bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Approach to the Allocation of Multidimensional Resources in Production Processes
Authors: Wikarek Jarosław , Sitek Paweł
Published: July 2022

Modern technologies in the field of automation, robotics and IT have significantly changed the face of modern production systems. In particular, the use of AVG, PLC, mobile robots, RFID, IoT, etc. results in modern production processes being characterized by, among others, shortened production cycles and supply chains, reduced production costs, increased product quality and reliability, etc. Moreover, the application of these technologies requires a new definition and methods of using production resources. Most often these are resources that are characterized by many functionalities, the so-called multidimensional resources, which can be configured, remotely controlled, updated, etc., and their use in many cases enables the self-optimization and self-organization of the production system. The article presents the problem of allocation and control of multidimensional resources in production processes. The proprietary formal model of the problem is proposed, as well as how to use it in both proactive and reactive modes. A procedure for reducing the size of the modeled problem is also proposed, the use of which enables a two-fold reduction in the number of constraints and even a fifty-fold reduction in the number of decision variables of the proposed model. This results in an almost hundredfold reduction in computation time for the considered data instances. An original hybrid approach is used to implement the model, which enables the integration of mathematical programming (MP) and programming in constrained logic (CLP). Model data and parameters have been saved as facts.
A Multi-Analytical Approach to Infer Mineral–Microbial Interactions Applied to Petroglyph Sites in the Negev Desert of Israel
Authors: Rabbachin Laura , Piñar Guadalupe , Nir Irit , Kushmaro Ariel , Pavan Mariela J. , Eitenberger Elisabeth , Waldherr Monika , Graf Alexandra , Sterflinger Katja
Published: July 2022

Petroglyph sites exist all over the world. They are one of the earliest forms of mankind’s expression and a precursor to art. Despite their outstanding value, comprehensive research on conservation and preservation of rock art is minimal, especially as related to biodeterioration. For this reason, the main objective of this study was to explore the factors involved in the degradation of petroglyph sites in the Negev desert of Israel, with a focus on biodegradation processes. Through the use of culture-independent microbiological methods (metagenomics), we characterized the microbiomes of the samples, finding they were dominated by bacterial communities, in particular taxa of Actinobacteria and Cyanobacteria, with resistance to radiation and desiccation. By means of XRF and Raman spectroscopies, we defined the composition of the stone (calcite and quartz) and the dark crust (clay minerals with Mn and Fe oxides), unveiling the presence of carotenoids, indicative of biological colonization. Optical microscopy and SEM–EDX analyses on thin sections highlighted patterns of weathering, possibly connected to the presence of biodeteriorative microorganisms that leach the calcareous matrix from the bedrock and mobilize metal cations from the black varnish for metabolic processes, slowly weathering it.
Coping with Access Difficulties and Absenteeism through Data Visualization: A Case Study from a Rural Vocational School in Northern Greece
Authors: Samaras Christos , Tsoni Rozita , Paxinou Evgenia , Kotsiantis Sotiris , Verykios Vassilios S.
Published: July 2022

Absenteeism and early school leaving (ESL) constitute two main problems in education with a significant impact on adolescents’ life. Early leavers from education and training may face considerable difficulties in the labor market later as adults. Motivated by the necessity of minimizing this phenomenon, we developed a novel application that uses big data, generated from a student attendance management system in a vocational senior high school in Greece. This application first automatically conducts data preprocessing and data transformation and saves the processed data on a cloud data warehouse. Then, an online analytical processing (OLAP) analysis is performed, resulting in a real-time visualization that provides a variety of different graphs. In this study, we demonstrate the need for real-time visualization of the analyzed data. Such a type of presentation provides information on the spot regarding potential early leavers’ behavior, helping school administrators gain time for prompt and effective actions. Through the data processing and analysis, the application provides instructors with constant information, in addition to those acquired by the formal student attendance management systems. Our research provides indicative evidence in favor of the use of such applications, as by adequately reacting to the observed patterns in real-time, we observed a significant decrease in students’ unnecessary absences and a reduction of the ELS phenomenon in a three-year school period.
Modernization of Heavy Loaded Tram Radial Effect on Noise and Vibration
Authors: Papánová Zuzana , Papán Daniel , Ižvolt Libor , Dobeš Peter
Published: July 2022

The noise and vibration that cause deterioration of comfort at specific locations can be reduced by modernisation of tram lines in some large cities where dense development surrounds tram lines. The paper deals with the impact of noise and vibration produced by tram traffic. Its aim was to verify whether the modernisation of one of the busiest tram lines in the capital of Slovakia had an impact on the reduction of noise and vibration emissions arising in its surroundings. The paper analysed experimental measurements conducted at the busiest locations of the studied tram line, focusing on the parameters LAeq and vrms. The methodology for reducing the adverse effects of noise and vibration is based on the modernisation of the tramway line, characterised in detail in the paper. The presentation and analysis of the measurement results are followed by conclusions that underline the importance of reducing noise and vibration emissions generated by tram traffic by modernising the tram line network.
Analysis of Vertical Wind Shear Effects on Offshore Wind Energy Prediction Accuracy Applying Rotor Equivalent Wind Speed and the Relationship with Atmospheric Stability
Authors: Ryu Geon Hwa , Kim Dongjin , Kim Dae-Young , Kim Young-Gon , Kwak Sung Jo , Choi Man Soo , Jeon Wonbae , Kim Bum-Suk , Moon Chae-Joo
Published: July 2022

