bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation of an Indoor Air Quality Baseline Model for School Retrofitting Using Automated and Semi-Automated Calibrations: The Case Study in South Korea
Authors: Sung Ho Jin , Kim Sean Hay , Choi Seung Yeoun
Published: September 2022

School retrofitting should aim to not only improve its energy performance, but also maintain a good IAQ. An optimal combination of retrofitting measures must be selected by considering the transient state changes of the outdoor and built environments. Although a simulation is an effective platform to evaluate a combination of the retrofitting measure candidates, there is a general lack of practical methods for practitioners to collect the field data and prepare a reliable IAQ baseline model within a project timeline. This study suggests a suite of tools to generate a classroom IAQ baseline, which includes standardized diagnostic scenarios based on common retrofitting practices and measurement protocols of classroom IAQs; the diagnostic scenarios intend to quantify the dilution and filtration capabilities of classrooms through deposition, infiltration, and natural/mechanical ventilations when a high concentration is observed; the first principle model is developed to normalize the measurement, which is fitted against the measurement by adjusting its parameter values. In order to save time and effort for practitioners, automated and semi-automated calibrations that run in a short time are also developed. While the automated calibrations performed better in some cases, the semi-automated calibrations performed better than the automated ones in many cases, the CV-RMSE were smaller, by between −7% and −0.5%. Meanwhile, it took a comparably larger effort and longer time (>1 h for the worst cases) for the heuristic calibrations to have a similar accuracy with the machine-driven calibrations. If the model structure suffers a problem with the measurement, the modeler must intervene in the calibrations. In this case, semi-automation can be a diagnostic tool for a practitioner to intuitively determine from which variables to start the calibration.
Two Steps Procedure for the Finite Elements Seismic Analysis of the Casamari Gothic Church
Authors: Malena Marialaura , Genoese Andrea , Panto’ Bartolomeo , Spina Daniele , de Felice Gianmarco
Published: September 2022

The structural analysis of historic masonry churches subject to earthquakes is commonly based on two distinct approaches: that of the global response to seismic actions and that of the local analysis of a priori pre-determined collapse mechanisms. This is a conventional decoupling of the structural problem due to the difficulty of addressing the seismic vulnerability of individual parts from the modelling of the whole. The aim of this work is to establish a link between the global behavior of the church and the assessment of the local mechanisms, re-evaluating the value of modal analysis to be associated with non-linear seismic assessment. With this aim, a two steps procedure is proposed, where: the first step is based on the detection of the main vibration modes of the whole building with identification of the structural bi-dimensional macro-elements that are responsible for the overall seismic vulnerability, while the second step, is based on the non-linear finite element analysis of the previously identified macro-elements, to evaluate the failure pattern caused by the earthquakes. The procedure will applied to the case study of the Casamari Gothic church in Veroli (Italy).
Thiosemicarbazone Derivatives Developed to Overcome COTI-2 Resistance
Authors: Pósa Vivien , Stefanelli Alessia , Nunes Julia H. Bormio , Hager Sonja , Mathuber Marlene , May Nóra V. , Berger Walter , Keppler Bernhard K. , Kowol Christian R. , Enyedy Éva A. , Heffeter Petra
Published: September 2022

COTI-2 is currently being evaluated in a phase I clinical trial for the treatment of gynecological and other solid cancers. As a thiosemicarbazone, this compound contains an N,N,S-chelating moiety and is, therefore, expected to bind endogenous metal ions. However, besides zinc, the metal interaction properties of COTI-2 have not been investigated in detail so far. This is unexpected, as we have recently shown that COTI-2 forms stable ternary complexes with copper and glutathione, which renders this drug a substrate for the resistance efflux transporter ABCC1. Herein, the complex formation of COTI-2, two novel terminal N-disubstituted derivatives (COTI-NMe2 and COTI-NMeCy), and the non-substituted analogue (COTI-NH2) with iron, copper, and zinc ions was characterized in detail. Furthermore, their activities against drug-resistant cancer cells was investigated in comparison to COTI-2 and Triapine. These data revealed that, besides zinc, also iron and copper ions need to be considered to play a role in the mode of action and resistance development of these thiosemicarbazones. Moreover, we identified COTI-NMe2 as an interesting new drug candidate with improved anticancer activity and resistance profile.
Radiomics Nomogram: Prediction of 2-Year Disease-Free Survival in Young Age Breast Cancer
Authors: Lee Jeongmin , Kim Sung Hun , Kim Yelin , Park Jaewoo , Park Ga Eun , Kang Bong Joo
Published: September 2022

