bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparing Push and Pull Factors Affecting Migration
Authors: Urbański Mariusz
Published: January 2022

The purpose of this research was to conduct a comparison of the push and pull factors affecting migration between Poland and Romania. The study aimed to find out which among the push and pull factors have a greater effect overall and individually on the migration activities. The study was conducted using primary data collected from migrants in both countries using a structured questionnaire. There were data from 298 and 288 surveys for Poland and Romania, respectively. The push and pull migration framework was applied to guide the study. The model suitability was confirmed satisfactory on validity, reliability and factor analysis. The hypothesis was analyzed and evaluated using multiple regression analysis. The findings of the study indicated that pull factors have a greater influence on migration in these two countries as compared to the push factors. Five out of six (economic, political and social in Poland and economic and political in Romania) pull factors were found significant as compared to two (social in Poland and in Romania) out of six push factors. Pull economic factors were significant determinants of migration in all the countries. Pull political factors were found to have the highest effect in both countries, because they influenced migrants in Romania. Economic factors are the major factors that influence migration, including the hope of finding better jobs and better life in the foreign countries, and these factors should be addressed in the effort to reduce migration. In addition, political issues such as unfair legal system, violent conflicts, underdevelopment, poverty, political instability and corruption should be addressed to control the issue of migration.
Impact of Naturally Occurring Asbestos on Asbestos Ban: Regulations and Experience of the Republic of Korea
Authors: Kwon Jiwoon
Published: January 2022

This review examined the main issues debated in Korea regarding the production and use of materials containing naturally occurring asbestos (NOA) as impurities, and investigated the impacts of these debates on the asbestos ban, as well as the future implications. In Korea, incidents associated with the production and use of NOA-contaminated talc powders, construction rocks, serpentinites, and dolomite rocks raised public concern and led to accelerating the ban on asbestos. The main controversies concern policies on appropriate asbestos content limits, whether materials containing a trace amount of NOA should be banned, and the control of materials with high human exposure risk. To address recurring controversies, the implementation of preventive measures to manage elongated mineral particles and the use of transmission electron microscopy for more sensitive analysis need to be discussed, along with reaching social agreement on the controversial policies. To minimize the potential exposure to asbestos that may occur during the production and use of industrial minerals in the future, it is necessary to apply occupational exposure control measures and monitor the health effects of the relevant population groups. These national policies on NOA should be prepared based on close collaboration and discussion with policymakers, industry stakeholders, and related academic experts.
A Poverty Measurement Method Incorporating Spatial Correlation: A Case Study in Yangtze River Economic Belt, China
Authors: Zhou Qianqian , Chen Nan , Lin Siwei
Published: January 2022

The UN 2030 Agenda sets poverty eradication as the primary goal of sustainable development. An accurate measurement of poverty is a critical input to the quality and efficiency of poverty alleviation in rural areas. However, poverty, as a geographical phenomenon, inevitably has a spatial correlation. Neglecting the spatial correlation between areas in poverty measurements will hamper efforts to improve the accuracy of poverty identification and to design policies in truly poor areas. To capture this spatial correlation, this paper proposes a new poverty measurement model based on a neural network, namely, the spatial vector deep neural network (SVDNN), which combines the spatial vector neural network model (SVNN) and the deep neural network (DNN). The SVNN was applied to measure spatial correlation, while the DNN used the SVNN output vector and explanatory variables dataset to measure the multidimensional poverty index (MPI). To determine the optimal spatial correlation structure of SVDNN, this paper compares the model performance of the spatial distance matrix, spatial adjacent matrix and spatial weighted adjacent matrix, selecting the optimal performing spatial distance matrix as the input data set of SVNN. Then, the SVDNN model was used for the MPI measurement of the Yangtze River Economic Belt, after which the results were compared with three baseline models of DNN, the back propagation neural network (BPNN), and artificial neural network (ANN). Experiments demonstrate that the SVDNN model can obtain spatial correlation from the spatial distance dataset between counties and its poverty identification accuracy is better than other baseline models. The spatio-temporal characteristics of MPI measured by SVDNN were also highly consistent with the distribution of urban aggregations and national-level poverty counties in the Yangtze River Economic Belt. The SVDNN model proposed in this paper could effectively improve the accuracy of poverty identification, thus reducing the misallocation of resources in tracking and targeting poverty in developing countries.
FEM-Validated Optimal Design of Laminate Process Parameters Based on Improved Genetic Algorithm
Authors: Mou Xing , Shen Zhiqiang , Liu Honghao , Xv Hui , Xia Xianzhao , Chen Shijun
Published: January 2022

