibitory concentrations. In contrast, the high-risk group was more sensitive to ABT.263 and AKT inhibitors VIII and AS601245. Using the CRLR models, the correlation between the tumor immune microenvironment and cancer immunotherapy response revealed that high-risk patients are more likely to respond to immunotherapy than low-risk patients. In terms of immune marker levels, there were significant differences between the high- and low-risk groups. A high TMB score in the high-risk CRLR group was associated with worse survival, which could be a prognostic factor for KIRC. (4) Conclusions: This study elucidates the core cuproptosis-related LncRNAs, FOXD2−AS1, AC026401.3, and LASTR, in terms of potential predictive value, immunotherapeutic strategy, and outcome of ccRCC.
Ferromagnetic Biochar Prepared from Hydrothermally Modified Calcined Mango Seeds for Fenton-like Degradation of Indigo Carmine
Authors: Bopda Aurelien , Mafo Sandrale Grace Mokue , Ndongmo Josiane Nguimatsia , Kenda Georges Teikam , Fotsop Cyrille Ghislain , Kuete Idris-Hermann Tiotsop , Ngakou Christian Sadeu , Tchuifon Donald Raoul Tchuifon , Tamo Arnaud Kamdem , Nche George Ndifor-Angwafor , Anagho Solomon Gabche
Published: December 2022

Biochar and ferromagnetic biochar obtained from the pyrolysis of dried mango seeds and modified using a hydrothermal method were used as catalyst for the heterogeneous degradation of indigo carmine in an aqueous medium. These prepared biochars were characterized using different techniques: Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). The analyses of the results revealed the presence of iron oxide in the form of magnetite (Fe3O4) in the catalyst. The catalytic tests carried out with this composite material showed a significant degradation of indigo carmine. The maximum degradation of indigo carmine in the aqueous solution was reached after 240 min of agitation. The Fenton degradation process using irradiation with a 100 W electric lamp and hydrogen peroxide (concentration 4 mol/L) showed the best results at pH = 3. From this study, it emerged that the second-order kinetic model better described the degradation process, and it gave lower half-lives compared to those obtained with the first-order kinetic law. The study also showed that ferromagnetic biochar could be prepared from mango seeds and used for the degradation of indigo carmine in an aqueous solution.
Immobilization of Glucose Oxidase on Glutathione Capped CdTe Quantum Dots for Bioenergy Generation
Authors: Lozano-López Daniel , Galván-Valencia Marisol , Rojas-de Soto Ivone , Escalona-Villalpando Ricardo A. , Ledesma-García Janet , Durón-Torres Sergio
Published: December 2022

An efficient immobilization of Glucose oxidase (GOx) on an appropriate substrate is one of the main challenges of developing fuel cells that allow energy to be obtained from renewable substrates such as carbohydrates in physiological environments. The research importance of biofuel cells relies on their experimental robustness and high compatibility with biological organisms such as tissues or the bloodstream with the aim of obtaining electrical energy even from living systems. In this work, we report the use of 5,10,15,20 tetrakis (1-methyl-4-pyridinium) porphyrin and glutathione capped CdTe Quantum dots (GSH-CdTeQD) as a support matrix for the immobilization of GOx on carbon surfaces. Fluorescent GSH-CdTeQD particles were synthesized and their characterization by UV-Vis spectrophotometry showed a particle size between 5–7 nm, which was confirmed by DLS and TEM measurements. Graphite and Toray paper electrodes were modified by a drop coating of porphyrin, GSH-CdTeQD and GOx, and their electrochemical activity toward glucose oxidation was evaluated by cyclic voltammetry, chronoamperometry and electrochemical impedance spectroscopy. Additionally, GOx modified electrode activity was explored by scanning electrochemical microscopy, finding that near to 70% of the surface was covered with active enzyme. The modified electrodes showed a glucose sensitivity of 0.58 ± 0.01 μA/mM and an apparent Michaelis constant of 7.8 mM. The addition of BSA blocking protein maintained the current response of common interferent molecules such as ascorbic acid (AA) with less than a 5% of interference percentage. Finally, the complex electrodes were employed as anodes in a microfluidic biofuel cell (μBFC) in order to evaluate the performance in energy production. The enzymatic anodes used in the μBFC allowed us to obtain a current density of 7.53 mAcm−2 at the maximum power density of 2.30 mWcm−2; an open circuit potential of 0.57 V was observed in the biofuel cell. The results obtained suggest that the support matrix porphyrin and GSH-CdTeQD is appropriate to immobilize GOx while preserving the enzyme’s catalytic activity. The reported electrode arrangement is a viable option for bioenergy production and/or glucose quantification.
Evaluation of Atypical Chemokine Receptor Expression in T Cell Subsets
Authors: Pacheco Messias Oliveira , Rocha Fernanda Agostini , Aloia Thiago Pinheiro Arrais , Marti Luciana Cavalheiro
Published: December 2022