This study aimed to predict early breast cancer recurrence in women under 40 years of age using radiomics signature and clinicopathological information. We retrospectively investigated 155 patients under 40 years of age with invasive breast cancer who underwent MRI and surgery. Through stratified random sampling, 111 patients were assigned as the training set, and 44 were assigned as the validation set. Recurrence-associated factors were investigated based on recurrence within 5 years during the total follow-up period. A Rad-score was generated through texture analysis (3D slicer, ver. 4.8.0) of breast MRI using the least absolute shrinkage and selection operator Cox regression model. The Rad-score showed a significant association with disease-free survival (DFS) in the training set (p = 0.003) and validation set (p = 0.020) in the Kaplan–Meier analysis. The nomogram was generated through Cox proportional hazards models, and its predictive ability was validated. The nomogram included the Rad-score and estrogen receptor negativity as predictive factors and showed fair DFS predictive ability in both the training and validation sets (C-index 0.63, 95% CI 0.45–0.79). In conclusion, the Rad-score can predict the disease recurrence of invasive breast cancer in women under 40 years of age, and the Rad-score-based nomogram showed reasonably high DFS predictive ability, especially within 2 years of surgery.
Molecular Characterizations of Gynecologic Carcinosarcomas: A Focus on the Immune Microenvironment
Authors: Nakad Borrego Sanaa , Lengyel Ernst , Kurnit Katherine C.
Published: September 2022

Gynecologic carcinosarcomas, specifically of endometrial and ovarian origin, are aggressive and rare tumors. Treatment data are limited and are often extrapolated from other histologies and smaller retrospective studies. While the optimal therapy approach remains contentious, treatment is often multimodal and may include surgery, chemotherapy, radiation, or a combination of multiple strategies. However, despite aggressive treatment, these tumors fare worse than carcinomas of the same anatomic sites irrespective of their stage. Recent studies have described in-depth molecular characterizations of gynecologic carcinosarcomas. Although many molecular features mirror those seen in other uterine and ovarian epithelial tumors, the high prevalence of epithelial-mesenchymal transition is more unique. Recently, molecular descriptions have expanded to begin to characterize the tumor immune microenvironment. While the importance of the immune microenvironment has been well-established for other tumor types, it has been less systematically explored in gynecologic carcinosarcomas. Furthermore, the use of immunotherapy in patients with gynecologic carcinosarcomas has not been extensively evaluated. In this review, we summarize the available data surrounding gynecologic carcinosarcomas, with a focus on the immune microenvironment. We end with a discussion of potential immunotherapy uses and future directions for the field.
Unraveling the Structural Variations of Early-Stage Mycosis Fungoides—CD3 Based Purification and Third Generation Sequencing as Novel Tools for the Genomic Landscape in CTCL
Authors: Hain Carsten , Stadler Rudolf , Kalinowski Jörn
Published: September 2022

Mycosis fungoides (MF) is the most common cutaneous T-cell lymphoma (CTCL). At present, knowledge of genetic changes in early-stage MF is insufficient. Additionally, low tumor cell fraction renders calling of copy-number variations as the predominant mutations in MF challenging, thereby impeding further investigations. We show that enrichment of T cells from a biopsy of a stage I MF patient greatly increases tumor fraction. This improvement enables accurate calling of recurrent MF copy-number variants such as ARID1A and CDKN2A deletion and STAT5 amplification, undetected in the unprocessed biopsy. Furthermore, we demonstrate that application of long-read nanopore sequencing is especially useful for the structural variant rich CTCL. We detect the structural variants underlying recurrent MF copy-number variants and show phasing of multiple breakpoints into complex structural variant haplotypes. Additionally, we record multiple occurrences of templated insertion structural variants in this sample. Taken together, this study suggests a workflow to make the early stages of MF accessible for genetic analysis, and indicates long-read sequencing as a major tool for genetic analysis for MF.
Enzymatic Formation of Recombinant Antibody-Conjugated Gold Nanoparticles in the Presence of Citrate Groups and Bacteria
Authors: Rad Maryam , Ebrahimipour Gholamhossein , Bandehpour Mojgan , Akhavan Omid , Yarian Fatemeh
Published: September 2022

With the spread of deadly diseases worldwide, the design of rapid tests to identify causative microorganisms is necessary. Due to the unique properties of gold nanoparticles, these nanoparticles are used in designing rapid diagnostic tests, such as strip tests. The current study aimed to investigate the ability of gold nanoparticles to bind to single-chain variable fragment antibodies. In this study, the biological and chemical methods included Escherichia coli TOP-10 and the Turkevich method to synthesize the gold nanoparticles, respectively. Then, the effect of synthetic nanoparticles on their capability of binding to recombinant antibodies was assessed by agarose gel and UV-vis spectroscopy. Our result showed that gold nanoparticles had a spherical morphology, and their average size was ~45 nm. Additionally, the citrate groups in gold nanoparticles were able to bind to serine residues in the antibody linker sequence; so, the chemical synthesis of gold nanoparticles is an effective strategy for binding these nanoparticles to antibodies that can be used in designing rapid diagnostic tests to promptly identify infectious microorganisms.
MiR-22 Deficiency Fosters Hepatocellular Carcinoma Development in Fatty Liver
Authors: Gjorgjieva Monika , Ay Anne-Sophie , Correia de Sousa Marta , Delangre Etienne , Dolicka Dobrochna , Sobolewski Cyril , Maeder Christine , Fournier Margot , Sempoux Christine , Foti Michelangelo
Published: September 2022

