bluuebunny/crossref_metadata_2025 huggingface dataset:
Femtosecond-Level Frequency Transfer at 10 GHz over Long Fiber Link with Optical–Electronic Joint Compensation
Authors: Huang Wantao , Li Yang , Zhang Peng , Fang Lujun , Hou Dong
Published: November 2022

We report a fiber-optic 10 GHz frequency transfer technique based on an optical–electronic joint phase compensator. A highly stable frequency signal at 10 GHz was transferred in a 50-km long fiber link by using this technique. Two key parameters of the frequency dissemination, the timing fluctuation and frequency stability were both measured. The experimental results show the root-mean-square timing fluctuation of the transferred microwave is about 103 fs within 10,000 s, and the frequency stability for the transmission link is 2.2 × 10−14 at 1 s and 8.5 × 10−17 at 2000 s. The technique proposed in this paper provides a powerful tool which can be used to transfer atomic clocks (e.g., commercial H-master and Cs clocks) in a long fiber link.
Definition of Urban Built Environment Climate Adaptive Design Actions Aided by Environmental Data-Driven Design Processes
Authors: Bassolino Eduardo
Published: November 2022

Environmental and technological design for climate adaptation in the urban built environment can no longer be separated from the generation, collection, or use of data (big data). ICT tools (Information and Communication Technologies), for the modelling and simulation of the built urban environment are identified as measuring devices and provide knowledge on the impacts of climate change in design practice based on an environmentally data-driven approach. This study aims to define a framework for the evaluation of environmental health and comfort parameters applicable to simulation tools, with a specific focus on thermal and environmental exchanges between indoor and outdoor spaces, to define those factors that affect the perception of user’s well-being in thermal stress conditions (e.g., heatwaves), both indoor and outdoor. Through the definition of two study cases in the city of Naples, Italy, special attention was paid to investigating the interaction between outdoor and indoor performance when urban temperatures rise. A comparison between a daily survey for occupants and simulations was conducted to confirm the validity of the data obtainable from the perceived thermal sensations. The obtained results show that the designed framework can reliably simulate real outdoor and indoor conditions according to comfort indices such as the predicted mean vote and adaptive comfort model. The methodological framework developed can guarantee the interoperability of data to simulate indoor and outdoor environments responding to real conditions and determine a favourable condition for the development of urban redevelopment interventions through the application of climate adaptive design strategies.
Influence of Seasonal Air–Sea Interaction on the Interannual Variation of the NPP of Terrestrial Natural Vegetation in China
Authors: Bai Hui , Xiao Fengjin , Zhang Guo , Liu Qiufeng , Qin Yun , Liao Yaoming
Published: November 2022

Based on Moderate Resolution Imaging Spectoradiometer (MODIS) remote sensing data, meteorological observation data, multisource atmospheric circulation, and sea surface temperature (SST) data from NCEP/NCAR reanalysis, we estimated the net primary productivity (NPP) of terrestrial natural vegetation in China according to the CASA model and analyzed the linear trend and interannual fluctuation of NPP, as well as the spatial distribution characteristics of the annual NPP response to climatic factors. The obtained results revealed the impact of air–sea interaction on interannual NPP variability in key climatic areas. In China, the annual NPP of natural vegetation, linear NPP trend, and interannual NPP fluctuation showed significant regional characteristics. The annual NPP exhibited a significant increasing trend and interannual fluctuation in North China and Northeast China, with spatially consistent responses from NPP to precipitation and temperature. On the seasonal time scale, NPP in the key climatic area (105~135° E, 35~55° N) exhibited a strong response to both summer precipitation and mean temperature. In the summer atmospheric circulation, the circulation anomaly area is mainly distributed in the northeast cold vortex area in the middle- and high-latitude westerlies in East Asia and in the Sea of Okhotsk with dipole circulation. In the SST of the preceding winter and spring, the key SST anomaly area was the Kuroshio region, with an impact of the Kuroshio SST anomaly on the interannual variation in annual NPP in the key climatic area. The cold vortex in Northeast China played a pivotal role in the influence of the SST anomaly in the Kuroshio region on atmospheric circulation anomalies, resulting in abnormal summer precipitation in the key climatic region and affecting the annual accumulation of NPP of natural vegetation.
Does Light Pollution Affect Nighttime Ground-Level Ozone Concentrations?
Authors: Shith Syabiha , Ramli Nor Azam , Awang Norrimi Rosaida , Ismail Mohd Rodzi , Latif Mohd Talib , Zainordin Nazatul Syadia
Published: November 2022