If the wind speed that passed through a wind turbine rotor disk area is constant, the hub height wind speed (HHWS) could be representative of the wind speed over the rotor disk area. However, this assumption cannot be applied to the large wind turbine, because of the wind shear effect by atmospheric stability. This is because the hub height wind speed cannot represent the vertical wind shear effect from the aerodynamics characteristic on the wind turbine. Using SCADA and offshore LiDAR observation data of the Anholt offshore wind farm, it is investigated whether the rotor equivalent wind speed (REWS) introduced in IEC61400-12-1 can contribute to the improvement of power output forecasting accuracy. The weighted value by separated sector area and vertical wind shear effect by difference between heights can explain the role of energy flux and atmospheric stability on the exact wind energy calculation. The commercial CFD model WindSim is used to calculate power production according to the HHWS and the REWS, and to compare them with the actual AEP of the local wind farm. The classification of atmospheric stability is carried out by Richardson number, which well represents the thermal and physical properties of the atmosphere below the atmospheric boundary layer, along with the wind shear coefficient and turbulence intensity. When atmospheric stability was classified by each stability index, the REWS-based predicted power output was sometimes more accurate than HHWS, but sometimes inferior. However, in most cases, using the REWS, it was possible to calculate an estimate closer to the actual power output. Through the results of this study, it is possible to provide a rationale for which method, REWS or HHWS, can more accurately calculate the expected power output and effectively derive the economic feasibility of the project by identifying the characteristics of local atmospheric stability before the wind farm project.
A Comprehensive Study of Mobile Robot: History, Developments, Applications, and Future Research Perspectives
Authors: Raj Ravi , Kos Andrzej
Published: July 2022

Intelligent mobile robots that can move independently were laid out in the real world around 100 years ago during the second world war after advancements in computer science. Since then, mobile robot research has transformed robotics and information engineering. For example, robots were crucial in military applications, especially in teleoperations, when they emerged during the second world war era. Furthermore, after the implementation of artificial intelligence (AI) in robotics, they became autonomous or more intelligent. Currently, mobile robots have been implemented in many applications like defense, security, freight, pattern recognition, medical treatment, mail delivery, infrastructure inspection and developments, passenger travel, and many more because they are more intelligent nowadays with artificial intelligence technology. To study the developments of mobile robots, we have studied an extensive literature survey of the last 50 years. In this article, we discuss a complete century of mobile robotics research, major sensors used in robotics, some major applications of mobile robots, and their impact on our lives and in applied engineering.
All Traveling Wave Exact Solutions of the Kawahara Equation Using the Complex Method
Authors: Ye Feng , Tian Jian , Zhang Xiaoting , Jiang Chunling , Ouyang Tong , Gu Yongyi
Published: July 2022

In this article, we prove that the ⟨p,q⟩ condition holds, first by using the Fuchs index of the complex Kawahara equation, and then proving that all meromorphic solutions of complex Kawahara equations belong to the class W. Moreover, the complex method is employed to get all meromorphic solutions of complex Kawahara equation and all traveling wave exact solutions of Kawahara equation. Our results reveal that all rational solutions ur(x+νt) and simply periodic solutions us,1(x+νt) of Kawahara equation are solitary wave solutions, while simply periodic solutions us,2(x+νt) are not real-valued. Finally, computer simulations are given to demonstrate the main results of this paper. At the same time, we believe that this method is a very effective and powerful method of looking for exact solutions to the mathematical physics equations, and the search process is simpler than other methods.
A New Fuzzy Extension of the Simple WISP Method
Authors: Karabašević Darjan , Ulutaş Alptekin , Stanujkić Dragiša , Saračević Muzafer , Popović Gabrijela
Published: July 2022

The purpose of this article is to introduce to the literature a new extension of the Simple WISP method adapted for utilizing the triangular fuzzy numbers. This extension is proposed to allow the use of the Simple WISP method for addressing decision-making problems related to uncertainties and inaccuracies, as well as for solving problems related to predictions. In addition, this article also discusses the use of linguistic variables to collect the attitudes of the respondents, as well as their transformation into appropriate triangular fuzzy numbers. The article discusses the use of two defuzzification procedures. The first normalization procedure is easy to use, while the second procedure uses the advantages that the application of asymmetric fuzzy numbers gives in terms of analysis. The usability of the proposed extension is presented through two examples.
Maximum Entropy Modeling the Distribution Area of Morchella Dill. ex Pers. Species in China under Changing Climate
Authors: Cao Yu-Ting , Lu Zhao-Ping , Gao Xin-Yu , Liu Mi-Li , Sa Wei , Liang Jian , Wang Le , Yin Wei , Shang Qian-Han , Li Zhong-Hu
Published: July 2022