Chemokines are molecules that pertain to a family of small cytokines and can generate cell chemotaxis through the interaction with their receptors. Chemokines can trigger signaling via conventional G-protein-coupled receptors or through atypical chemokine receptors. Currently, four atypical chemokine receptors have been are described (ACKR1, ACKR2, ACKR3 and ACKR4). ACKRs are expressed in various cells and tissues, including T lymphocytes. These receptors’ main function is related to the internalization and degradation of chemokines, as well as to the inflammation control. However, the expression of these receptors in human T lymphocytes is unclear in the literature. The objective of this study was to evaluate the expression of ACKRs in different subpopulations of T lymphocytes. For this, peripheral blood from healthy donors was used to analyze the expression of ACKR2, ACKR3 and ACKR4 by immunophenotyping CD4, CD8 T lymphocytes and, in their subsets, naive, transition and memory. Results obtained in this study demonstrated that ACKR2, ACKR3 and ACKR4 receptors were expressed by T lymphocytes subsets in different proportions. These receptors are highly expressed in the cytoplasmic milieu of all subsets of T lymphocytes, therefore suggesting that their expression in plasma membrane is regulated after transcription, and it must be dependent on a stimulus, which was not identified in our study. Thus, regarding ACKRs function as scavenger receptors, at least for the ACKR3, this function does not impair the chemotaxis exert for their ligand compared to the typical counterpart receptor.
An Important Step in Neuroscience: Camillo Golgi and His Discoveries
Authors: Saceleanu Vicentiu Mircea , Covache-Busuioc Razvan-Adrian , Costin Horia-Petre , Glavan Luca-Andrei , Ciurea Alexandru Vlad
Published: December 2022

Camillo Golgi (Figure 1) is one of the most prestigious personalities of modern medicine [...]
D4Z4 Methylation Levels Combined with a Machine Learning Pipeline Highlight Single CpG Sites as Discriminating Biomarkers for FSHD Patients
Authors: Caputo Valerio , Megalizzi Domenica , Fabrizio Carlo , Termine Andrea , Colantoni Luca , Bax Cristina , Gimenez Juliette , Monforte Mauro , Tasca Giorgio , Ricci Enzo , Caltagirone Carlo , Giardina Emiliano , Cascella Raffaella , Strafella Claudia
Published: December 2022