Ground-level ozone (O3) is mainly produced during daytime in the presence of ultraviolet (UV) light and later destroyed by nitrogen oxides during nighttime. However, light pollution caused by the excessive use of artificial lights may disrupt the chemistry of night-time ground-level O3 by providing enough energy to initiate nighttime ground-level O3 production. In this study, nighttime (7 p.m. to 7 a.m.) ground-level O3, nitrogen oxide (NO), and nitrogen dioxides (NO2) concentrations were observed for three years (2013, 2014, and 2015). The existence of O3 was found during nighttime, especially in urban areas with a concentration range of 8–20 ppb. The results suggested that nighttime variations of ground-level O3 concentrations were higher in urban areas than in suburban areas. The mean nighttime O3 concentration at urban sites varied, possibly because the distribution of anthropogenic lights around the urban sites is brighter than in suburban locations, as indicated by the data from the light-pollution map. This anthropogenic light has not caused the suspected nighttime photolysis processes, which directly slowed nighttime oxidation. The photochemistry rate of JNO2/k3 was supposed to be near zero because of the absence of photochemical reactions at night. However, the minimum concentration in all urban and suburban sites ranged from 2–3 ppb, indicating that O3 might also form at night, albeit not due to light pollution.
Extended Calculations of Atomic Structure Parameters for Na-like Ar, Kr and Xe Ions Using Relativistic MCDHF and MBPT Methods
Authors: Rathi Shikha , Sharma Lalita
Published: November 2022

In this study, comprehensive calculations of energies, hyperfine structure constants, Landé gJ factors and isotope shifts have been performed for the lowest 71 states of Na-like Ar7+, Kr25+ and Xe43+ ions. Radiative parameters viz., wavelengths, transition rates, oscillator strengths and lifetimes are estimated for the electric dipole E1 transitions among these levels. The states under consideration include 1s22s22p6nl for n = 3–9, l = 0–6, and the fully relativistic multiconfiguration Dirac–Hartree–Fock (MCDHF) method integrated in the latest version of the general-purpose relativistic atomic structure package (GRASP2018) is used for the calculations. The additional corrections, such as the Breit interaction and quantum electrodynamics effects are included in the relativistic configuration interaction calculations, and their effects on energies and other parameters are analysed. We examined the impact of including the core–core and core–valence correlations on level energies. Furthermore, to inspect the reliability of our MCDHF results, we performed another set of calculations using the many-body perturbation theory built into the Flexible Atomic Code (FAC). Moreover, we estimated the uncertainties in the computed lifetimes and transition parameters and assigned their accuracy class. A thorough comparison between the two obtained calculations and with the previous theoretical and experimental results, wherever available, is carried out and a good agreement is observed.
Domainal Investigation of a Quartz-Fluorite Composite Using Spectroscopic Techniques
Authors: Dubey Sonali , Rai Abhishek Kumar , Pati Jayanta Kumar , Kumar Rohit , Dwivedi Mrigank Mauli , Rai Awadhesh Kumar
Published: November 2022

The analysis of geological samples that have several chemically diffused zones which formed under certain physico-chemical condition is difficult to achieve. The quantitative estimations of the minerals in such samples are tedious. The present work demonstrates the application of LIBS for qualitative and quantitative analyses of a quartz-fluorite composite which was procured from an amygdaloidal basalt from Deccan Traps, India. The presence of weak emission lines of F in the spectral range of 200–900 nm makes it challenging to quantify the fluorine. This study has addressed a promising alternative to quantify the fluorine using electronic bands of CaF molecules observed in the Laser-induced Breakdown Spectroscopy (LIBS) spectrum. In addition to this spectroscopic technique, the authors also have used Photoacoustic Spectroscopy (PAS) and UV-VIS spectroscopy technique to obtain molecular information from the geological sample. Principal Component Analysis (PCA) was applied to a truncated spectral region of the CaF molecule, and it showed 99% variance. Further, the obtained results with these spectroscopic techniques were compared with the results that were obtained from X-ray diffraction and Electron Probe Micro Analyzer, and they show good agreement. Thus, the LIBS technique can be promising for in situ profile section (varies from few microns to centimeters size) studies without the sample’s destruction using the point detection capability of LIBS.
Fission Mechanism of 235U+n Reaction According to the Symmetrical Atomic Nucleus Model
Authors: Denisov Vladimir A. , Razinkin Vladimir P. , Atuchin Victor V.
Published: November 2022

In this study, the variants of structures are considered for fission fragments of the 235U nucleus caused by thermal neutrons, depending on differences in the initial configuration of proton, neutron and alpha particle compositions, according to a symmetrical model developed for the atomic nucleus. The proposed model is based on the principles of spatial symmetry and the analysis of the binding energy of the nucleus, taking into account the quark structure of nucleons. For the first time, the number of alpha particles in the composition of the 235U nucleus is considered to be 44 and the total number of connections between nucleons is 292. The work compares the binding energy of fragments of the atomic nucleus 235U, which have the same number of protons and neutrons in their composition, but a different number of alpha particles. The results obtained are the basis for an experimental study on the energy characteristics of various fission options of the 235U+n reaction, which is of interest for improving the efficiency of nuclear power sources.
Joint Approximation of Analytic Functions by Shifts of the Riemann Zeta-Function Twisted by the Gram Function II
Authors: Laurinčikas Antanas
Published: November 2022