Morchella is a kind of precious edible, medicinal fungi with a series of important effects, including anti-tumor and anti-oxidation effects. Based on the data of 18 environmental variables and the distribution sites of wild Morchella species, this study used a maximum entropy (MaxEnt) model to predict the changes in the geographic distribution of Morchella species in different historical periods (the Last Glacial Maximum (LGM), Mid Holocene (MH), current, 2050s and 2070s). The results revealed that the area under the curve (AUC) values of the receiver operating characteristic curves of different periods were all relatively high (>0.83), indicating that the results of the maximum entropy model are good. Species distribution modeling showed that the major factors influencing the geographical distribution of Morchella species were the precipitation of the driest quarter (Bio17), elevation, the mean temperature of the coldest quarter (Bio11) and the annual mean temperature (Bio1). The simulation of geographic distribution suggested that the current suitable habitat of Morchella was mainly located in Yunnan, Sichuan, Gansu, Shaanxi, Xinjiang Uygur Autonomous Region (XUAR) and other provinces in China. Compared with current times, the suitable area in Northwest and Northeast China decreased in the LGM and MH periods. As for the future periods, the suitable habitats all increased under the different scenarios compared with those in contemporary times, showing a trend of expansion to Northeast and Northwest China. These results could provide a theoretical basis for the protection, rational exploitation and utilization of wild Morchella resources under scenarios of climate change.
Assessment of Specific Tumoral Markers, Inflammatory Status, and Vitamin D Metabolism before and after the First Chemotherapy Cycle in Patients with Lung Cancer
Authors: Crintea Andreea , Drugan Cristina , Constantin Anne-Marie , Lupan Iulia , Fekete Zsolt , Silaghi Ciprian Nicolae , Crăciun Alexandra Mărioara
Published: July 2022

Background: We aimed to investigate the changes of inflammatory status reflected by serum levels of chitotriosidase (CHT) and neopterin, and how specific tumor markers such as neuron-specific enolase (NSE) and squamous cell carcinoma antigen (SCCA), as well as vitamin D metabolism assessed by vitamin D receptor (VDR) and 25-hydroxy vitamin D3 (25OHD3), were modified after the first cycle of chemotherapy in patients with lung cancer. Methods: We performed this first pilot study on twenty patients diagnosed with lung cancer by investigating the serum concentrations of CHT, neopterin, NSE, SCCA, VDR and 25OHD3 before and after the first cycle of chemotherapy. Results: The post-treatment values of NSE were significantly lower compared to the pre-treatment levels (14.37 vs. 17.10 ng/mL, p = 0.031). We noticed a similar trend in neopterin levels, but the difference was only marginally significant (1.44 vs. 1.17 ng/mL, p = 0.069). On the contrary, the variations of circulating SCCA, CHT, neopterin, VDR and 25OHD3, before and after treatment, did not reach statistical significance. Conclusion: Only circulating NSE was treatment responsive to the first chemotherapy cycle in patients with lung cancer, while inflammatory markers and vitamin D status were not significantly modified.
Zinc Modulation of Neuronal Calcium Sensor Proteins: Three Modes of Interaction with Different Structural Outcomes
Authors: Baksheeva Viktoriia E. , Tsvetkov Philipp O. , Zalevsky Arthur O. , Vladimirov Vasiliy I. , Gorokhovets Neonila V. , Zinchenko Dmitry V. , Permyakov Sergei E. , Devred François , Zernii Evgeni Yu.
Published: July 2022

Neuronal calcium sensors (NCSs) are the family of EF-hand proteins mediating Ca2+-dependent signaling pathways in healthy neurons and neurodegenerative diseases. It was hypothesized that the calcium sensor activity of NCSs can be complemented by sensing fluctuation of intracellular zinc, which could further diversify their function. Here, using a set of biophysical techniques, we analyzed the Zn2+-binding properties of five proteins belonging to three different subgroups of the NCS family, namely, VILIP1 and neurocalcin-δ/NCLD (subgroup B), recoverin (subgroup C), as well as GCAP1 and GCAP2 (subgroup D). We demonstrate that each of these proteins is capable of coordinating Zn2+ with a different affinity, stoichiometry, and structural outcome. In the absence of calcium, recoverin and VILIP1 bind two zinc ions with submicromolar affinity, and the binding induces pronounced conformational changes and regulates the dimeric state of these proteins without significant destabilization of their structure. In the presence of calcium, recoverin binds zinc with slightly decreased affinity and moderate conformational outcome, whereas VILIP1 becomes insensitive to Zn2+. NCALD binds Zn2+ with micromolar affinity, but the binding induces dramatic destabilization and aggregation of the protein. In contrast, both GCAPs demonstrate low-affinity binding of zinc independent of calcium, remaining relatively stable even at submillimolar Zn2+ concentrations. Based on these data, and the results of structural bioinformatics analysis, NCSs can be divided into three categories: (1) physiological Ca2+/Zn2+ sensor proteins capable of binding exchangeable (signaling) zinc (recoverin and VILIP1), (2) pathological Ca2+/Zn2+ sensors responding only to aberrantly high free zinc concentrations by denaturation and aggregation (NCALD), and (3) Zn2+-resistant, Ca2+ sensor proteins (GCAP1, GCAP2). We suggest that NCS proteins may therefore govern the interconnection between Ca2+-dependent and Zn2+-dependent signaling pathways in healthy neurons and zinc cytotoxicity-related neurodegenerative diseases, such as Alzheimer’s disease and glaucoma.
Genome-Wide Classification and Evolutionary Analysis Reveal Diverged Patterns of Chalcone Isomerase in Plants
Authors: Wang Jianyong , Jiang Yifei , Sun Tong , Zhang Chenhao , Liu Xuhui , Li Yangsheng
Published: July 2022