The study describes a protocol for methylation analysis integrated with Machine Learning (ML) algorithms developed to classify Facio-Scapulo-Humeral Dystrophy (FSHD) subjects. The DNA methylation levels of two D4Z4 regions (DR1 and DUX4-PAS) were assessed by an in-house protocol based on bisulfite sequencing and capillary electrophoresis, followed by statistical and ML analyses. The study involved two independent cohorts, namely a training group of 133 patients with clinical signs of FSHD and 150 healthy controls (CTRL) and a testing set of 27 FSHD patients and 25 CTRL. As expected, FSHD patients showed significantly reduced methylation levels compared to CTRL. We utilized single CpG sites to develop a ML pipeline able to discriminate FSHD subjects. The model identified four CpGs sites as the most relevant for the discrimination of FSHD subjects and showed high metrics values (accuracy: 0.94, sensitivity: 0.93, specificity: 0.96). Two additional models were developed to differentiate patients with lower D4Z4 size and patients who might carry pathogenic variants in FSHD genes, respectively. Overall, the present model enables an accurate classification of FSHD patients, providing additional evidence for DNA methylation as a powerful disease biomarker that could be employed for prioritizing subjects to be tested for FSHD.
Nuclear Shape-Shifters: Lipid and Protein Dynamics at the Nuclear Envelope
Authors: Antonin Wolfram , Siniossoglou Symeon
Published: December 2022

The nuclear envelope constitutes a selective barrier that segregates chromatin into the nucleus of eukaryotic cells [...]
UC-BSCs Exosomes Regulate Th17/Treg Balance in Patients with Systemic Lupus Erythematosus via miR-19b/KLF13
Authors: Tu Jianxin , Zheng Nan , Mao Chentong , Liu Shan , Zhang Hongxing , Sun Li
Published: December 2022

Umbilical cord blood mesenchymal stem cells (UC-BSCs) are cells with low immunogenicity and differentiation potential, and the transfer of exosomes carried by UC-BSCs can regulate innate and adaptive immunity and affect immune homeostasis. This is an area of focus for autoimmune illnesses such as systemic lupus erythematosus (SLE). The target of this research was to investigate the immunomodulatory effect of exosomes produced from mesenchymal stem cells on SLE and its mechanism. After isolation of peripheral blood mononuclear cells (PBMC) from the SLE group and healthy group and treatment of SLE-derived PBMCs with UC-BSC-derived exosomes, the mRNA levels of corresponding factors in cells under different treatments were determined by RT-PCR, Th17/Treg content was analyzed by FCM (flow cytometry), and the targeted binding of microRNA-19b (miR-19b) to KLF13 was identified by in vitro experiments and bioinformatics analysis. The findings demonstrated that PBMC cells from SLE patients had higher proportions of Th17 subsets than the control group, whereas Treg subgroups with lower percentages were discovered. miR-19b’s expression level was markedly reduced, which was inversely associated to the concentration of KLF13. In vitro experiments show that UC-BSC-derived exosome treatment can target KLF13 expression by increasing the miR-19b level, thereby regulating Th17/Treg balance and inhibiting the expression of inflammatory factors. According to the study’s findings, SLE patients have dysregulated expression of the genes miR-19b and KLF13, and UC-BSC exosomes could regulate Th17/Treg cell balance and inflammatory factor expression in SLE patients through miR-19b/KLF13.
Filled Sb-Based Skutterudites from 1996–2022
Authors: Rogl Gerda , Rogl Peter Franz
Published: December 2022

In the present review the focus is set on filled antimony-based skutterudites as they are among the most promising TE materials. Thermoelectric properties (at 300 K and 800 K) of more than 1200 compositions from more than 250 publications from 1996 to 2022 were collected and evaluated. In various figures the dependence of the peak ZT for single-filled, double-filled and multi-filled compounds of p- and n-type skutterudites on the publishing year, the peak temperature, electrical resistivity, thermal and lattice thermal conductivity, the power factor and the fillers are displayed. Together with plots of electrical resistivity versus Seebeck coefficient and especially thermal conductivity versus power factor these evaluations etc. may help to find the ideal skutterudite material for practical applications.
Smoking Cessation after Cancer Diagnosis and Enhanced Therapy Response: Mechanisms and Significance
Authors: Chellappan Srikumar
Published: December 2022