Let tτ be a solution to the equation θ(t)=(τ−1)π, τ>0, where θ(t) is the increment of the argument of the function π−s/2Γ(s/2) along the segment connecting points s=1/2 and s=1/2+it. tτ is called the Gram function. In the paper, we consider the approximation of collections of analytic functions by shifts of the Riemann zeta-function (ζ(s+itτα1),…,ζ(s+itταr)), where α1,…,αr are different positive numbers, in the interval [T,T+H] with H=o(T), T→∞, and obtain the positivity of the density of the set of such shifts. Moreover, a similar result is obtained for shifts of a certain absolutely convergent Dirichlet series connected to ζ(s). Finally, an example of the approximation of analytic functions by a composition of the above shifts is given.
RETRACTED: Diabetic Retinopathy Progression Prediction Using a Deep Learning Model
Authors: Hosni Mahmoud Hanan
Published: November 2022

Diabetes is an illness that happens with a high level of glucose in the body, and can harm the retina, causing permanent loss vision or diabetic retinopathy. The fundus oculi method comprises detecting the eyes to perform a pathology test. In this research, we implement a method to predict the progress of diabetic retinopathy. There is a research gap that exists for the detection of diabetic retinopathy progression employing deep learning models. Therefore, in this research, we introduce a recurrent CNN (R-CNN) model to detect upcoming visual field inspections to predict diabetic retinopathy progression. A benchmark dataset of 7000 eyes from healthy and diabetic retinopathy progress cases over the years are utilized in this research. Approximately 80% of ocular cases from the dataset is utilized for the training stage, 10% of cases are used for validation, and 10% are used for testing. Six successive visual field tests are used as input and the seventh test is compared with the output of the R-CNN. The precision of the R-CNN is compared with the regression model and the Hidden Markov (HMM) method. The average prediction precision of the R-CNN is considerably greater than both regression and HMM. In the pointwise classification, R-CNN depicts the least classification mean square error among the compared models in most of the tests. Also, R-CNN is found to be the minimum model affected by the deterioration of reliability and diabetic retinopathy severity. Correctly predicting a progressive visual field test with the R-CNN model can aid physicians in making decisions concerning diabetic retinopathy.
Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences
Authors: Shukla Amit K.
Published: November 2022

With more than 50 years of literature, fuzzy logic has gradually progressed from an emerging field to a developed research domain, incorporating the sub-domain of mathematical fuzzy logic (MFL) [...]
An Experimental Study on the Cell Balancing Parameters for Faulty Cell Detection in a Battery Module
Authors: Choi Woongchul , Hong Sungsoo
Published: November 2022

Along with global efforts to reduce the carbon footprint, electrification of powertrains is occurring in various applications, certainly including transportation systems. One of the most important components is an electric energy storage system, i.e., a battery pack. Regardless of battery form factors, such as cylindrical, pouch and prismatic type, it is critical to maintain the safety of the battery module/pack by monitoring the conditions of each and every battery cell of the battery pack. It becomes even more critical as the battery cells are used over many charging and discharging cycles. Thermal runaways of the battery packs can even be triggered by a single faulty battery cell which degrades in an unexpected manner and speed compared to the neighboring battery cells, resulting in extreme fire hazards. Typically, this faulty cell with an abnormally increased internal resistance can be detected using a voltage sensor or a temperature sensor. However, in this study, instead of depending on those sensors, activities of cell balancing switching devices are used to identify a degraded cell compared to other cells in a relative manner. A currently proposed faulty cell detection algorithm was developed through multiple simulations with Matlab Simulink®, then, a simple BMS prototype was built and tested as a proof of concept.
Engineering Auxetic Cylinders and Intestine to Improve Longitudinal Intestinal Lengthening and Tailoring Procedure
Authors: Valentini Luca , Chiesa Irene , De Maria Carmelo , Ugolini Sara , Volpe Yary , Mussi Elisa , Pappalardo Lucia , Coletta Riccardo , Morabito Antonino
Published: November 2022

Auxetic materials can be exploited for coupling different types of tissues. Herein, we designed a material where the microorganism metabolic activity yields the formation of buckled/collapsed bubbles within gelling silicone cylinders thus providing auxetic properties. The finite element model of such hollow auxetic cylinders demonstrated the tubular structure to promote worm-like peristalsis. In this scenario, the described hybrid auxetic structures may be applied to the longitudinal intestinal lengthening and tailoring procedure to promote enteral autonomy in short bowel syndrome. The presented material and analytical design synergistic approach offer a pioneering step for the clinical translation of hybrid auxetic materials.
Central Neuropathic Pain Development Modulation Using Coffee Extract Major Polyphenolic Compounds in Spinal-Cord-Injured Female Mice
Authors: Soler-Martínez Roger , Deulofeu Meritxell , Bagó-Mas Anna , Dubový Petr , Verdú Enrique , Fiol Núria , Boadas-Vaello Pere
Published: November 2022