Flavonoids as a class of important secondary metabolites are widely present in land plants, and chalcone isomerase (CHI) is the key rate-limiting enzyme that participates in catalyzing the stereospecific isomerization of chalcones to yield their corresponding flavanones. However, the phylogenetic dynamics and functional divergence of CHI family genes during the evolutionary path of green plants remains poorly understood. Here, a total of 122 CHI genes were identified by performing a genome-wide survey of 15 representative green plants from the most ancestral basal plant chlorophyte algae to higher angiosperm plants. Phylogenetic, orthologous groups (OG) classification, and genome structure analysis showed that the CHI family genes have evolved into four distinct types (types I–IV) containing eight OGs after gene duplication, and further studies indicated type III CHIs consist of three subfamilies (FAP1, FAP2, and FAP3). The phylogeny showed FAP3 CHIs as an ancestral out-group positioned on the outer layers of the main branch, followed by type IV CHIs, which are placed in an evolutionary intermediate between FAP3 CHIs and bona fide CHIs (including type I and type II). The results imply a potential intrinsic evolutionary connection between CHIs existing in the green plants. The amino acid substitutions occurring in several residues have potentially affected the functional divergence between CHI proteins. This is supported by the analysis of transcriptional divergence and cis-acting element analysis. Evolutionary dynamics analyses revealed that the differences in the total number of CHI family genes in each plant are primarily attributed to the lineage-specific expansion by natural selective forces. The current studies provide a deeper understanding of the phylogenetic relationships and functional diversification of CHI family genes in green plants, which will guide further investigation on molecular characteristics and biological functions of CHIs.
Untargeted Metabolomic Plasma Profiling of Emirati Dialysis Patients with Diabetes versus Non-Diabetic: A Pilot Study
Authors: Banimfreg Bayan Hassan , Alshraideh Hussam , Shamayleh Abdulrahim , Guella Adnane , Semreen Mohammad Harb , Al Bataineh Mohammad Tahseen , Soares Nelson C.
Published: July 2022

Diabetic kidney disease (DKD) is a severe irreversible complication of diabetes mellitus that further disturbs glucose metabolism. Identifying metabolic changes in the blood may provide early insight into DKD pathogenesis. This study aims to determine blood biomarkers differentiating DKD from non-diabetic kidney disease in the Emirati population utilizing the LC-MS/MS platform. Blood samples were collected from hemodialysis subjects with and without diabetes to detect indicators of pathological changes using an untargeted metabolomics approach. Metabolic profiles were analyzed based on clinically confirmed diabetic status and current HbA1c values. Five differentially significant metabolites were identified based on the clinically confirmed diabetic status, including hydroxyprogesterone and 3,4-Dihydroxymandelic acid. Similarly, we identified seven metabolites with apparent differences between Dialysis Diabetic (DD) and Dialysis non-Diabetic (DND) groups, including isovalerylglycine based on HbA1c values. Likewise, the top three metabolic pathways, including Tyrosine metabolism, were identified following the clinically confirmed diabetic status. As a result, nine different metabolites were enriched in the identified metabolic pathways, such as 3,4-Dihydroxymandelic acid. As a result, eleven different metabolites were enriched, including Glycerol. This study provides an insight into blood metabolic changes related to DKD that may lead to more effective management strategies.
Differentially Aquaporin 5 Expression in Submandibular Glands and Cerebral Cortex in Alzheimer’s Disease
Authors: Antequera Desiree , Carrero Laura , Cunha Alves Victoria , Ferrer Isidro , Hernández-Gallego Jesús , Municio Cristina , Carro Eva
Published: July 2022

Impaired brain clearance mechanisms may result in the accumulation of aberrant proteins that define Alzheimer’s disease (AD). The water channel protein astrocytic aquaporin 4 (AQP4) is essential for brain amyloid-β clearance, but it is known to be abnormally expressed in AD brains. The expression of AQPs is differentially regulated during diverse brain injuries, but, whereas AQP4 expression and function have been studied in AD, less is known about AQP5. AQP5 functions include not only water transport but also cell migration mediated by cytoskeleton regulation. Moreover, AQP5 has been reported to be expressed in astrocytes, which are regulated after ischemic and traumatic injury. Additionally, AQP5 is particularly abundant in the salivary glands suggesting that it may be a crucial factor in gland dysfunction associated with AD. Herein, we aim to determine whether AQP5 expression in submandibular glands and the brain was altered in AD. First, we demonstrated impaired AQP5 expression in submandibular glands in APP/PS1 mice and AD patients. Subsequently, we observed that AQP5 expression was upregulated in APP/PS1 cerebral cortex and confirmed its expression both in astrocytes and neurons. Our findings propose AQP5 as a significant role player in AD pathology, in addition to AQP4, representing a potential target for the treatment of AD.
A Fast, Reliable Oil-In-Water Microemulsion Procedure for Silica Coating of Ferromagnetic Zn Ferrite Nanoparticles Capable of Inducing Cancer Cell Death In Vitro
Authors: Nitica Stefan , Fizesan Ionel , Dudric Roxana , Barbu-Tudoran Lucian , Pop Anca , Loghin Felicia , Vedeanu Nicoleta , Lucaciu Constantin Mihai , Iacovita Cristian
Published: July 2022