In tape placement process, the laying angle and laying sequence of laminates have proven their significant effects on the mechanical properties of carbon fibre reinforced composite material, specifically, laminates. In order to optimise these process parameters, an optimisation algorithm is developed based on the principles of genetic algorithms for improving the precision of traditional genetic algorithms and resolving the premature phenomenon in the optimisation process. Taking multi-layer symmetrically laid carbon fibre laminates as the research object, this algorithm adopts binary coding to conduct the optimisation of process parameters and mechanical analysis with the laying angle as the design variable and the strength ratio R as the response variable. A case study was conducted and its results were validated by the finite element analyses. The results show that the stresses before and after optimisation are 116.0 MPa and 100.9 MPa, respectively, with a decrease of strength ratio by 13.02%. The results comparison indicates that, in the iterative process, the search range is reduced by determining the code and location of important genes, thereby reducing the computational workload by 21.03% in terms of time consumed. Through multiple calculations, it validates that “gene mutation” is an indispensable part of the genetic algorithm in the iterative process.
Special Issue “Feature Papers in Journal of Developmental Biology”
Authors: Dettman Robert W.
Published: January 2022

Here, we have assembled five interesting manuscripts that deserve special attention [...]
The Risk Measurement under the Variance-Gamma Process with Drift Switching
Authors: Ivanov Roman V.
Published: January 2022

The paper discusses an extension of the variance-gamma process with stochastic linear drift coefficient. It is assumed that the linear drift coefficient may switch to a different value at the exponentially distributed time. The size of the drift jump is supposed to have a multinomial distribution. We have obtained the distribution function, the probability density function and the lower partial expectation for the considered process in closed forms. The results are applied to the calculation of the value at risk and the expected shortfall of the investment portfolio in the related multivariate stochastic model.
Territorial and Gender Differences in the Home Care of Family Members with Dementia
Authors: Anaut-Bravo Sagrario , Lopes-Dos-Santos María Cristina
Published: January 2022

The increasing prevalence of dementia is threatening the capacity of health and social service systems to provide long-term care support at the territorial level. In both rural and urban areas, specific family members (gendered care) are responsible for the daily care of their relatives. The aim of this work is to explore gender and territorial implications in the provision of in-home care by family members. To this end, family caregivers in Navarre, Spain, were administered the Psychosocial Adjustment to Illness Scale (PAIS-SR) and a semi-structured interview. The results show the good psychosocial adjustment of caregivers of relatives with dementia but the negative impacts of caregiving in the domestic, relational, and psychological domains. Moreover, the feminization of psychological distress was found to predominate in rural areas since mainly women are responsible for instrumental and care tasks, while men seek other complementary forms of support. Place of residence (rural vs. urban) was found to exert a strong effect on the respondents’ conception, life experience, and provision of care. Consequently, territorial and gender differences in coping with and adjusting to care require the design of contextualized actions adapted to caregivers’ needs.
Cultural Experience Influences Multisensory Emotion Perception in Bilinguals
Authors: Chen Peiyao , Chung-Fat-Yim Ashley , Marian Viorica
Published: January 2022

Emotion perception frequently involves the integration of visual and auditory information. During multisensory emotion perception, the attention devoted to each modality can be measured by calculating the difference between trials in which the facial expression and speech input exhibit the same emotion (congruent) and trials in which the facial expression and speech input exhibit different emotions (incongruent) to determine the modality that has the strongest influence. Previous cross-cultural studies have found that individuals from Western cultures are more distracted by information in the visual modality (i.e., visual interference), whereas individuals from Eastern cultures are more distracted by information in the auditory modality (i.e., auditory interference). These results suggest that culture shapes modality interference in multisensory emotion perception. It is unclear, however, how emotion perception is influenced by cultural immersion and exposure due to migration to a new country with distinct social norms. In the present study, we investigated how the amount of daily exposure to a new culture and the length of immersion impact multisensory emotion perception in Chinese-English bilinguals who moved from China to the United States. In an emotion recognition task, participants viewed facial expressions and heard emotional but meaningless speech either from their previous Eastern culture (i.e., Asian face-Mandarin speech) or from their new Western culture (i.e., Caucasian face-English speech) and were asked to identify the emotion from either the face or voice, while ignoring the other modality. Analyses of daily cultural exposure revealed that bilinguals with low daily exposure to the U.S. culture experienced greater interference from the auditory modality, whereas bilinguals with high daily exposure to the U.S. culture experienced greater interference from the visual modality. These results demonstrate that everyday exposure to new cultural norms increases the likelihood of showing a modality interference pattern that is more common in the new culture. Analyses of immersion duration revealed that bilinguals who spent more time in the United States were equally distracted by faces and voices, whereas bilinguals who spent less time in the United States experienced greater visual interference when evaluating emotional information from the West, possibly due to over-compensation when evaluating emotional information from the less familiar culture. These findings suggest that the amount of daily exposure to a new culture and length of cultural immersion influence multisensory emotion perception in bilingual immigrants. While increased daily exposure to the new culture aids with the adaptation to new cultural norms, increased length of cultural immersion leads to similar patterns in modality interference between the old and new cultures. We conclude that cultural experience shapes the way we perceive and evaluate the emotions of others.
Rheumatological Adverse Events Following Immunotherapy for Cancer
Authors: Cretu Ioana , Cretu Bogdan , Cirstoiu Catalin , Cursaru Adrian , Milicescu Mihaela , Bojinca Mihai , Ionescu Ruxandra
Published: January 2022