The adverse effects of smoking on human health have been recognized for several decades, especially in the context of cancer. The ability of tobacco smoke components, including tobacco-specific carcinogens and additive compounds such as nicotine, to initiate or promote tumor growth have been described in hundreds of studies. These investigations have revealed the tumor-promoting activities of nicotine and other tobacco smoke components and have also recognized the ability of these agents to suppress the efficacy of cancer therapy; it is now clear that smoking can reduce the efficacy of most of the widely used therapeutic modalities, including immunotherapy, radiation therapy, and chemotherapy. Several studies examined if continued smoking after cancer diagnosis affected therapy response; it was found that while never smokers or non-smokers had the best response to therapy, those who quit smoking at the time of diagnosis had higher overall survival and reduced side-effects than those who continued to smoke. These studies also revealed the multiple mechanisms via which smoking enhances the growth and survival of tumors while suppressing therapy-induced cell death. In conclusion, smoking cessation during the course of cancer therapy markedly increases the chances of survival and the quality of life.
Evidence of Critical Dynamics in Movements of Bees inside a Hive
Authors: Shpurov Ivan , Froese Tom
Published: December 2022

Social insects such as honey bees exhibit complex behavioral patterns, and their distributed behavioral coordination enables decision-making at the colony level. It has, therefore, been proposed that a high-level description of their collective behavior might share commonalities with the dynamics of neural processes in brains. Here, we investigated this proposal by focusing on the possibility that brains are poised at the edge of a critical phase transition and that such a state is enabling increased computational power and adaptability. We applied mathematical tools developed in computational neuroscience to a dataset of bee movement trajectories that were recorded within the hive during the course of many days. We found that certain characteristics of the activity of the bee hive system are consistent with the Ising model when it operates at a critical temperature, and that the system’s behavioral dynamics share features with the human brain in the resting state.
Universal Non-Extensive Statistical Physics Temporal Pattern of Major Subduction Zone Aftershock Sequences
Authors: Anyfadi Eleni-Apostolia , Avgerinou Sophia-Ekaterini , Michas Georgios , Vallianatos Filippos
Published: December 2022

Large subduction-zone earthquakes generate long-lasting and wide-spread aftershock sequences. The physical and statistical patterns of these aftershock sequences are of considerable importance for better understanding earthquake dynamics and for seismic hazard assessments and earthquake risk mitigation. In this work, we analyzed the statistical properties of 42 aftershock sequences in terms of their temporal evolution. These aftershock sequences followed recent large subduction-zone earthquakes of M ≥ 7.0 with focal depths less than 70 km that have occurred worldwide since 1976. Their temporal properties were analyzed by investigating the probability distribution of the interevent times between successive aftershocks in terms of non-extensive statistical physics (NESP). We demonstrate the presence of a crossover behavior from power-law (q ≠ 1) to exponential (q = 1) scaling for greater interevent times. The estimated entropic q-values characterizing the observed distributions range from 1.67 to 1.83. The q-exponential behavior, along with the crossover behavior observed for greater interevent times, are further discussed in terms of superstatistics and in view of a stochastic mechanism with memory effects, which could generate the observed scaling patterns of the interevent time evolution in earthquake aftershock sequences.
A Review of Fuel Cell Powertrains for Long-Haul Heavy-Duty Vehicles: Technology, Hydrogen, Energy and Thermal Management Solutions
Authors: Pardhi Shantanu , Chakraborty Sajib , Tran Dai-Duong , El Baghdadi Mohamed , Wilkins Steven , Hegazy Omar
Published: December 2022