The applications of ferrimagnetic nanoparticles (F-MNPs) in magnetic hyperthermia (MH) are restricted by their stabilization in microscale aggregates due to magnetostatic interactions significantly reducing their heating performances. Coating the F-MNPs in a silica layer is expected to significantly reduce the magnetostatic interactions, thereby increasing their heating ability. A new fast, facile, and eco-friendly oil-in-water microemulsion-based method was used for coating Zn0.4Fe2.6O4 F-MNPs in a silica layer within 30 min by using ultrasounds. The silica-coated clusters were characterized by various physicochemical techniques and MH, while cytotoxicity studies, cellular uptake determination, and in vitro MH experiments were performed on normal and malignant cell lines. The average hydrodynamic diameter of silica-coated clusters was approximately 145 nm, displaying a high heating performance (up to 2600 W/gFe). Biocompatibility up to 250 μg/cm2 (0.8 mg/mL) was recorded by Alamar Blue and Neutral Red assays. The silica-coating increases the cellular uptake of Zn0.4Fe2.6O4 clusters up to three times and significantly improves their intracellular MH performances. A 90% drop in cellular viability was recorded after 30 min of MH treatment (20 kA/m, 355 kHz) for a dosage level of 62.5 μg/cm2 (0.2 mg/mL), while normal cells were more resilient to MH treatment.
PC-12 Cell Line as a Neuronal Cell Model for Biosensing Applications
Authors: Oprea Daniela , Sanz Caroline G. , Barsan Madalina M. , Enache Teodor Adrian
Published: July 2022

PC-12 cells have been widely used as a neuronal line study model in many biosensing devices, mainly due to the neurogenic characteristics acquired after differentiation, such as high level of secreted neurotransmitter, neuron morphology characterized by neurite outgrowth, and expression of ion and neurotransmitter receptors. For understanding the pathophysiology processes involved in brain disorders, PC-12 cell line is extensively assessed in neuroscience research, including studies on neurotoxicity, neuroprotection, or neurosecretion. Various analytical technologies have been developed to investigate physicochemical processes and the biosensors based on optical and electrochemical techniques, among others, have been at the forefront of this development. This article summarizes the application of different biosensors in PC-12 cell cultures and presents the modern approaches employed in neuronal networks biosensing.
Challenges and Limitations of Biological Network Analysis
Authors: Milano Marianna , Agapito Giuseppe , Cannataro Mario
Published: July 2022

High-Throughput technologies are producing an increasing volume of data that needs large amounts of data storage, effective data models and efficient, possibly parallel analysis algorithms. Pathway and interactomics data are represented as graphs and add a new dimension of analysis, allowing, among other features, graph-based comparison of organisms’ properties. For instance, in biological pathway representation, the nodes can represent proteins, RNA and fat molecules, while the edges represent the interaction between molecules. Otherwise, biological networks such as Protein–Protein Interaction (PPI) Networks, represent the biochemical interactions among proteins by using nodes that model the proteins from a given organism, and edges that model the protein–protein interactions, whereas pathway networks enable the representation of biochemical-reaction cascades that happen within the cells or tissues. In this paper, we discuss the main models for standard representation of pathways and PPI networks, the data models for the representation and exchange of pathway and protein interaction data, the main databases in which they are stored and the alignment algorithms for the comparison of pathways and PPI networks of different organisms. Finally, we discuss the challenges and the limitations of pathways and PPI network representation and analysis. We have identified that network alignment presents a lot of open problems worthy of further investigation, especially concerning pathway alignment.
BIM for the Realization of Sustainable Digital Models in a University-Business Collaborative Learning Environment: Assessment of Use and Students’ Perception
Authors: Sanchez-Lite Alberto , Zulueta Patricia , Sampaio Alcínia Zita , Gonzalez-Gaya Cristina
Published: July 2022

This paper develops an assessment of an academic implementation of building information modeling (BIM) carried out in an expert project subject of a School of Industrial Engineering. The objectives were for the students discover sustainable industrial during the design process and the students understand and participate in a real process of the implementation of industrial projects through real collaboration between academic and business contexts. The outcomes of this academic initiative were evaluated using academic results as well as students’ perceptions. Academic results were analyzed using the FUZZY VIKOR method. An analysis of variance (ANOVA) was performed to determine whether the use of BIM, the proposed university-enterprise environment and the sustainability proposal rate of the students’ projects had statistically significant effects on the results. Students´ perception evaluation was based on a Likert survey with five levels, and the results were interpreted using fuzzy k-means clustering and classification tree analysis. The results show that 77.8% of students consider that for learning, it is more effective to carry out a project related to an existing company, with the realization of the project with BIM methodology being of great value. The sustainability aspects were applied more easily thanks to the proposed methodology, and they were positively valued by the company.
Designing for COVID-2x: Reflecting on Future-Proofing Human Habitation for the Inevitable Next Pandemic
Authors: Spennemann Dirk H. R.
Published: July 2022