Background and Objectives: The occurrence of rheumatological side effects in a patient after receiving immunotherapy for cancer is becoming increasingly common. Oncologists often fail to diagnose and refer affected patients to rheumatologists. This paper presents the various rheumatological adverse events that occur after immunotherapy in patients as well as their treatment and evolution. Materials and Methods: A total of 36 patients were monitored between November 2018 and March 2020. The oncologist monitoring the immunotherapy-treated patients identified the occurrence of musculoskeletal side effects. The grading of toxicities was performed by both the oncologist and the rheumatologist using common terminology criteria for adverse events (CTCAE). Rheumatological treatment was administered, and for some patients, immunotherapy was discontinued. Results: The clinical presentations of the patients varied. Mild side effects (grade 1–2) were reported in a higher proportion than severe side effects (grade 3–5). Therefore, thirty-one patients had mild-to-moderate side effects, and five patients had severe side effects. Adverse reactions occurred, on average, 10 weeks after the initiation of immunotherapy; this indicated that the severity of the toxicity was dose dependent. Patients were treated with NSAIDs or prednisone, depending on the severity of the side effects, and for patients with severe manifestations, immunotherapy was discontinued. The remission of rheumatic manifestations varied depending on the grade of the manifestations. Conclusions: The clinical, biological, and ultrasound presentations of the patients with adverse events followed by cancer treatments differed from classic rheumatological manifestations. Thorough examinations of these patients by both oncologists and rheumatologists are needed in order to correctly diagnose and treat rheumatological adverse events. Multiple studies that include a larger number of participants are needed in order to better understand the pathogenesis and clinical evolution of these patients under different treatment conditions.
NIRS and Aquaphotomics Trace Robusta-to-Arabica Ratio in Liquid Coffee Blends
Authors: Aouadi Balkis , Vitalis Flora , Bodor Zsanett , Zinia Zaukuu John-Lewis , Kertesz Istvan , Kovacs Zoltan
Published: January 2022

Coffee is both a vastly consumed beverage and a chemically complex matrix. For a long time, an arduous chemical analysis was necessary to resolve coffee authentication issues. Despite their demonstrated efficacy, such techniques tend to rely on reference methods or resort to elaborate extraction steps. Near infrared spectroscopy (NIRS) and the aquaphotomics approach, on the other hand, reportedly offer a rapid, reliable, and holistic compositional overview of varying analytes but with little focus on low concentration mixtures of Robusta-to-Arabica coffee. Our study aimed for a comparative assessment of ground coffee adulteration using NIRS and liquid coffee adulteration using the aquaphotomics approach. The aim was to demonstrate the potential of monitoring ground and liquid coffee quality as they are commercially the most available coffee forms. Chemometrics spectra analysis proved capable of distinguishing between the studied samples and efficiently estimating the added Robusta concentrations. An accuracy of 100% was obtained for the varietal discrimination of pure Arabica and Robusta, both in ground and liquid form. Robusta-to-Arabica ratio was predicted with R2CV values of 0.99 and 0.9 in ground and liquid form respectively. Aquagrams results accentuated the peculiarities of the two coffee varieties and their respective blends by designating different water conformations depending on the coffee variety and assigning a particular water absorption spectral pattern (WASP) depending on the blending ratio. Marked spectral features attributed to high hydrogen bonded water characterized Arabica-rich coffee, while those with the higher Robusta content showed an abundance of free water structures. Collectively, the obtained results ascertain the adequacy of NIRS and aquaphotomics as promising alternative tools for the authentication of liquid coffee that can correlate the water-related fingerprint to the Robusta-to-Arabica ratio.
Preparation of Hollow Core–Shell Fe3O4/Nitrogen-Doped Carbon Nanocomposites for Lithium-Ion Batteries
Authors: Wang Jie , Hu Qin , Hu Wenhui , Zhu Wei , Wei Ying , Pan Kunming , Zheng Mingbo , Pang Huan
Published: January 2022