MiR-22 is mostly considered as a hepatic tumor-suppressor microRNA based on in vitro analyses. Yet, whether miR-22 exerts a tumor-suppressive function in the liver has not been investigated in vivo. Herein, in silico analyses of miR-22 expression were performed in hepatocellular carcinomas from human patient cohorts and different mouse models. Diethylnitrosamine-induced hepatocellular carcinomas were then investigated in lean and diet-induced obese miR-22-deficient mice. The proteome of liver tissues from miR-22-deficient mice prior to hepatocellular carcinoma development was further analyzed to uncover miR-22 regulated factors that impact hepatocarcinogenesis with miR-22 deficiency. MiR-22 downregulation was consistently observed in hepatocellular carcinomas from all human cohorts and mouse models investigated. The time of appearance of the first tumors was decreased and the number of tumoral foci induced by diethylnitrosamine was significantly increased by miR-22-deficiency in vivo, two features which were further drastically exacerbated with diet-induced obesity. At the molecular level, we provide evidence that the loss of miR-22 significantly affects the energetic metabolism and mitochondrial functions of hepatocytes, and the expression of tumor-promoting factors such as thrombospondin-1. Our study demonstrates that miR-22 acts as a hepatic tumor suppressor in vivo by restraining pro-carcinogenic metabolic deregulations through pleiotropic mechanisms and the overexpression of relevant oncogenes.
Exosome Release by Glucose Deprivation Is Important for the Viability of TSC-Null Cells
Authors: Bae Ji-Hyun , Kim Jong Hyun
Published: September 2022

The control of exosome release is associated with numerous physiological and pathological activities, and that release is often indicative of health, disease, and environmental nutrient stress. Tuberous sclerosis complex (TSC) regulates the cell viability via the negative regulation of the mammalian target of rapamycin complex (mTORC1) during glucose deprivation. However, the mechanism by which viability of TSC-null cells is regulated by mTORC1 inhibition under glucose deprivation remains unclear. Here, we demonstrated that exosome release regulates cell death induced by glucose deprivation in TSC-null cells. The mTORC1 inhibition by rapamycin significantly increased the exosome biogenesis, exosome secretion, and cell viability in TSC-null cells. In addition, the increase in cell viability by mTORC1 inhibition was attenuated by two different types of inhibitors of exosome release under glucose deprivation. Taken together, we suggest that exosome release inhibition might be a novel way for regression of cell growth in TSC-null cells showing lack of cell death by mTORC1 inhibition.
Hybrid Mineral/Organic Material Induces Bone Bridging and Bone Volume Augmentation in Rat Calvarial Critical Size Defects
Authors: Dubus Marie , Scomazzon Loïc , Ledouble Charlotte , Braux Julien , Beljebbar Abdelilah , Van Gulick Laurence , Baldit Adrien , Gorin Caroline , Alem Halima , Bouland Nicole , Britton Marissa , Schiavi Jessica , Vaughan Ted J. , Mauprivez Cédric , Kerdjoudj Halima
Published: September 2022

In craniofacial bone defects, the promotion of bone volume augmentation remains a challenge. Finding strategies for bone regeneration such as combining resorbable minerals with organic polymers would contribute to solving the bone volume roadblock. Here, dicalcium phosphate dihydrate, chitosan and hyaluronic acid were used to functionalize a bone-side collagen membrane. Despite an increase in the release of inflammatory mediators by human circulating monocytes, the in vivo implantation of the functionalized membrane allowed the repair of a critical-sized defect in a calvaria rat model with de novo bone exhibiting physiological matrix composition and structural organization. Microtomography, histological and Raman analysis combined with nanoindentation testing revealed an increase in bone volume in the presence of the functionalized membrane and the formation of woven bone after eight weeks of implantation; these data showed the potential of dicalcium phosphate dihydrate, chitosan and hyaluronic acid to induce an efficient repair of critical-sized bone defects and establish the importance of thorough multi-scale characterization in assessing biomaterial outcomes in animal models.
The EXTREME Regimen Associating Cetuximab and Cisplatin Favors Head and Neck Cancer Cell Death and Immunogenicity with the Induction of an Anti-Cancer Immune Response
Authors: De Azevedo Justine , Mourtada Jana , Bour Cyril , Devignot Véronique , Schultz Philippe , Borel Christian , Pencreach Erwan , Mellitzer Georg , Gaiddon Christian , Jung Alain C.
Published: September 2022