The COVID-19 pandemic of 2020–2022 has revealed the vulnerability of modern society to a highly contagious airborne virus. Many spaces in the urban and built environment designed during the late twentieth and early twenty-first century are ill-suited to maintain the level of social distancing required to reduce the probability of virus transmission. Enclosed spaces—in particular, communal circulation spaces such as corridors, elevators and lobbies—have proven loci of transmission, together with circulating reticulated air and lack of proper ventilation. While urban planning needs to incorporate the lessons learnt during COVID-19 in order to future-proof our communities through the provision of well-designed greenspaces, the main burden will fall on architects, who will play an instrumental role in designing buildings that are fit-for purpose. This conceptual paper reviews the status quo and discusses a number of strategies to future-proof human habitation for the inevitable next pandemic.
Retinal Proteomic Alterations and Combined Transcriptomic-Proteomic Analysis in the Early Stages of Progression of a Mouse Model of X-Linked Retinoschisis
Authors: Jin Xiuxiu , Zhang Xiaoli , Liu Jingyang , Wang Weiping , Liu Meng , Yang Lin , Liu Guangming , Qiu Ruiqi , Yang Mingzhu , Yao Shun , Lei Bo
Published: July 2022

X-linked retinoschisis (XLRS) is among the most commonly inherited degenerative retinopathies. XLRS is caused by functional impairment of RS1. However, the molecular mechanisms underlying RS1 malfunction remain largely uncharacterized. Here, we performed a data-independent acquisition-mass spectrometry-based proteomic analysis in RS1-null mouse retina with different postal days (Ps), including the onset (P15) and early progression stage (P56). Gene set enrichment analysis showed that type I interferon-mediated signaling was upregulated and photoreceptor proteins responsible for detection of light stimuli were downregulated at P15. Positive regulation of Tor signaling was downregulated and nuclear transcribed mRNA catabolic process nonsense-mediated decay was upregulated at P56. Moreover, the differentially expressed proteins at P15 were enriched in metabolism of RNA and RNA destabilization. A broader subcellular localization distribution and enriched proteins in visual perception and phototransduction were evident at P56. Combined transcriptomic-proteomic analysis revealed that functional impairments, including detection of visible light, visual perception, and visual phototransduction, occurred at P21 and continued until P56. Our work provides insights into the molecular mechanisms underlying the onset and progression of an XLRS mouse model during the early stages, thus enhancing the understanding of the mechanism of XLRS.
Antioxidant Activity of New Sulphur- and Selenium-Containing Analogues of Potassium Phenosan against H2O2-Induced Cytotoxicity in Tumour Cells
Authors: Klyushova Lyubov S. , Kandalintseva Natalya V. , Grishanova Alevtina Y.
Published: July 2022

Among known phenolic antioxidants, the overwhelming majority of compounds have lipophilic properties and the number of known water-soluble compounds is very small. The list of hydrophilic phenolic antioxidants can be expanded via the synthesis of a structurally related series of polyfunctional compounds for further research on their biological activity in vitro. New sulphur- and selenium-containing analogues of antioxidant potassium phenosan were synthesised. In vitro cytotoxicity and cytostaticity as well as antioxidant activity against H2O2-induced cytotoxicity to human cell lines (HepG2, Hep-2 and MCF-7) were investigated by high-content analysis. A selenium-containing analogue showed higher biological activity than did a sulphur-containing one. As compared to the activity of potassium phenosan, the selenium-containing analogue had a cell line-dependent antioxidant effect against H2O2-induced cytotoxicity: comparable in HepG2 cells and greater in Hep-2 cells. The selenium-containing analogue significantly increased the death of MCF-7 cells at concentrations above 50 µM. The sulphur-containing analogue has lower biological activity as compared to potassium phenosan and the selenium-containing analogue.
Diagnostic and Therapeutic Challenges in a Patient with Ureteral Metastases from a Triple Negative Breast Cancer
Authors: Saranti Georgia , Zolota Vasiliki , Kalogeropoulou Christina , Papathanasiou Nikolaos , Katsila Theodora , Kitsou Konstantina , Haliassos Ilias , Kardamakis Dimitrios
Published: July 2022

Metastatic ureteral tumors arising from a primary breast carcinoma are extremely rare. They present with hematuria and radiological findings compatible with obstructive ureteral phenomena. We present a case of an 87-year-old woman with a history of lymphoma and triple negative breast cancer (TNBC), during an emergency admission for peptic ulcer, developed macroscopic hematuria. Radiologic and endoscopic investigations revealed a remarkable stenosis at the lower segment of the right ureter, attributed to metastases from her breast carcinoma. We report this case with the aim to make both oncologists and urologists aware of this rare condition.
Pretreatment Modified Albumin–Bilirubin Grade Is an Important Predictive Factor Associated with the Therapeutic Response and the Continuation of Atezolizumab plus Bevacizumab Combination Therapy for Patients with Unresectable Hepatocellular Carcinoma
Authors: Tanaka Takashi , Takata Kazuhide , Yokoyama Keiji , Fukuda Hiromi , Yamauchi Ryo , Fukunaga Atsushi , Shakado Satoshi , Sakisaka Shotaro , Hirai Fumihito
Published: July 2022