Iron oxides are potential electrode materials for lithium-ion batteries because of their high theoretical capacities, low cost, rich resources, and their non-polluting properties. However, iron oxides demonstrate large volume expansion during the lithium intercalation process, resulting in the electrode material being crushed, which always results in poor cycle performance. In this paper, to solve the above problem, iron oxide/carbon nanocomposites with a hollow core–shell structure were designed. Firstly, an Fe2O3@polydopamine nanocomposite was prepared using an Fe2O3 nanocube and dopamine hydrochloride as precursors. Secondly, an Fe3O4@N-doped C composite was obtained by means of further carbonization treatment. Finally, Fe3O4@void@N-Doped C-x composites with core–shell structures with different void sizes were obtained by means of Fe3O4 etching. The effect of the etching time on the void size was studied. The electrochemical properties of the composites when used as lithium-ion battery materials were studied in more detail. The results showed that the sample that was obtained via etching for 5 h using 2 mol L−1 HCl solution at 30 °C demonstrated better electrochemical performance. The discharge capacity of the Fe3O4@void@N-Doped C-5 was able to reach up to 1222 mA g h−1 under 200 mA g−1 after 100 cycles.
Liposome-Mediated Delivery of MERS Antigen Induces Potent Humoral and Cell-Mediated Immune Response in Mice
Authors: Khan Masood Alam , Malik Ajamaluddin , Alzohairy Mohammad A. , Alruwetei Abdulmohsen M. , Alhatlani Bader Y. , Rugaie Osamah Al , Khan Arif
Published: January 2022

The advancements in the field of nanotechnology have provided a great platform for the development of effective antiviral vaccines. Liposome-mediated delivery of antigens has been shown to induce the antigen-specific stimulation of the humoral and cell-mediated immune responses. Here, we prepared dried, reconstituted vesicles (DRVs) from DPPC liposomes and used them as the vaccine carrier system for the Middle East respiratory syndrome coronavirus papain-like protease (DRVs-MERS-CoV PLpro). MERS-CoV PLpro emulsified in the Incomplete Freund’s Adjuvant (IFA-MERS-CoV PLpro) was used as a control. Immunization of mice with DRVs-MERS-CoV PLpro did not induce any notable toxicity, as revealed by the levels of the serum alanine transaminase (ALT), aspartate transaminase (AST), blood urea nitrogen (BUN) and lactate dehydrogenase (LDH) in the blood of immunized mice. Immunization with DRVs-MERS-CoV PLpro induced greater antigen-specific antibody titer and switching of IgG1 isotyping to IgG2a as compared to immunization with IFA-MERS-CoV PLpro. Moreover, splenocytes from mice immunized with DRVs-MERS-CoV PLpro exhibited greater proliferation in response to antigen stimulation. Moreover, splenocytes from DRVs-MERS-CoV PLpro-immunized mice secreted significantly higher IFN-γ as compared to splenocytes from IFA-MERS-CoV PLpro mice. In summary, DRVs-MERS-CoV PLpro may prove to be an effective prophylactic formulation to prevent MERS-CoV infection.
Chemical and Physical Characterisation of Macroaggregated Human Serum Albumin: Strength and Specificity of Bonds with 99mTc and 68Ga
Authors: Canziani Letizia , Marenco Manuela , Cavenaghi Giorgio , Manfrinato Giulia , Taglietti Angelo , Girella Alessandro , Aprile Carlo , Pepe Giovanna , Lodola Lorenzo
Published: January 2022