(1) Background: The first line of treatment for recurrent/metastatic Head and Neck Squamous Cell Carcinoma (HNSCC) has recently evolved with the approval of immunotherapies that target the anti-PD-1 immune checkpoint. However, only about 20% of the patients display a long-lasting objective tumor response. The modulation of cancer cell immunogenicity via a treatment-induced immunogenic cell death is proposed to potentially be able to improve the rate of patients who respond to immune checkpoint blocking immunotherapies. (2) Methods: Using human HNSCC cell line models and a mouse oral cancer syngeneic model, we have analyzed the ability of the EXTREME regimen (combination therapy using the anti-EGFR cetuximab antibody and platinum-based chemotherapy) to modify the immunogenicity of HNSCC cells. (3) Results: We showed that the combination of cetuximab and cisplatin reduces cell growth through both cell cycle inhibition and the induction of apoptotic cell death independently of p53. In addition, different components of the EXTREME regimen were found to induce, to a variable extent, and in a cell-dependent manner, the emission of mediators of immunogenic cell death, including calreticulin, HMGB1, and type I Interferon-responsive chemokines. Interestingly, cetuximab alone or combined with the IC50 dose of cisplatin can induce an antitumor immune response in vivo, but not when combined with a high dose of cisplatin. (4) Conclusions: Our observations suggest that the EXTREME protocol or cetuximab alone are capable, under conditions of moderate apoptosis induction, of eliciting the mobilization of the immune system and an anti-tumor immune response in HNSCC.
High-Dose Mycobacterium tuberculosis H37rv Infection in IL-17A- and IL-17A/F-Deficient Mice
Authors: Ritter Kristina , Behrends Jochen , Rückerl Dominik , Hölscher Alexandra , Volz Johanna , Prinz Immo , Hölscher Christoph
Published: September 2022

During experimental tuberculosis (TB), interleukin (IL)-17A appears to be involved in the formation of lung granulomas, possibly through the attraction of neutrophils to the sites of infection. However, the protective impact of cytokine appears to depend on the degree of its induction. Hence, robust production of IL-17A in mice infected with the hypervirulent isolate Mycobacterium tuberculosis (Mtb) HN878 mediates protection, while the cytokine is dispensable for protective immune responses against low-dose infection with the less virulent strain H37rv. Here, we show that after experimental infection with high doses of Mtb H37rv, IL-17A-deficient (−/−) mice exhibited high susceptibility to the infection, which was mediated by the strong accumulation of neutrophils in the infected lung tissue. Accordingly, we observed nearly unrestricted bacterial replication within the neutrophils, indicating that they may serve as a survival niche for Mtb. By use of IL-17A/IL-17F-double-deficient mice, we demonstrated that the susceptibility in the absence of IL-17A is mediated by a compensatory expression of IL-17F, which, however, appeared not to be dependent on neutrophils. Together, our results illustrate the compensatory potential of the Th17-secreted cytokines IL-17A and IL-17F in the context of experimental TB and once again emphasize the detrimental effect of excessive neutrophil infiltration in response to Mtb.
Visual Expressions of Children’s Strengths, Difficulties and Wishes in Person Picking an Apple from a Tree Drawings among Preschoolers Living in Areas of Persistent Political Violence
Authors: Bat Or Michal , Ishai Rafi , Barkay Nirit , Shalev Or
Published: September 2022

The present study sought to inquire into the subjective experience of 156 preschoolers (age 4–6.9 years) living in an area of political violence in Israel (on the border with the Gaza Strip) during a period of massive bombing. Children were invited to draw a Person Picking an Apple from a Tree (PPAT), and were interviewed on their sense of self-potency using the CAMP, a measure of potency. Teachers were asked to report problems in executive functions using a few BRIEF scales; and mothers filled out a questionnaire for maternal distress (BSI), a measure of their child strengths and difficulties (SDQ), and were asked to provide their assessment regarding the extent to which their child was exposed to political violence. Findings reveal associations between mothers’ distress, the degree of exposure of their child to trauma, and the child’s emotional symptoms. PPAT analysis identified four main factors: Tree Generosity, Person Agency, Vividness, and As-Real-R. Positive associations were found between self-potency and the main factors of the drawings; negative associations were found between the child’s difficulties in executive functions and the drawing’s four main factors; and two small negative associations were found between the child’s emotional symptoms and Tree Generosity and As-Real-R factors. The following associations were found within each gender group: mothers’ depression degree was associated with boy’s Tree Generosity, and mother’s perceptions of their girl’s exposure to trauma was related to Person Agency, Tree Generosity, and As-Real-R factors; furthermore, a significant difference was found between the narrative focus of drawings in this sample and the narrative focus of drawings of a sample of the same age group from a non-war zone. In addition, narrative focus was found to be related to children’s self-potency. The discussion deals with the study’s findings through the prism of developmental psychology, self-agency, object-relations, and art-therapy theories.
Wear-Resistant Hydrophobic Coatings from Low Molecular Weight Polytetrafluoroethylene Formed on a Polyester Fabric
Authors: Prorokova Natalia P. , Kumeeva Tatyana Yu. , Kholodkov Igor V.
Published: September 2022