Background: Atezolizumab plus bevacizumab (ATZ + BV) treatment is recommended as the first-line systemic therapy for patients with unresectable hepatocellular carcinoma (u-HCC). This study aimed to investigate the predictive factors of therapeutic response and the continuation of ATZ + BV treatment for u-HCC in a real-world setting. Methods: This retrospective study was conducted between January 2021 and April 2022. Twenty-eight patients with u-HCC, who were treated with ATZ + BV, were assessed for their treatment response, continuation, and adverse events (AEs). Results: Among the 28 patients, 24 were evaluated at the first imaging. The objective response rate (ORR) was 29.2% (n = 7), and 54.2% (n = 13) on the response evaluation criteria in solid tumors (RECIST 1.1) and in the modified RECIST (mRECIST) guidelines, respectively. Comparing the objective response (OR) group (n = 13) and the non-OR group (n = 11), the modified albumin–bilirubin (mALBI) grades 1 and 2a were found to be significant predictive factors for OR (p = 0.021) in the mRECIST guidelines. Among the 28 patients, 17 discontinued their treatment due to AEs. Comparing the treatment continuation (n = 11) and discontinuation groups (n = 17), a Child–Pugh score of five points (p = 0.009) and mALBI grades 1 and 2a (p = 0.020) were predictive factors with significant differences. Conclusions: Pretreatment mALBI grades 1 and 2a were the important predictive factors associated with the therapeutic response and the therapeutic continuation of ATZ + BV for patients with u-HCC.
Through the COVID-19 to Prospect Online School Learning: Voices of Students from China, Lebanon, and the US
Authors: Xu Zhining , Pang Jia , Chi Jin
Published: July 2022

Online learning has emerged as a widely used learning mode and will likely supplement traditional learning in the post-pandemic era. The purpose of this study is to present student voices of online school education by investigating students’ online learning experiences during the COVID-19 pandemic in various contexts, and explain why the impacts are important to student learning and well-being. Semi-structured in-depth interviews were conducted with nine students from China, Lebanon, and the United States to gain direct insight into students’ perceptions of each country. The results showed that the online learning environment provided at the national level, such as social conflicts, and the facilities provided at the individual level, such as information access, increase the educational inequity. High-school students experienced numerous psychological changes and encountered academic cheating issues in the home online-learning environment. We recommend that online school education should make significant improvements in pedagogy, students’ mental health, and learning assessment, and consider factors beyond technology solutions.
Pre-Training and Fine-Tuning with Next Sentence Prediction for Multimodal Entity Linking
Authors: Li Lu , Wang Qipeng , Zhao Baohua , Li Xinwei , Zhou Aihua , Wu Hanqian
Published: July 2022

As an emerging research field, more and more researchers are turning their attention to multimodal entity linking (MEL). However, previous works always focus on obtaining joint representations of mentions and entities and then determining the relationship between mentions and entities by these representations. This means that their models are often very complex and will result in ignoring the relationship between different modal information from different corpus. To solve the above problems, we proposed a paradigm of pre-training and fine-tuning for MEL. We designed three different categories of NSP tasks for pre-training, i.e., mixed-modal, text-only and multimodal and doubled the amount of data for pre-training by swapping the roles of sentences in NSP. Our experimental results show that our model outperforms other baseline models and our pre-training strategies all contribute to the improvement of the results. In addition, our pre-training gives the final model a strong generalization capability that performs well even on smaller amounts of data.
Unknown System Dynamics Estimator-Based Anti-Disturbance Attitude Funnel Control for Quadrotors with Experimental Verifications
Authors: Zhen Shiyu , Zhang Lihong
Published: July 2022

In the article, an unknown system dynamics estimator-based anti-disturbance attitude funnel control technique is considered for quadrotors to ensure tracking performance when experiencing parametric uncertainties and external perturbations. To reinforce the anti-disturbance ability, an unknown system dynamics estimator was established by constructing the filtering operation-based invariant manifold, resulting in a more concise design framework, lower computational consumption and an asymptotic error convergence. Additionally, a funnel control policy was employed to regulate angle-tracking errors within a minor overshoot, a faster convergence time and a lower steady-state error by devising the funnel variables, where an exponential decaying function was used to construct the funnel boundary. The great improvements beyond the available quadrotor control policies are related to satisfied disturbance mitigation and performance guarantees as a priority despite uncertainties. The error arguments comprising of angle and angular rate for quadrotors were ultimately uniformly bounded and the angles controlling the deviations were restricted to the funnel boundary. Finally, the simulations and experiments verified the superiority of the proposed control technique in terms of reduced control actions and higher precision, as well as shorter settling time.
Semantic Super-Resolution of Text Images via Self-Distillation
Authors: Park Hanhoon
Published: July 2022