It was recently shown that coffee polyphenolic extract exerts preventive effects on central neuropathic pain development, but it is unknown whether its beneficial effects are associated with only one of its major polyphenolic compounds or if the whole extract is needed to exert such effects. The main objective of this study was to determine whether the separate administration of major polyphenols from coffee extract exerts preventive effects on the development of central neuropathic pain in mice compared with the effects of the whole coffee extract. Thus, spinal-cord-injured female ICR-CD1 mice were daily treated with either coffee extract or its major polyphenolic compounds during the first week, and reflexive and nonreflexive pain responses were evaluated within the acute phase of spinal cord injury. In addition, the injury-induced gliosis and dorsal horn sprouting were evaluated with immunohistochemistry. The results showed that the coffee extract prevented spinal cord injury-induced neuropathic pain, whereas its major polyphenolic compounds resulted in reflexive pain response attenuation. Both preventive and attenuation effects were associated with gliosis and afferent fiber sprouting modulation. Overall, the results suggested that coffee extract effects may be associated with potential synergistic mechanisms exerted by its major polyphenolic compounds and not by the sole effect of only one of them.
Butterfly Wing Color Pattern Modification Inducers May Act on Chitin in the Apical Extracellular Site: Implications in Morphogenic Signals for Color Pattern Determination
Authors: Otaki Joji M. , Nakazato Yugo
Published: November 2022

Butterfly wing color patterns are modified by various treatments, such as temperature shock, injection of chemical inducers, and covering materials on pupal wing tissue. Their mechanisms of action have been enigmatic. Here, we investigated the mechanisms of color pattern modifications using the blue pansy butterfly Junonia orithya. We hypothesized that these modification-inducing treatments act on the pupal cuticle or extracellular matrix (ECM). Mechanical load tests revealed that pupae treated with cold shock or chemical inducers were significantly less rigid, suggesting that these treatments made cuticle formation less efficient. A known chitin inhibitor, FB28 (fluorescent brightener 28), was discovered to efficiently induce modifications. Taking advantage of its fluorescent character, fluorescent signals from FB28 were observed in live pupae in vivo from the apical extracellular side and were concentrated at the pupal cuticle focal spots immediately above the eyespot organizing centers. It was shown that chemical modification inducers and covering materials worked additively. Taken together, various modification-inducing treatments likely act extracellularly on chitin or other polysaccharides to inhibit pupal cuticle formation or ECM function, which probably causes retardation of morphogenic signals. It is likely that an interactive ECM is required for morphogenic signals for color pattern determination to travel long distances.
Genetic Characterization and Alternative Preservation Ways of Locally Adapted Sheep Breeds: Cases of Private and Public Sheep Sectors in Tunisia and Italy
Authors: Ben Sassi-Zaidy Yousra , Mohamed-Brahmi Aziza , Aloulou Rafik , Charfi-Cheikhrouha Faouzia , Cendron Filippo , Tormen Nicola , Cassandro Martino
Published: November 2022

Non-commercialized sheep breeds known as local or native breeds are well adapted to their environmental constraints and constitute precious genetic resources that need prioritization for genetic diversity characterization and preservation. The aim of the present study was to assess the genetic diversity level and the related preservation decisions of very old and traditional native Mediterranean sheep breeds from Tunisia and Italy using 17 microsatellite markers. In total, 975 sheep were sampled from five Tunisian, one Center Italian, and four Venetian native breeds. Both private and publicly available farms were considered for each breed for breeding strategies’ comparison purposes. The microsatellite set used was highly informative (PIC = 0.80 ± 0.08), with a total of 383 alleles. Moderate genetic differentiation was revealed between the native sheep of the two Mediterranean sides (global overall loci FST = 0.081). The genetic diversity level was higher in the case of the Tunisian native breeds compared to the Italian ones, as evidenced by higher mean allelic richness, higher expected and observed heterozygosities, and lower inbreeding levels. Priority for conservation suggestions was carried out for each private or public breed population based on the contribution of each population to the diversity of the whole data. The four Venetian breeds, already undergoing conservation, the Tunisian dairy breed, and the very ancient Maghrebian breed, would be favored for conservation. In conclusion, our results highlighted the importance of the analyzed Mediterranean native sheep breeds as valuable inherited genetic reservoirs and supported previous conservation decisions made for the threatened breeds.
Antipsychotics in the Management of Disruptive Behavior Disorders in Children and Adolescents: An Update and Critical Review
Authors: Rajkumar Ravi Philip
Published: November 2022