Background: Macroaggregated human serum albumin (MAA) properties are widely used in nuclear medicine, labelled with 99mTc. The aim of this study is to improve the knowledge about the morphology, size, dimension and physical–chemical characteristics of MAA and their bond with 99mTc and 68Ga. Methods: Commercial kits of MAA (Pulmocis®) were used. Characterisation through experiments based on SEM, DLS and Stokes’ Law were carried out. In vitro experiments for Langmuir isotherms and pH studies on radiolabelling were performed and the stability of the radiometal complex was verified through competition reactions. Results: The study settles the MAA dimension within the range 43–51 μm. The Langmuir isotherm reveals for [99mTc]MAA: Bmax (46.32), h (2.36); for [68Ga]MAA: Bmax (44.54), h (0.893). Dual labelling reveals that MAA does not discriminate different radioisotopes. Experiments on pH placed the optimal pH for labelling with 99mTc at 6. Conclusion: Radiolabelling of MAA is possible with high efficiency. The nondiscriminatory MAA bonds make this drug suitable for radiolabelling with different radioisotopes or for dual labelling. This finding illustrates the need to continue investigating MAA chemical and physical characteristics to allow for secure labelling with different isotopes.
Anticancer Effects and Molecular Action of 7-α-Hydroxyfrullanolide in G2/M-Phase Arrest and Apoptosis in Triple Negative Breast Cancer Cells
Authors: Chimplee Siriphorn , Roytrakul Sittiruk , Sukrong Suchada , Srisawat Theera , Graidist Potchanapond , Kanokwiroon Kanyanatt
Published: January 2022

Triple negative breast cancer (TNBC) is a breast cancer subtype characterized by the absence of estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 expression. TNBC cells respond poorly to targeted chemotherapies currently in use and the mortality rate of TNBC remains high. Therefore, it is necessary to identify new chemotherapeutic agents for TNBC. In this study, the anti-cancer effects of 7-α-hydroxyfrullanolide (7HF), derived from Grangea maderaspatana, on MCF-7, MDA-MB-231 and MDA-MB-468 breast cancer cells were assessed using MTT assay. The mode of action of 7HF in TNBC cells treated with 6, 12 and 24 µM of 7HF was determined by flow cytometry and propidium iodide (PI) staining for cell cycle analysis and annexin V/fluorescein isothiocyanate + PI staining for detecting apoptosis. The molecular mechanism of action of 7HF in TNBC cells was investigated by evaluating protein expression using proteomic techniques and western blotting. Subsequently, 7HF exhibited the strongest anti-TNBC activity toward MDA-MB-468 cells and a concomitantly weak toxicity toward normal breast cells. The molecular mechanism of action of low-dose 7HF in TNBC cells primarily involved G2/M-phase arrest through upregulation of the expression of Bub3, cyclin B1, phosphorylated Cdk1 (Tyr 15) and p53-independent p21. Contrastingly, the upregulation of PP2A-A subunit expression may have modulated the suppression of various cell survival proteins such as p-Akt (Ser 473), FoxO3a and β-catenin. The concurrent apoptotic effect of 7HF on the treated cells was mediated via both intrinsic and extrinsic modes through the upregulation of Bax and active cleaved caspase-7–9 expression and downregulation of Bcl-2 and full-length caspase-7–9 expression. Notably, the proteomic approach revealed the upregulation of the expression of pivotal protein clusters associated with G1/S-phase arrest, G2/M-phase transition and apoptosis. Thus, 7HF exhibits promising anti-TNBC activity and at a low dose, it modulates signal transduction associated with G2/M-phase arrest and apoptosis.
Comparative Study of the Petal Structure and Fragrance Components of the Nymphaea hybrid, a Precious Water Lily
Authors: Zhou Qi , Shi Man , Zhang Huihui , Zhu Zunling
Published: January 2022

Nymphaea hybrid, a precious water lily, is a widely-cultivated aquatic flower with high ornamental, economic, medicinal, and ecological value; it blooms recurrently and emits a strong fragrance. In the present study, in order to understand the volatile components of N. hybrid and its relationship with petals structure characteristics, the morphologies and anatomical structures of the flower petals of N. hybrid were investigated, and volatile compounds emitted from the petals were identified. Scanning and transmission electron microscopy were used to describe petal structures, and the volatile constituents were collected using headspace solid-phase microextraction (HS-SPME) fibers and analyzed using gas chromatography coupled with mass spectrometry (GC-MS). The results indicated that the density and degree of protrusion and the number of plastids and osmiophilic matrix granules in the petals play key roles in emitting the fragrance. There were distinct differences in the components and relative contents of volatile compounds among the different strains of N. hybrid. In total, 29, 34, 39, and 43 volatile compounds were detected in the cut flower petals of the blue-purple type (Nh-1), pink type (Nh-2), yellow type (Nh-3) and white type (Nh-4) of N. hybrid at the flowering stage, with total relative contents of 96.78%, 97.64%, 98.56%, and 96.15%, respectively. Analyses of these volatile components indicated that alkenes, alcohols, and alkanes were the three major types of volatile components in the flower petals of N. hybrid. The predominant volatile compounds were benzyl alcohol, pentadecane, trans-α-bergamotene, (E)-β-farnesene, and (6E,9E)-6,9-heptadecadiene, and some of these volatile compounds were terpenes, which varied among the different strains. Moreover, on the basis of hierarchical cluster analysis (HCA) and principal component analysis (PCA), the N. hybrid samples were divided into four groups: alcohols were the most important volatile compounds for Nh-4 samples; esters and aldehydes were the predominant volatiles in Nh-3 samples; and ketones and alkenes were important for Nh-2 samples. These compounds contribute to the unique flavors and aromas of the four strains of N. hybrid.
Umbu Fruit Peel as Source of Antioxidant, Antimicrobial and α-Amylase Inhibitor Compounds
Authors: Ribeiro Leilson de Oliveira , de Freitas Beatriz Pereira , Lorentino Carolline Margot Albanez , Frota Heloisa Freire , dos Santos André Luis Souza , Moreira Davyson de Lima , do Amaral Bruno Sérgio , Jung Eliane Przytyk , Kunigami Claudete Norie
Published: January 2022