The paper presents a comparative analysis of the surface structure and morphology of hydrophobic coatings formed on a polyester fabric from various types of low molecular weight tetrafluoroethylenes by a new method. The low molecular weight compounds used include: ultrafine polytetrafluoroethylene of the FORUM® trademark prepared through thermo-gas-dynamic decomposition of industrial polytetrafluoroethylene waste, and tetrafluoroethylene telomers, synthesized by radiation-chemical initiation from fluoromonomers in acetone, butyl chloride and trimethylchlorosilane solutions. The formation of coatings consists in deposition of low molecular weight tetrafluoroethylenes from solutions in supercritical carbon dioxide and organic solvents. The contact angle and water absorption of the polyester fabric with coatings containing the specified water-repellents are determined. The resistance of the achieved effect to various types of wear—washing, dry cleaning and abrasionis evaluated. The hydrophobic properties of the fabric are found to be affected by the coating plasticity characterized by the stiffness coefficient. The importance of this indicator to targeted changes in fabric properties is proved. All the considered types of low molecular weight polytetrafluoroethylene (PTFE) are shown to be effective water-repellents for the polyester fabric.
Characterization of Defects in GaN: Optical and Magnetic Resonance Techniques
Authors: Freitas Jaime A. , Culbertson James C. , Glaser Evan R.
Published: September 2022

GaN and its alloys with InN and AlN are of technological importance for a variety of optical, electronic, and optoelectronic devices due to its high thermal conductivity, wide band gap, high breakdown voltage and high saturation velocity. GaN-based devices now provide superior performance for a variety of high power, high frequency, high temperature, and optical applications. The major roadblock for the full realization of Nitride semiconductor potential is still the availability of affordable large-area and high-quality native substrates with controlled electrical properties. Despite the impressive accomplishments recently achieved by techniques such as hydride vapor phase epitaxy and ammonothermal for GaN growth, much more must be attained before establishing a fully satisfactory bulk growth method for this material. Recent results suggest that ammonothermal GaN wafers can be successfully used as seeds to grow thick freestanding GaN wafers by hydride vapor phase epitaxy. A brief review of defect-sensitive optical and paramagnetic spectroscopy techniques employed to evaluate structural, optical, and electronic properties of the state-of-the-art bulk and thick-film (quasi-bulk) Nitride substrates and homoepitaxial films is presented. Defects control the performance of devices and feeding back knowledge of defects to growth efforts is key to advancing technology.
A First-Principles Study of F and Cl Doping in LiNi0.83Co0.08Mn0.08O2 Cathode Materials
Authors: Yao Can , Zhou Changdong , Cheng Benjun , Li Mao
Published: September 2022

Ion doping can modify the cell structure, which is one of the effective methods to improve electrochemical performance. However, there is a lack of research on F- and Cl-doped LiNi0.8Co0.1Mn0.1O2. In this paper, the effects of F and Cl doping on the electrochemical properties and cell structure of LiNi0.83Co0.08Mn0.08O2 during the process of lithium removal were studied by a first-principles calculation based on density functional theory. The results show that F doping reduces the change in cell parameters and improves the stability of cell structure. On the contrary, Cl doping reduces the stability of the cell structure. F doping increased the delithiation potential from 3.64 V to 3.76 V, and the delithiation potential was relatively stable in the process of delithiation. Cl doping decreased the delithiation potential from 3.64 V to 3.26 V, and the voltage stability became worse. F doping can effectively reduce the occurrence of Li–Ni mixed arrangement phenomena. Meanwhile, Cl doping can inhibit the formation of oxygen vacancies, and the further degradation of the materials. F doping broadens the Li+ diffusion channel away from the doping site and improves the diffusion rate of Li+ in this layer. In the vicinity of F-doped sites, the electrostatic field in the process of Li+ diffusion is enhanced and the diffusion of Li+ is reduced. Cl doping increases the diffusion barrier of Li+ and slows down the diffusion rate of Li+.
Structural Characterization and Dynamics of a Layered 2D Perovskite [NH3(CH2)5NH3]MnCl4 Crystal near Phase Transition Temperature
Authors: Lim Ae Ran , Na Yeji
Published: September 2022

[NH3(CH2)5NH3]MnCl4 crystals are grown via slow evaporation, and the crystal undergoes a phase transition at 298 K (TC) according to differential scanning calorimetry, and the structures determined via X-ray diffraction at 173 and 333 K are orthorhombic systems in the space group Imma. These results differed slightly from those previously reported, and the reasons for this are analyzed. The thermal stability is relatively high, with a thermal decomposition temperature of approximately 570 K. The 1H spin-lattice relaxation times t1ρ exhibited very large variations, as indicated by the large thermal displacement around the 1H atoms, suggesting energy transfer at ~TC, even if no structural changes occurred. The influences of the chemical shifts of 1H of NH3 and short t1ρ of C1 adjacent to NH3 in cation are insignificant, indicating a minor change in the N−H⋯Cl hydrogen bond related to the coordination geometry of the MnCl6 octahedron. These properties will be make it a potential application for eco-friendly solar cells.
Floristics and Biogeographical Affinity of Diatoms Attached to Sargassum fluitans (Børgesen) Børgesen and Sargassum natans (Linnaeus) Gaillon Arriving on Mexico’s Caribbean Coasts
Authors: López-Fuerte Francisco , Siqueiros Beltrones David , Martínez Yuriko , Altamirano-Cerecedo María
Published: September 2022