Disruptive behaviour disorders (DBDs) in childhood include conduct disorder (CD) and oppositional defiant disorder (ODD). Though psychological therapies are considered to be the first-line treatment for DBDs, many patients require adjunctive pharmacotherapy for the control of specific symptoms, such as aggression. Three prior systematic reviews have examined the evidence for the use of antipsychotics in DBDs and have concluded that their efficacy is marginal and limited by adverse effects. This paper has two objectives: (i) to summarize the findings of existing systematic reviews of antipsychotics for the management of DBDs in children and adolescents (2012–2017), and (ii) to provide an update to these reviews by examining recent clinical trials of antipsychotics in this population, published in the period from 2 January 2017 to 10 October 2022. The PubMed, Scopus and ScienceDirect databases were searched for relevant citations using the search terms “disruptive behaviour disorder”, “oppositional defiant disorder”, “conduct disorder” and their variants, along with “antipsychotic”, “atypical antipsychotic” and the generic names of all currently approved atypical antipsychotics. Six relevant trials were identified during this period, including five randomized controlled trials and one naturalistic open-label trial. These trials were critically evaluated in terms of outcome measures, efficacy and safety. Overall, the data from these trials suggests that of all available antipsychotics, risperidone appears to be effective in the short-term management of DBDs. All available antipsychotics are associated with significant metabolic adverse effects in this population. These results are discussed in the light of global trends towards increasing off-label prescription of antipsychotic medication in children and adolescents and of recent literature on the neuropharmacology of aggression in this patient population. The need for rational, short-term use of these drugs is highlighted, as well as the importance of post-marketing surveillance for long-term or severe adverse events.
How the Immune System Responds to Allergy Immunotherapy
Authors: Veneziani Irene , Landolina Nadine , Ricci Biancamaria , Rossi Oliviero , Moretta Lorenzo , Maggi Enrico
Published: November 2022

IgE-mediated diseases represent a highly diversified and multifactorial group of disorders that can deeply impact the patients’ quality of life. Currently, allergy immunotherapy (AIT) still remains the gold standard for the management of such pathologies. In this review, we comprehensively examine and discuss how AIT can affect both the innate and the adaptive immune responses at different cell levels and propose timing-scheduled alterations induced by AIT by hypothesizing five sequential phases: after the desensitization of effector non-lymphoid cells and a transient increase of IgE (phase 1), high doses of allergen given by AIT stimulate the shift from type 2/type 3 towards type 1 response (phase 2), which is progressively potentiated by the increase of IFN-γ that promotes the chronic activation of APCs, progressively leading to the hyperexpression of Notch1L (Delta4) and the secretion of IL-12 and IL-27, which are essential to activate IL-10 gene in Th1 and ILC1 cells. As consequence, an expansion of circulating memory Th1/Tr1 cells and ILC-reg characterizes the third phase addressed to antagonize/balance the excess of type 1 response (phase 3). The progressive increase of IL-10 triggers a number of regulatory circuits sustained by innate and adaptive immune cells and favoring T-cell tolerance (phase 4), which may also be maintained for a long period after AIT interruption (phase 5). Different administration approaches of AIT have shown a similar tailoring of the immune responses and can be monitored by timely, optimized biomarkers. The clinical failure of this treatment can occur, and many genetic/epigenetic polymorphisms/mutations involving several immunological mechanisms, such as the plasticity of immune responses and the induction/maintenance of regulatory circuits, have been described. The knowledge of how AIT can shape the immune system and its responses is a key tool to develop novel AIT strategies including the engineering of allergen or their epitopes. We now have the potential to understand the precise causes of AIT failure and to establish the best biomarkers of AIT efficacy in each phase of the treatment.
The Role of TIM-3 and LAG-3 in the Microenvironment and Immunotherapy of Ovarian Cancer
Authors: Kozłowski Mateusz , Borzyszkowska Dominika , Cymbaluk-Płoska Aneta
Published: November 2022

Ovarian cancer has the highest mortality rate among gynecologic malignancies. The main treatment options are surgical removal of the tumor and chemotherapy. Cancer treatment has been revolutionized by immunotherapy, which has developed explosively over the past two decades. Clinical anticancer strategies used in immunotherapy include therapies based on the inhibition of PD-1, PD-L1 or CTLA-4. Despite encouraging results, a large proportion of cancer patients are resistant to these therapies or eventually develop resistance. It is important to perform research that will focus on immunotherapy based on other immune checkpoint inhibitors. The aim of the review was to analyze studies considering the expression of TIM-3 and LAG-3 in the ovarian cancer microenvironment and considering immunotherapy for ovarian cancer that includes antibodies directed against TIM-3 and LAG-3. As the data showed, the expression of the described immune checkpoints was shown in different ways. Higher TIM-3 expression was associated with a more advanced tumor stage. Both TIM-3 and LAG-3 were co-expressed with PD-1 in a large proportion of studies. The effect of LAG-3 expression on progression-free survival and/or overall survival is inconclusive and certainly requires further study. Co-expression of immune checkpoints prompts combination therapies using anti-LAG-3 or anti-TIM-3. Research on immune checkpoints, especially TIM-3 and LAG-3, should be further developed.
Accurate and Rapid Genetic Tracing the Authenticity of Floral Originated Honey with the Molecular Lateral Flow Strip
Authors: Wu Qian , Chen Qi , Yan Chao , Xu Jianguo , Chen Zhaoran , Yao Li , Lu Jianfeng , Yao Bangben , Chen Wei
Published: November 2022