This research develops an effective single-image super-resolution (SR) method that increases the resolution of scanned text or document images and improves their readability. To this end, we introduce a new semantic loss and propose a semantic SR method that guides an SR network to learn implicit text-specific semantic priors through self-distillation. Experiments on the enhanced deep SR (EDSR) model, one of the most popular SR networks, confirmed that semantic loss can contribute to further improving the quality of text SR images. Although the improvement varied depending on image resolution and dataset, the peak signal-to-noise ratio (PSNR) value was increased by up to 0.3 dB by introducing the semantic loss. The proposed method outperformed an existing semantic SR method.
Multilabel Text Classification Algorithm Based on Fusion of Two-Stream Transformer
Authors: Duan Lihua , You Qi , Wu Xinke , Sun Jun
Published: July 2022

Existing multilabel text classification methods rely on a complex manual design to mine label correlation, which has the risk of overfitting and ignores the relationship between text and labels. To solve the above problems, this paper proposes a multilabel text classification algorithm based on a transformer encoder–decoder, which can adaptively extract the dependency relationship between different labels and text. First, text representation learning is carried out through word embedding and a bidirectional long short-term memory network. Second, the global relationship of the text is modeled by the transformer encoder, and then the multilabel query is adaptively learned by the transformer decoder. Last, a weighted fusion strategy under the supervision of multiple loss functions is proposed to further improve the classification performance. The experimental results on the AAPD and RCV1-V2 datasets show that compared with the existing methods, the proposed algorithm achieves better classification results. The optimal micro-F1 reaches 73.4% and 87.8%, respectively, demonstrating the effectiveness of the proposed algorithm.
High-Resolution Delay Spread of Wide-Band Wireless Link in Long Tunnels—Theory and Experimental Verification
Authors: Taragin Yehuda , Rapaport Liat , Elkayamn Niv , Pinhasi Gad A. , Pinhasi Yosef
Published: July 2022

The need for wireless communication appears everywhere, and with as few interruptions as possible. An extensive and in-depth study has been conducted on the limitations of wireless communication in pedestrian tunnels. Using an analytical mathematical ray tracing model, and performing tunnel measurements, with an autonomous measuring setup, the model was validated. An extraordinary wide band was used for the experiments, which also featured optical systems to ensure accurate results. Since the tunnel is narrow, the differences between the different paths are small, and in order to distinguish them a resolution of 0.2 ns was used. The RMS delay spread, στ, decreases throughout the tunnel, and at no point exceeds 1 ns.
Voting-Based Scheme for Leader Election in Lead-Follow UAV Swarm with Constrained Communication
Authors: Zuo Yuan , Yao Wen , Chang Qiang , Zhu Xiaozhou , Gui Jianjun , Qin Jiangyi
Published: July 2022

The recent advances in unmanned aerial vehicles (UAVs) enormously improve their utility and expand their application scope. The UAV and swarm implementation further prevail in Smart City practices with the aid of edge computing and urban Internet of Things. The lead–follow formation in UAV swarm is an important organization means and has been adopted in diverse exercises, for its efficiency and ease of control. However, the reliability of centralization makes the entire swarm system in risk of collapse and instability, if a fatal fault incident happens in the leader. The motivation is to build a mechanism helping the distributed swarm recover from possible failures. Existing ways include assigning definite backups, temporary clustering and traversing to select a new leader are traditional ways that lack flexibility and adaptability. In this article, we propose a voting-based leader election scheme inspired by the Raft method in distributed computation consensus to solve the problem. We further discuss the impact of communication conditions imposed on the decentralized voting process by implementing a network resource pool. To dynamically evaluate UAV individuals, we outline measurement design principles and provide a realizable calculation example. Lastly but not least, empirical simulation results manifest better performance than the Raft-based method. Our voting-based approach exhibits advantages and is a promising way for quick regrouping and fault recovery in lead–follow swarms.
Distributed Multi-Mobile Robot Path Planning and Obstacle Avoidance Based on ACO–DWA in Unknown Complex Terrain
Authors: Wang Qian , Li Junli , Yang Liwei , Yang Zhen , Li Ping , Xia Guofeng
Published: July 2022

Multi-robot systems are popularly distributed in logistics, transportation, and other fields. We propose a distributed multi-mobile robot obstacle-avoidance algorithm to coordinate the path planning and motion navigation among multiple robots and between robots and unknown territories. This algorithm fuses the ant colony optimization (ACO) and the dynamic window approach (DWA) to coordinate a multi-robot system through a priority strategy. Firstly, to ensure the optimality of robot motion in complex terrains, we proposed the dual-population heuristic functions and a sort ant pheromone update strategy to enhance the search capability of ACO, and the globally optimal path is achieved by a redundant point deletion strategy. Considering the robot’s path-tracking accuracy and local target unreachability problems, an adaptive navigation strategy is presented. Furthermore, we propose the obstacle density evaluation function to improve the robot’s decision-making difficulty in high-density obstacle environments and modify the evaluation function coefficients adaptively by combining environmental characteristics. Finally, the robots’ motion conflict is resolved by combining our obstacle avoidance and multi-robot priority strategies. The experimental results show that this algorithm can realize the cooperative obstacle avoidance of AGVs in unknown environments with high safety and global optimality, which can provide a technical reference for distributed multi-robot in practical applications.