Herein, the extraction of bioactive compounds from umbu fruit peel was optimized using thermal-assisted solid–liquid extraction. In parallel, antioxidant, antimicrobial, and inhibitory effects against α-amylase of optimized extract were also evaluated. The combination of operational conditions including the temperature (32–74 °C), ethanol concentration (13–97%), and solid/liquid ratio (1:10–1:60; w/v) was employed using a rotational central composite design for optimization. The extracts were evaluated for total phenolic compounds (TPC), total flavonoid compounds (TFC) and antioxidant capacity by ABTS•+, DPPH• and FRAP assays. The bioactive profile of the optimized extract was obtained by ultra-performance liquid chromatography coupled to quadrupole/time-of-flight mass spectrometry in electrospray ionization in both negative and positive modes. The statistically evaluated results showed that the optimal operational conditions for the recovery of bioactive compounds from umbu fruit peel included 74 °C, 37% ethanol, and a solid–liquid ratio of 1:38. Under these conditions, the obtained values were 1985 mg GAE/100 g, 1364 mg RE/100 g, 122 µmol TE/g, 174 µmol/TE g and 468 µmol Fe2+/g for TPC, TFC, ABTS•+, DPPH•, and FRAP assays, respectively. In addition, the optimized extract was effective against Gram-positive and Gram-negative bacteria (MBC ranged from 0.060 to 0.24 mg GAE/mL), as well as it was effective to inhibit α-amylase (IC50 value of 0.076 mg GAE/mL). The optimized extract showed to be mainly constituted by phenolic acids and flavonoids.
Application of Mathematical Models to Determine the Feasibility of Amorphous Drug Layering in Pan Coaters
Authors: Choi Michael , Porter Stuart C. , Meisen Axel
Published: January 2022

Oral solid dosage forms that contain APIs in the amorphous state have become commonplace because of many drug substances exhibiting poor water solubility, which negatively impacts their absorption in the human GI tract. While micronization, solvent spray-drying, and hot-melt extrusion can address solubility issues, spray coating of the APIs onto beads and tablets offers another option for producing amorphous drug products. High-level comparisons between bead and tablet coating technologies have the potential for simpler equipment and operation that can reduce the cost of development and manufacturing. However, spray coating directly onto tablets is not without challenges, especially with respect to meeting uniformity acceptance value (AV) criteria, comprising accuracy (mean) and precision (variance) objectives. The feasibility of meeting AV criteria is examined, based on mathematical models for accuracy and precision. The results indicate that the main difficulty in manufacturing satisfactory drug-layered tablets by spray coating is caused by the practical limitations of achieving the necessary coating precision. Despite this limitation, it is shown that AV criteria can be consistently met by appropriate materials monitoring and control as well as processing equipment setup, operation, and maintenance.
Detecting Extratropical Cyclones of the Northern Hemisphere with Single Shot Detector
Authors: Shi Minjing , He Pengfei , Shi Yuli
Published: January 2022