Honey is a natural product and is heavily consumed for its well-known nutritional functions. Honeys with different floral origins possess distinctive flavors, tastes, functions and economic values. It is vital to establish an effective strategy for identifying the authenticity of honey. The intrinsic genetic materials of pollen were adopted as target analytes for the effective identification of honey with floral origins. With an optimized protocol for the rapid gene extraction from honey, target genetic templates were amplified on-site with a portable device. Conveniently, all on-site amplified functional products were easily judged by the designed lateral flow strip (LFS), which was defined as the molecular LFS in this research. Additionally, the entire on-site genetic authentication of honey was completed in less than 2 h by visual observation. Commercial honey products have been successfully identified with excellent accuracy. This low-cost, high-efficiency and easy-operational strategy will greatly benefit the quality guarantee of foods with specific functions and geographical markers.
Efficient Detection of 2,6-Dinitrophenol with Silver Nanoparticle-Decorated Chitosan/SrSnO3 Nanocomposites by Differential Pulse Voltammetry
Authors: Faisal M. , Alam M. M. , Ahmed Jahir , Asiri Abdullah M. , Alsaiari Mabkhoot , Alruwais Raja Saad , Madkhali O. , Rahman Mohammed M. , Harraz Farid A.
Published: November 2022

Herein, an ultra-sonication technique followed by a photoreduction technique was implemented to prepare silver nanoparticle-decorated Chitosan/SrSnO3 nanocomposites (Ag-decorated Chitosan/SrSnO3 NCs), and they were successively used as electron-sensing substrates coated on a glassy carbon electrode (GCE) for the development of a 2,6-dinitrophenol (2,6-DNP) efficient electrochemical sensor. The synthesized NCs were characterized in terms of morphology, surface composition, and optical properties using FESEM, TEM, HRTEM, BET, XRD, XPS, FTIR, and UV-vis analysis. Ag-decorated Chitosan/SrSnO3 NC/GCE fabricated with the conducting binder (PEDOT:PSS) was found to analyze 2,6-DNP in a wide detection range (LDR) of 1.5~13.5 µM by applying the differential pulse voltammetry (DPV) approach. The 2,6-DNP sensor parameters, such as sensitivity (54.032 µA µM−1 cm−2), limit of detection (LOD; 0.18 ± 0.01 µM), limit of quantification (LOQ; 0.545 µM) reproducibility, and response time, were found excellent and good results. Additionally, various environmental samples were analyzed and obtained reliable analytical results. Thus, it is the simplest way to develop a sensor probe with newly developed nanocomposite materials for analyzing the carcinogenic contaminants from the environmental effluents by electrochemical approach for the safety of environmental and healthcare fields in a broad scale.
Differential Predictors of Response to Early Start Denver Model vs. Early Intensive Behavioral Intervention in Young Children with Autism Spectrum Disorder: A Systematic Review and Meta-Analysis
Authors: Asta Lisa , Persico Antonio M.
Published: November 2022

The effectiveness of early intensive interventions for Autism Spectrum Disorder (ASD) is now well-established, but there continues to be great interindividual variability in treatment response. The purpose of this systematic review is to identify putative predictors of response to two different approaches in behavioral treatment: Early Intensive Behavioral Interventions (EIBI) and the Early Start Denver Model (ESDM). Both are based upon the foundations of Applied Behavioral Analysis (ABA), but the former is more structured and therapist-driven, while the latter is more naturalistic and child-driven. Four databases (EmBase, PubMed, Scopus and WebOfScience) were systematically screened, and an additional search was conducted in the reference lists of relevant articles. Studies were selected if participants were children with ASD aged 12–48 months at intake, receiving either EIBI or ESDM treatment. For each putative predictor, p-values from different studies were combined using Fisher’s method. Thirteen studies reporting on EIBI and eleven on ESDM met the inclusion criteria. A higher IQ at intake represents the strongest predictor of positive response to EIBI, while a set of social cognitive skills, including intention to communicate, receptive and expressive language, and attention to faces, most consistently predict response to ESDM. Although more research will be necessary to reach definitive conclusions, these findings begin to shed some light on patient characteristics that are predictive of preferential response to EIBI and ESDM, and may provide clinically useful information to begin personalizing treatment.
On the Application of Developmental Cognitive Neuroscience in Educational Environments
Authors: Leisman Gerry
Published: November 2022

The paper overviews components of neurologic processing efficiencies to develop innovative methodologies and thinking to school-based applications and changes in educational leadership based on sound findings in the cognitive neurosciences applied to schools and learners. Systems science can allow us to better manage classroom-based learning and instruction on the basis of relatively easily evaluated efficiencies or inefficiencies and optimization instead of simply examining achievement. “Medicalizing” the learning process with concepts such as “learning disability” or employing grading methods such as pass-fail does little to aid in understanding the processes that learners employ to acquire, integrate, remember, and apply information learned. The paper endeavors to overview and provided reference to tools that can be employed that allow a better focus on nervous system-based strategic approaches to classroom learning.
A Novel Deep Learning Method Based on an Overlapping Time Window Strategy for Brain–Computer Interface-Based Stroke Rehabilitation
Authors: Cao Lei , Wu Hailiang , Chen Shugeng , Dong Yilin , Zhu Changming , Jia Jie , Fan Chunjiang
Published: November 2022