The environmental contingency caused by the recent massive arrivals of pelagic sargasso (Sargassum natans and S. fluitans) on Mexico’s Caribbean coasts have given rise to several areas of scientific research. Our work proposed identifying the diatom flora adhered to the thalli of these two sargasso species collected on the coasts of Cancun, Isla Mujeres, and Puerto Morelos. We recorded 184 diatom taxa (all illustrated) from 68 genera. Taxa from the genera Mastogloia (37), Cocconeis (11), Nitzschia (10), Diploneis (8), and Amphora (9) represented 41% of the total, while 44 of these genera were represented by a single species. In the total floristic count, 41 taxa occurred exclusively on S. fluitans, 53 exclusively on S. natans (22 and 29%, respectively) and 90 (49%) were found on both. Species of Navicula were scarce, and Navicula barbara var. densestriata was here transferred to the genus Lyrella (Lyrella barbara var. densestriata (Foged) López-Fuerte & Siqueiros Beltrones comb. nov.). Overall, 17 (9%) of the identified taxa were new recordings for Mexico’s coasts. Supporting the hypothesis proposed, the 37 Mastogloia taxa suggested a tropical affinity, while the high species richness denoted that the surfaces of both sargasso species constituted favorable substrata for the growth of diatom assemblages.
Utility–Privacy Trade-Off in Distributed Machine Learning Systems
Authors: Zeng Xia , Yang Chuanchuan , Dai Bin
Published: September 2022

In distributed machine learning (DML), though clients’ data are not directly transmitted to the server for model training, attackers can obtain the sensitive information of clients by analyzing the local gradient parameters uploaded by clients. For this case, we use the differential privacy (DP) mechanism to protect the clients’ local parameters. In this paper, from an information-theoretic point of view, we study the utility–privacy trade-off in DML with the help of the DP mechanism. Specifically, three cases including independent clients’ local parameters with independent DP noise, dependent clients’ local parameters with independent/dependent DP noise are considered. Mutual information and conditional mutual information are used to characterize utility and privacy, respectively. First, we show the relationship between utility and privacy for the three cases. Then, we show the optimal noise variance that achieves the maximal utility under a certain level of privacy. Finally, the results of this paper are further illustrated by numerical results.
Opinion Dynamics with Higher-Order Bounded Confidence
Authors: Wang Chaoqian
Published: September 2022

The higher-order interactions in complex systems are gaining attention. Extending the classic bounded confidence model where an agent’s opinion update is the average opinion of its peers, this paper proposes a higher-order version of the bounded confidence model. Each agent organizes a group opinion discussion among its peers. Then, the discussion’s result influences all participants’ opinions. Since an agent is also the peer of its peers, the agent actually participates in multiple group discussions. We assume the agent’s opinion update is the average over multiple group discussions. The opinion dynamics rules can be arbitrary in each discussion. In this work, we experiment with two discussion rules: centralized and decentralized. We show that the centralized rule is equivalent to the classic bounded confidence model. The decentralized rule, however, can promote opinion consensus. In need of modeling specific real-life scenarios, the higher-order bounded confidence is more convenient to combine with other higher-order interactions, from the contagion process to evolutionary dynamics.
AP Shadow Net: A Remote Sensing Shadow Removal Network Based on Atmospheric Transport and Poisson’s Equation
Authors: Li Fan , Wang Zhiyi , He Guoliang
Published: September 2022

Shadow is one of the fundamental indicators of remote sensing image which could cause loss or interference of the target data. As a result, the detection and removal of shadow has already been the hotspot of current study because of the complicated background information. In the following passage, a model combining the Atmospheric Transport Model (hereinafter abbreviated as ATM) with the Poisson Equation, AP ShadowNet, is proposed for the shadow detection and removal of remote sensing images by unsupervised learning. This network based on a preprocessing network based on ATM, A Net, and a network based on the Poisson Equation, P Net. Firstly, corresponding mapping between shadow and unshaded area is generated by the ATM. The brightened image will then enter the Confrontation identification in the P Net. Lastly, the reconstructed image is optimized on color consistency and edge transition by Poisson Equation. At present, most shadow removal models based on neural networks are significantly data-driven. Fortunately, by the model in this passage, the unsupervised shadow detection and removal could be released from the data source restrictions from the remote sensing images themselves. By verifying the shadow removal on our model, the result shows a satisfying effect from a both qualitative and quantitative angle. From a qualitative point of view, our results have a prominent effect on tone consistency and removal of detailed shadows. From the quantitative point of view, we adopt the non-reference evaluation indicators: gradient structure similarity (NRSS) and Natural Image Quality Evaluator (NIQE). Combining various evaluation factors such as reasoning speed and memory occupation, it shows that it is outstanding among other current algorithms.
Cultural Production, Reproduction and Subversion of Gender Stereotyping among Pre-Service Science Teachers: Insights from Science Educators
Authors: Allu Daniel , Govender Nadaraj , James Angela
Published: September 2022