Long-haul heavy-duty vehicles, including trucks and coaches, contribute to a substantial portion of the modern-day European carbon footprint and pose a major challenge in emissions reduction due to their energy-intensive usage. Depending on the hydrogen fuel source, the use of fuel cell electric vehicles (FCEV) for long-haul applications has shown significant potential in reducing road freight CO2 emissions until the possible maturity of future long-distance battery-electric mobility. Fuel cell heavy-duty (HD) propulsion presents some specific characteristics, advantages and operating constraints, along with the notable possibility of gains in powertrain efficiency and usability through improved system design and intelligent onboard energy and thermal management. This paper provides an overview of the FCEV powertrain topology suited for long-haul HD applications, their operating limitations, cooling requirements, waste heat recovery techniques, state-of-the-art in powertrain control, energy and thermal management strategies and over-the-air route data based predictive powertrain management including V2X connectivity. A case study simulation analysis of an HD 40-tonne FCEV truck is also presented, focusing on the comparison of powertrain losses and energy expenditures in different subsystems while running on VECTO Regional delivery and Longhaul cycles. The importance of hydrogen fuel production pathways, onboard storage approaches, refuelling and safety standards, and fleet management is also discussed. Through a comprehensive review of the H2 fuel cell powertrain technology, intelligent energy management, thermal management requirements and strategies, and challenges in hydrogen production, storage and refuelling, this article aims at helping stakeholders in the promotion and integration of H2 FCEV technology towards road freight decarbonisation.
Development of Ultra-High-Efficiency Medium-Capacity Chillers with Two-Stage Compression and Interstage Vapor Injection Technologies
Authors: Zhang Zhiping , Qiu Hongye , Li Dantong , He Zhilong , Xing Ziwen , Wu Lijian
Published: December 2022

Chillers are widely used in commercial buildings for air conditioning, and their energy consumption is the main contribution to the building’s carbon emissions. Currently, the COPs of small- and medium-capacity screw chillers are still generally lower than 6.5, whereas large-capacity commercial centrifugal chillers have achieved an ultra-high energy-efficiency level of COP ≥ 7.0. To achieve an ultra-high energy efficiency of COP ≥ 6.5 in medium-capacity chillers, the authors developed a 200 RT screw chiller by adopting the technologies of two-stage compression and interstage vapor injection. The whole development process, including the design, simulation, analysis, and experiment, is presented in this paper. It was found that the two-stage compression technology could effectively boost the performance of the chiller’s compressor to a maximum volumetric and adiabatic efficiency of 99% and 80%, respectively. With the interstage vapor injection technology, the chiller’s cooling capacity and COP were increased by more than 11% and 8%, respectively. When the use of these two technologies was combined, the maximum COP of the chiller reached 7.17. Additionally, under these working conditions, the COP and integrated part-load value (IPLV) were 6.74 and 10.04, respectively. In all, the combination use of vapor injection and two-stage compression technologies shows great potential to improve the performance of chillers. The work and conclusions described here might provide an effective reference for the future development of high-efficiency small- and medium-capacity screw chillers.
Impact of Renewable Energy Sources and Nuclear Energy on CO2 Emissions Reductions—The Case of the EU Countries
Authors: Petruška Igor , Litavcová Eva , Chovancová Jana
Published: December 2022

The aim of this work is to analyse the dependence of carbon dioxide (CO2) emissions on total energy consumption, the energy produced from renewable sources, the energy produced in nuclear power plants and the gross domestic product (GDP) in 22 European countries, over the period 1992–2019. The fully modified ordinary least squares model (FMOLS) and dynamic OLS (DOLS) were used to estimate the long-term cointegration relationship between the variables. First differenced (FD) general moments methods (GMM) were used in the estimation of short-run relationship dynamics. The results suggest that energy produced from renewable sources causes a reduction in CO2 emissions per capita. On the other hand, total energy consumption increases CO2 emissions in the long run. Although the mitigation effect of nuclear power was not found to be significant across the entire block of countries studied, a closer look at countries utilising nuclear energy reveals that nuclear energy positively affects the reduction in CO2 emissions. Economic growth also has a positive effect on the reduction in CO2 emissions, which confirms the decoupling of economic development from environmental impacts. These findings are crucial for understanding the causality between these variables and the adoption of new or revision of existing policies and strategies promoting the carbon-neutral and green economy at the EU and national level.
Decision on Mixed Trading between Medium- and Long-Term Markets and Spot Markets for Electricity Sales Companies under New Electricity Reform Policies
Authors: Wang Hui , Wang Congcong , Zhao Wenhui
Published: December 2022