Globally, stroke is a leading cause of death and disability. The classification of motor intentions using brain activity is an important task in the rehabilitation of stroke patients using brain–computer interfaces (BCIs). This paper presents a new method for model training in EEG-based BCI rehabilitation by using overlapping time windows. For this aim, three different models, a convolutional neural network (CNN), graph isomorphism network (GIN), and long short-term memory (LSTM), are used for performing the classification task of motor attempt (MA). We conducted several experiments with different time window lengths, and the results showed that the deep learning approach based on overlapping time windows achieved improvements in classification accuracy, with the LSTM combined vote-counting strategy (VS) having achieved the highest average classification accuracy of 90.3% when the window size was 70. The results verified that the overlapping time window strategy is useful for increasing the efficiency of BCI rehabilitation.
Applying Deep Learning on a Few EEG Electrodes during Resting State Reveals Depressive States: A Data Driven Study
Authors: Jan Damián , de Vega Manuel , López-Pigüi Joana , Padrón Iván
Published: November 2022

The growing number of depressive people and the overload in primary care services make it necessary to identify depressive states with easily accessible biomarkers such as mobile electroencephalography (EEG). Some studies have addressed this issue by collecting and analyzing EEG resting state in a search of appropriate features and classification methods. Traditionally, EEG resting state classification methods for depression were mainly based on linear or a combination of linear and non-linear features. We hypothesize that participants with ongoing depressive states differ from controls in complex patterns of brain dynamics that can be captured in EEG resting state data, using only nonlinear measures on a few electrodes, making it possible to develop cheap and wearable devices that could be even monitored through smartphones. To validate such a perspective, a resting-state EEG study was conducted with 50 participants, half with depressive state (DEP) and half controls (CTL). A data-driven approach was applied to select the most appropriate time window and electrodes for the EEG analyses, as suggested by Giacometti, as well as the most efficient nonlinear features and classifiers, to distinguish between CTL and DEP participants. Nonlinear features showing temporo-spatial and spectral complexity were selected. The results confirmed that computing nonlinear features from a few selected electrodes in a 15 s time window are sufficient to classify DEP and CTL participants accurately. Finally, after training and testing internally the classifier, the trained machine was applied to EEG resting state data (CTL and DEP) from a publicly available database, validating the capacity of generalization of the classifier with data from different equipment, population, and environment obtaining an accuracy near 100%.
Influencing Mechanism of Safety Sign Features on Visual Attention of Construction Workers: A Study Based on Eye-Tracking Technology
Authors: Fang Yaqi , Ni Guodong , Gao Fengling , Zhang Qi , Niu Miaomiao , Ding Zhihua
Published: November 2022

Visual attention of construction workers is closely related to their safety performance. Identifying and understanding safety signs on workplace effectively is beneficial to improve visual attention. This study focuses on exploring the influencing mechanism of construction safety sign features on visual attention of construction workers using the eye-tracking technology, in order to improve visual attention and workplace safety performance through optimizing the construction safety signs. A theoretical model of influencing mechanism of safety sign features on visual attention was constructed based on visual information processing theory. To verify the theoretical model, an experiment was conducted as follows: 28 pictures of safety signs including visual and cognitive features were shown on the computer screen, then eye movement data from 41 subjects was obtained using EyeLink1000 Plus. Statistical test methods were employed to analyze the relationship between safety sign features and eye-tracking metrics. The statistical results of theoretical model indicate that, among visual features, red and rectangular safety signs can reduce cognitive load of first fixation, green signs can reduce cognitive difficulties, however visual attention is not closely related to auxiliary words. Among the cognitive features, unfamiliar signs require more cognitive effort, while no significant difference exists in visual attention of different levels of concreteness and sematic closeness. This study provides theoretical and practical basis for improving construction workers’ visual attention through optimizing visual and cognitive features of construction safety signs.
Study on Shear-Lag Effect of Steel–UHPC Ribbed Slab Composite Structures Using Bar Simulation Method
Authors: Tan Chengjun , Zhang Yufei , Zhao Hua , Zhang Bin , Du Tie
Published: November 2022

Recently, Ultra-High Performance Concrete (UHPC) has attracted increasing attention in civil engineering. Numerous steel–UHPC composite structures have been constructed around the world. The proper consideration of the shear-lag effect has a significant influence on the safety of structures. In view of the shear-lag effect of steel–UHPC ribbed slab composite structure (SU-RSCS) in the elastic stage, a theoretical calculation model based on the bar simulation method is first developed. Then, the feasibility and accuracy of that are verified using both experimental data and numerical simulation. Moreover, many factors (including width-to-span ratio, the ratio of rib height to UHPC layer thickness, the ratio of rib width to rib spacing, and the number of transverse ribs) are parametrically investigated to further investigate the structural shear-lag effect using the proposed method. In addition, the orthogonal analysis is applied to determine the sensitivity of each parameter to the shear-lag effect. The parametric interactions are also considered. At last, the comparison between calculation results of the proposed method and specifications are discussed. The results show that the proposed approach can accurately predict the shear-lag effect on SU-RSCSs in the elastic stage. It is also found that the width-to-span ratio has a great influence on the structural shear-lag effect, while the number of transverse ribs has no significant influence on that.
Review on the Developments of Structure, Construction Automation, and Monitoring of Intelligent Construction
Authors: Liu Kewei , Meng Qingfei , Kong Qingzhao , Zhang Xihong
Published: November 2022