We perceive contestations between science, education and women’s engagement and have raised disruptions in their act of knowing and mobility in science education. This study explored science educators’ views, beliefs and actions of reproduction and subversion of gender stereotyping at a teacher education college in Nigeria. Six science educators were selected based on comprehensive gender information that facilitated conduction of the study. The six educators were purposively selected out of 11 educators who completed and returned the questionnaire. A qualitative approach and case study framed the research using instruments such as questionnaires, interviews, and classroom observation schedules. Thematic analysis and coding were done. Educators consciously and unconsciously reproduced gender stereotypes beliefs and practices. Educators explicitly and implicitly engaged in unequal distribution of cognitive activities amongst pre-service teachers influenced by their practice of cultural norms and patriarchal ideology. The findings revealed multiple oppressions females faced, contradictory science classrooms, and political and democratic classroom space for negotiating and renegotiating discriminatory classroom beliefs, perception and views of educators during science engagements. However, several possibilities such as political advocacy, productive activism and transformative resistance for educators to re-negotiate discriminatory gendered space through constructive gender equality awareness for freedom and intellectual growth in science education could be emancipatory possibilities.
Specific Emitter Identification Based on Self-Supervised Contrast Learning
Authors: Liu Bo , Yu Hongyi , Du Jianping , Wu You , Li Yongbin , Zhu Zhaorui , Wang Zhenyu
Published: September 2022

The current deep learning (DL)-based Specific Emitter Identification (SEI) methods rely heavily on the training of massive labeled data during the training process. However, the lack of labeled data in a real application would lead to a decrease in the method’s identification performance. In this paper, we propose a self-supervised method via contrast learning (SSCL), which is used to extract fingerprint features from unlabeled data. The proposed method uses large amounts of unlabeled data to constitute positive and negative pairs by designing a composition of data augmentation operations for emitter signals. Then, the pairs would be input into the neural network (NN) for feature extraction, and a contrastive loss function is introduced to drive the network to measure the similarity among data. Finally, the identification model can be completed by fixing the parameters of the feature extraction network and fine-tuning with few labeled data. The simulation experiment result shows that, after being fine-tuned, the proposed method can effectively extract fingerprint features. When the SNR is 20 dB, the identification accuracy reaches 94.45%, which is better than the current mainstream DL approaches.
ISUC: IoT-Based Services for the User’s Comfort
Authors: Abbas Rizwan , Amran Gehad Abdullah , Mohsan Syed Agha Hassnain , Alsharif Mohammed H. , Jahid Abu , Marey Mohamed , Mostafa Hala
Published: September 2022

Emotions are alluded to as characteristic intuitive perspectives from certain conditions or temperaments. IoT applications can help in routine tasks and businesses. Most advances have not been taken advantage of regarding emotions. Emotions could be detected via the data gathered through IoT. Our investigation of related works revealed an absence of strategic methodologies in planning IoT frameworks according to feelings and shrewd alteration rules; thus, we present a philosophy that can rapidly assist in planning an IoT framework in this situation, where the identification of users is significant. We applied the proposed phases to test an IoT recommender framework named ISUC. The framework involves anticipating a user’s future emotions by utilizing boundaries gathered from IoT gadgets. It suggests new exercises for the user to obtain the ‘last’ state. Experimental results confirm our recommended framework has achieved over 85% exactness in anticipating users’ emotions in the future. The examination results presumed that an IoT-based framework could be created to detect positive emotions (e.g., peace, concretism, patience, enjoyment, and comfort) and negative emotions (e.g., irritation, abstraction, impatience, displeasure, and discomfort) to incite good emotions.
A 5.67 ENOB Vector Matrix Multiplier with Charge Storage FET Cells and Non-Linearity Compensation Techniques
Authors: Hwang Jin-Young , Ryu Young-Taek , Kwon Kee-Won
Published: September 2022

In this paper, we provide a thorough analysis and enhancement techniques of the linearity between the input voltage and output current in charge storage field effect transistor (FET) cells for a vector–matrix multiplier array in neural networks. A planar floating gate FET cell revealed superior linearity, because of boosting the floating gate using a drain voltage through capacitive coupling. If the coupling capacitance is extended by up to half of the gate capacitance, the coefficient of determination for linear regression is easily greater than 99.5%. However, the linearity of the charge trap FET, which keeps electrons in the insulating gate dielectric, must be compensated by either boosting the drain voltage, using a non-linear input driver, or supplying a quadratic current through an auxiliary path in the cell. Drain voltage boosting is limitedly effective over a small input range, while the auxiliary current path shows a coefficient of determination greater than 99.5% over a 500 mV input range. If the cell area matters, the charge trap FET with a diode connected FET as an auxiliary current path revealed the best performance, with an effective number of bits of 5.67, in a 21.3 F2 cell area.
Characterization of Microstructures in Lacustrine Organic-Rich Shale Using Micro-CT Images: Qingshankou Formation in Songliao Basin
Authors: Cao Yan , Wu Qi , Jin Zhijun , Zhu Rukai
Published: September 2022