In this paper, we propose a deep learning-based model to detect extratropical cyclones (ETCs) of the northern hemisphere, while developing a novel workflow of processing images and generating labels for ETCs. We first labeled the cyclone center by adapting an approach from Bonfanti et al. in 2017 and set up criteria of labeling ETCs of three categories: developing, mature, and declining stages. We then gave a framework of labeling and preprocessing the images in our dataset. Once the images and labels were ready to serve as inputs, an object detection model was built with Single Shot Detector (SSD) and adjusted to fit the format of the dataset. We trained and evaluated our model with our labeled dataset on two settings (binary and multiclass classifications), while keeping a record of the results. We found that the model achieves relatively high performance with detecting ETCs of mature stage (mean Average Precision is 86.64%), and an acceptable result for detecting ETCs of all three categories (mean Average Precision 79.34%). The single-shot detector model can succeed in detecting ETCs of different stages, and it has demonstrated great potential in the future applications of ETC detection in other relevant settings.
Research on Multiple Spectral Ranges with Deep Learning for SpO2 Measurement
Authors: Shen Chih-Hsiung , Chen Wei-Lun , Wu Jung-Jie
Published: January 2022

Oxyhemoglobin saturation by pulse oximetry (SpO2) has always played an important role in the diagnosis of symptoms. Considering that the traditional SpO2 measurement has a certain error due to the number of wavelengths and the algorithm and the wider application of machine learning and spectrum combination, we propose to use 12-wavelength spectral absorption measurement to improve the accuracy of SpO2 measurement. To investigate the multiple spectral regions for deep learning for SpO2 measurement, three datasets for training and verification were built, which were constructed over the spectra of first region, second region, and full region and their sub-regions, respectively. For each region under the procedures of optimization of our model, a thorough of investigation of hyperparameters is proceeded. Additionally, data augmentation is preformed to expand dataset with added noise randomly, increasing the diversity of data and improving the generalization of the neural network. After that, the established dataset is input to a one dimensional convolution neural network (1D-CNN) to obtain a measurement model of SpO2. In order to enhance the model accuracy, GridSearchCV and Bayesian optimization are applied to optimize the hyperparameters. The optimal accuracies of proposed model optimized by GridSearchCV and Bayesian Optimization is 89.3% and 99.4%, respectively, and trained with the dataset at the spectral region of six wavelengths including 650 nm, 680 nm, 730 nm, 760 nm, 810 nm, 860 nm. The total relative error of the best model is only 0.46%, optimized by Bayesian optimization. Although the spectral measurement with more features can improve the resolution ability of the neural network, the results reveal that the training with the dataset of the shorter six wavelength is redundant. This analysis shows that it is very important to construct an effective 1D-CNN model area for spectral measurement using the appropriate spectral ranges and number of wavelengths. It shows that our proposed 1D-CNN model gives a new and feasible approach to measure SpO2 based on multi-wavelength.
A Microfluidic Dielectric Spectroscopy System for Characterization of Biological Cells in Physiological Media
Authors: Bakhtiari Shide , Manshadi Mohammad K. D. , Mansoorifar Amin , Beskok Ali
Published: January 2022

Dielectric spectroscopy (DS) is a promising cell screening method that can be used for diagnostic and drug discovery purposes. The primary challenge of using DS in physiological buffers is the electrode polarization (EP) that overwhelms the impedance signal within a large frequency range. These effects further amplify with the miniaturization of the measurement electrodes. In this study, we present a microfluidic system and the associated equivalent circuit models for real-time measurements of cell membrane capacitance and cytoplasm resistance in physiological buffers with 10 s increments. The current device captures several hundreds of biological cells in individual microwells through gravitational settling and measures the system’s impedance using microelectrodes covered with dendritic gold nanostructures. Using PC-3 cells (a highly metastatic prostate cancer cell line) suspended in cell growth media (CGM), we demonstrate stable measurements of cell membrane capacitance and cytoplasm resistance in the device for over 15 min. We also describe a consistent application of the equivalent circuit model, starting from the reference measurements used to determine the system parameters. The circuit model is tested using devices with varying dimensions, and the obtained cell parameters between different devices are nearly identical. Further analyses of the impedance data have shown that accurate cell membrane capacitance and cytoplasm resistance can be extracted using a limited number of measurements in the 5 MHz to 10 MHz range. This will potentially reduce the timescale required for real-time DS measurements below 1 s. Overall, the new microfluidic device can be used for the dielectric characterization of biological cells in physiological buffers for various cell screening applications.
Generating High-Quality Panorama by View Synthesis Based on Optical Flow Estimation
Authors: Zhang Wenxin , Wang Yumei , Liu Yu
Published: January 2022