The building and construction industry is a traditional industry that features high-capacity investment, long return period, high environment impact, and low technology demand in the past decades. With the fast development of technology and the demand for environmental sustainability, it is inevitable for the building and construction industry to embrace the revolution of technology. Intelligent construction is developed in light of advanced technologies including advanced computing technology, 3D design and manufacturing, automation and control, sensing, unmanned aircraft, and autonomous intelligence. It is also closely integrated with using perceived, analytical, decision-making coordination for building construction with perceived intelligent execution technology in the processes. Currently, there is no consensus definition on “intelligent construction” despite its rapid development. This paper reviews existing and current development in intelligent construction focusing on the following three aspects: (a) new structural forms, which are innovative and with potential or are being applied to automated and mass manufacturing/construction; (b) automated and intelligent construction system; and (c) advanced structure sensing and monitoring technology. These three components do not compromise the entire aspects for intelligent construction, but they have no doubt are the core elements for intelligent construction towards future building systems.
Numerical Simulation of Galloping Characteristics of Multi-Span Iced Eight-Bundle Conductors Tower Line System
Authors: Tian Bowen , Cai Mengqi , Zhou Linshu , Huang Hanjie , Ding Shunli , Liang Junhao , Hu Maoming
Published: November 2022

The galloping condition of an iced eight-bundle conductor tower line system, under different parameters, is studied by using a finite element model of a multi-span iced eight-bundle conductor tower line system. The galloping frequency, amplitude, traces of multi-span iced eight-bundle conductors under different wind velocities, span lengths, and initial angles of wind attack are discussed. The different tower line connection methods are compared, based on existing research on the relationship between the aerodynamic characteristics of the conductor and galloping conditions. The results show that the galloping situation of a multi-span iced eight-bundle conductor tower line system varies greatly depending on the conditions, which has a significant impact on the tower line.
Research on Design Framework of Middle School Teaching Building Based on Performance Optimization and Prediction in the Scheme Design Stage
Authors: Wang Meng , Cao Shuqi , Chen Daxing , Ji Guohua , Ma Qiang , Ren Yucheng
Published: November 2022

The good indoor light environment and comfort of the teaching space are very important for students’ physical and mental health. Meanwhile, China advocates energy conservation and emission reduction policies. However, in order to obtain lower building energy consumption, higher thermal comfort, and daylighting, architects use performance simulation software to repeatedly simulate and refine, which is time-consuming and difficult to obtain the best results from three performances. Given this problem, we constructed the design framework in the early stage of the architectural design of the teaching building. In the first stage of the framework, architects optimized the performance objectives of lighting, thermal comfort, and energy consumption, and performed a cluster analysis on the optimized non-dominated solution to provide a reference for the architect. In the second stage of the framework, architects used the data generated in the optimization process to train the BP neural network and use the trained BP neural network to predict the performance of the building. In this paper, we selected Nanjing Donglu Middle School as a case study. The optimization of the building performance was assessed by a genetic algorithm, generating 3000 sets of sample data during the optimization iteration. Then, we analyzed the non-dominated solution of the sample data through the method of cluster analysis and trained the BP neural network with the sample data as a data set. The prediction model with R-values of 0.998 in the training set and test set was obtained by repeatedly debugging the number of neurons in the BP neural network. Finally, five groups of design parameters were randomly selected and brought into the trained BP neural network, and the predictive value was close to the simulated value. The construction of the framework provides design ideas for architects in the early teaching of building design and helps designers to make better decisions.
Modern Design Methods on Optimised Novel Aluminium Profiles
Authors: Marinopoulou Eva , Tsavdaridis Konstantinos Daniel , Efthymiou Evangelos
Published: November 2022

Within the framework of optimisation of structural elements, in the last years, significant activity has been demonstrated towards developing new sectional designs beyond standardised forms aiming to combine aesthetic innovation, material efficiency, and weight over stiffness, together with structural reliability and manufacture cost savings. Moreover, in terms of sustainability performance, as material-weight reduction leads to less carbon emissions from production to installation processes, the pursuit of suitable materials that can correspond to this challenge becomes imperative. In this context, aluminium is lightweight and corrosion resistant, but due to its low elastic modulus, an increased cross-sectional stiffness is required. In this paper, 16 previously optimised aluminium cross-section profiles are presented and analysed using the finite element analysis software ABAQUS. The obtained ultimate compression resistances were compared with the predictions made in accordance with Eurocode 9, the direct strength method (DSM), and the continuous strength method (CSM). The percentage of difference of these design methods with respect to FE results is depicted. The outcomes point out the vagueness in accuracy of the prediction methods, particularly in reference to stocky or slender cross-sections.