In order to explore the development characteristics and influencing factors of microscale pores in lacustrine organic-rich muddy shale, this study selected five shale samples with different mineral compositions from the Qingshankou Formation in the Songliao Basin. The oil content and mineralogy of the shale samples were obtained by pyrolysis and X-ray diffraction analysis, respectively, while the porosity of the samples was computed by micro-CT imaging. Next, based on the CT images, the permeability of each sample was calculated by the Avizo software. Results showed that the continuous porosity of Qingshankou shale in the Songliao Basin was found between 0.84 and 7.79% (average 4.76%), the total porosity between 1.87 and 12.03% (average 8.28%), and the absolute permeability was calculated between 0.061 and 2.284 × 10−3 μm2. The total porosity of the samples has a good positive correlation with the continuous porosity and permeability. This means higher values of total porosity suggested better continuous porosity and permeability. Both total porosity and continuous porosity are positively correlated with the content of clay minerals. Moreover, the oil content of the samples (the S1 peak from programmed pyrolysis) exhibits a good positive correlation with the total porosity, continuous porosity, permeability, and clay mineral content. Therefore, pores that are developed by clay minerals are the main storage space for oil and flow conduits as well. Clay minerals were found to be the main controlling factor in the porosity, permeability, and the amount of oil content in the pores in the study area.
Recent Advances in Hydrothermal Carbonization of Sewage Sludge
Authors: Jellali Salah , Zorpas Antonis A. , Alhashmi Sulaiman , Jeguirim Mejdi
Published: September 2022

The transition from the use of fossil fuels to renewable and green energy is a worldwide challenge that must be seriously considered in order to ensure sustainable development and the preservation of the environment. The conversion of wet biomasses (i.e., sewage sludge) into energy through thermochemical processes in general and hydrothermal carbonization (HTC) in particular has been pointed out as an interesting and attractive approach for the energetic and agricultural valorization of the produced solid residues, named hydrochars. The success of such valorization options is highly dependent on these hydrochars’ physico-chemical and energetic properties that are influenced not only by the type of the sludge (urban or industrial) and its nature (primary, secondary, or digested) but also by the HTC parameters, especially temperature, pressure, and residence time. This editorial provides a summary of the latest studies regarding the impact of the cited above parameters on the properties of the produced hydrochars. The economic and environmental feasibility of this process for sewage sludge management is also presented.
Ensemble Learning Techniques-Based Monitoring Charts for Fault Detection in Photovoltaic Systems
Authors: Harrou Fouzi , Taghezouit Bilal , Khadraoui Sofiane , Dairi Abdelkader , Sun Ying , Hadj Arab Amar
Published: September 2022

Over the past few years, there has been a significant increase in the interest in and adoption of solar energy all over the world. However, despite ongoing efforts to protect photovoltaic (PV) plants, they are continuously exposed to numerous anomalies. If not detected accurately and in a timely manner, anomalies in PV plants may degrade the desired performance and result in severe consequences. Hence, developing effective and flexible methods capable of early detection of anomalies in PV plants is essential for enhancing their management. This paper proposes flexible data-driven techniques to accurately detect anomalies in the DC side of the PV plants. Essentially, this approach amalgamates the desirable characteristics of ensemble learning approaches (i.e., the boosting (BS) and bagging (BG)) and the sensitivity of the Double Exponentially Weighted Moving Average (DEWMA) chart. Here, we employ ensemble learning techniques to exploit their capability to enhance the modeling accuracy and the sensitivity of the DEWMA monitoring chart to uncover potential anomalies. In the ensemble models, the values of parameters are selected with the assistance of the Bayesian optimization algorithm. Here, BS and BG are adopted to obtain residuals, which are then monitored by the DEWMA chart. Kernel density estimation is utilized to define the decision thresholds of the proposed ensemble learning-based charts. The proposed monitoring schemes are illustrated via actual measurements from a 9.54 kW PV plant. Results showed the superior detection performance of the BS and BG-based DEWMA charts with non-parametric threshold in uncovering different types of anomalies, including circuit breaker faults, inverter disconnections, and short-circuit faults. In addition, the performance of the proposed schemes is compared to that of BG and BS-based DEWMA and EWMA charts with parametric thresholds.
A Novel Condition Monitoring Method of Wind Turbines Based on GMDH Neural Network
Authors: Tian Xiange , Jiang Yongjian , Liang Chen , Liu Cong , Ying You , Wang Hua , Zhang Dahai , Qian Peng
Published: September 2022

The safety of power transmission systems in wind turbines is crucial to the wind turbine’s stable operation and has attracted a great deal of attention in condition monitoring of wind farms. Many different intelligent condition monitoring schemes have been developed to detect the occurrence of defects via supervisory control and data acquisition (SCADA) data, which is the most commonly applied condition monitoring system in wind turbines. Normally, artificial neural networks are applied to establish prediction models of the wind turbine condition monitoring. In this paper, an alternative and cost-effective methodology has been proposed, based on the group method of data handling (GMDH) neural network. GMDH is a kind of computer-based mathematical modelling and structural identification algorithm. GMDH neural networks can automatically organize neural network architecture by heuristic self-organization methods and determine structural parameters, such as the number of layers, the number of neurons in hidden layers, and useful input variables. Furthermore, GMDH neural network can avoid over-fitting problems, which is a ubiquitous problem in artificial neural networks. The effectiveness and performance of the proposed method are validated in the case studies.