The introduction of the new round of electricity reform policies has made the electricity sales companies’ trading environment increasingly complex. In the medium- and long-term market and spot market, following the new policy-oriented optimization of trading decisions is the focus of electricity sales companies. The main objective of this study is to consider the impact of the latest policies of China’s current electricity reform on each subject of electricity trading and to propose a method for electricity sales companies to make optimal decisions on renewable energy source (RES) power and conventional energy source (CES) power mixed with power trading in the medium- and long-term and spot markets to improve the efficiency of electricity market trading, promoting the consumption of renewable energy and helping the synergistic development of the electricity market and the tradable green certificate (TGC) market. This paper first discusses the impact of the new electricity reform policies on the transactions of various subjects in the electricity market and constructs the model of the consumer utility function, the profit model of an electricity sales company, and the profit model of power generators with energy storage. Considering the complex power supply and demand relationship among the various subjects of the electricity market, a game model is established for the decision on mixed trading between the medium- and long-term market, the spot market, and the tradable green certificate market to minimize the comprehensive power purchase cost of an electricity sales company. To reduce the decision-making risk caused by the uncertainty of spot price, the prophet model is used to predict the spot price; finally, through the analysis of the decision-making model of the electricity sales companies, the optimal transaction decisions of the electricity sales companies in different trading periods and different scenarios are solved. The test results show that the proposed model can significantly improve the profitability of the electricity sales companies and provide a decision-making reference for electricity sales companies to participate in the medium- and long-term market and spot market.
The Influence of Various Solar Radiations on the Efficiency of a Photovoltaic Solar Module Integrated with a Passive Cooling System
Authors: Rubaiee Saeed , Fazal M. A.
Published: December 2022

The thermal regulation of a silicon photovoltaic (PV) solar system is essential as the module surface temperature beyond 25 °C deteriorates its Power Conversion Efficiency (PCE). The intensity of solar radiation seems to have a crucial impact on the PCE of a PV solar system. The present study aims to assess the effect of solar radiation variations on the PCEs of PV modules integrated with and without passive cooling systems. The used passive cooling systems are (a) multi-pipe copper frame filled with Phase Change Material (PCM) and (b) multi-pipe copper frame filled with ZnO-doped PCM. The tests were conducted at the University of Jeddah in the month of March at various local times. The results show that the ambient and module surface temperatures are directly dominated by solar radiations. The conventional PV solar system presents a higher module surface temperature as compared to that of a PV system integrated with ZnO/PCM. The enhanced module surface temperature decreases the open circuit voltage (Voc) and slightly increases the short circuit current (Isc) indicating its reduced electric efficiency.
Cork Oak Production Estimation Using a Mask R-CNN
Authors: Guimarães André , Valério Maria , Fidalgo Beatriz , Salas-Gonzalez Raúl , Pereira Carlos , Mendes Mateus
Published: December 2022

Cork is a versatile natural material. It can be used as an insulator in construction, among many other applications. For good forest management of cork oaks, forest owners need to calculate the volume of cork periodically. This will allow them to choose the right time to harvest the cork. The traditional method is laborious and time consuming. The present work aims to automate the process of calculating the trunk area of a cork oak from which cork is extracted. Through this calculation, it will be possible to estimate the volume of cork produced before the stripping process. A deep neural network, Mask R-CNN, and a machine learning algorithm are used. A dataset of images of cork oaks was created, where targets of known dimensions were fixed on the trunks. The Mask R-CNN was trained to recognize targets cork regions, and so the area of cork was estimated based on the target dimensions. Preliminary results show that the model presents a good performance in the recognition of targets and trunks, registering a mAP@0.7 of 0.96. After obtaining the mask results, three machine learning models were trained to estimate the cork volume based on the area and biometric parameters of the tree. The results showed that a support vector machine produced an average error of 8.75%, which is within the error margins obtained using traditional methods.