Generating high-quality panorama is a key element in promoting the development of VR content. The panoramas generated by the traditional image stitching algorithm have some limitations, such as artifacts and irregular shapes. We consider solving this problem from the perspective of view synthesis. We propose a view synthesis approach based on optical flow to generate a high-quality omnidirectional panorama. In the first stage, we present a novel optical flow estimation algorithm to establish a dense correspondence between the overlapping areas of the left and right views. The result obtained can be approximated as the parallax of the scene. In the second stage, the reconstructed version of the left and the right views is generated by warping the pixels under the guidance of optical flow, and the alpha blending algorithm is used to synthesize the final novel view. Experimental results demonstrate that the subjective experience obtained by our approach is better than the comparison algorithm without cracks or artifacts. Besides the commonly used image quality assessment PSNR and SSIM, we also calculate MP-PSNR, which can provide accurate high-quality predictions for synthesized views. Our approach can achieve an improvement of about 1 dB in MP-PSNR and PSNR and 25% in SSIM, respectively.
The Use of Drone Photo Material to Classify the Purity of Photovoltaic Panels Based on Statistical Classifiers
Authors: Czarnecki Tomasz , Bloch Kacper
Published: January 2022

The subject of this work is the analysis of methods of detecting soiling of photovoltaic panels. Environmental and weather conditions affect the efficiency of renewable energy sources. Accumulation of soil, dust, and dirt on the surface of the solar panels reduces the power generated by the panels. This paper presents several variants of the algorithm that uses various statistical classifiers to classify photovoltaic panels in terms of soiling. The base material was high-resolution photos and videos of solar panels and sets dedicated to solar farms. The classifiers were tested and analyzed in their effectiveness in detecting soiling. Based on the study results, a group of optimal classifiers was defined, and the classifier selected that gives the best results for a given problem. The results obtained in this study proved experimentally that the proposed solution provides a high rate of correct detections. The proposed innovative method is cheap and straightforward to implement, and allows use in most photovoltaic installations.
Tension-Stiffening Effect Consideration for Modeling Deflection of Cracked Reinforced UHPC Beams
Authors: Teng Le , Zhang Rongling , Khayat Kamal Henri
Published: January 2022

Tension-stiffening effects can significantly influence the flexural performance of cracked reinforced concrete specimens. Such effect is amplified for fiber-reinforced concrete, given the fact that fibers can bridge the cracks. The objective of this study was to develop a model to predict the deflection of cracked reinforced ultra-high performance concrete (R-UHPC) beam elements. The modeling approach characterized the average bending moment of inertia by combining the existing model used for conventional reinforced concrete and the analytical model of stress distribution of UHPC along the cross-section. The finite element analysis (FEA) was employed to evaluate the flexural deflection based on the average bending moment of inertia. The calculated load-deflection relationships have been compared to experimental results. The results indicated that the relative errors of deflection between predicted and experimental results can be controlled within 15%, compared to values ranging from 5% to 50% calculated by neglecting the tensile properties of cracked UHPC and values ranging from 5% to 30% calculated by effective inertia of bending moment of ACI code. Therefore, the developed model can be used in practice because it can secure the accuracy of deflection prediction of the R-UHPC beams. Such a simplified model also has higher sustainability compared to FEA using solid elements since it is easier and time-saving to be established and calculated.
The Effect of Tourism Experience on Tourists’ Environmentally Responsible Behavior at Cultural Heritage Sites: The Mediating Role of Cultural Attachment
Authors: Cheng Zhenfeng , Chen Xin
Published: January 2022

With the rapid development of tourism and the explosive growth of tourist arrivals, the destructive effects of tourist activities on the ecological environment of tourist destinations are becoming increasingly severe, seriously restricting the sustainable development of these destinations. As one of the most important types of current tourist destinations, cultural heritage sites are in urgent need of a well-protected ecological environment. Environmental protection has already become an important task for their sustainable development. The behavior of tourists during visits, which plays a central role in tourist activities, has gradually become a key factor affecting the environment of tourist destinations. Therefore, approaches to effectively identify the mechanisms underpinning tourists’ environmentally responsible behavior have become a focus of both theoretical and practical domains. Based on a stimulus-organism-response (S-O-R) theoretical framework, our study established a mediation model based on cultural attachments, and explored the mechanisms affecting how cognitive, emotional, and cultural experiences influence tourists’ environmentally responsible behavior. The experience-attachment-behavior transmission mechanism was also considered. A structural equation model was applied to empirically test the 588 pieces of data collected from tourists involved in heritage tourism. The test results show that the cognitive, emotional, and cultural experiences delivered from tourist destinations of cultural heritage, positively affected tourists’ environmentally responsible behavior. Cultural attachment plays a partially mediating role between cognitive, emotional, cultural experiences and tourists’ environmentally responsible behavior. These study results not only support theoretical research on the relationship between tourism experiences and tourists’ environmentally responsible behavior, but also indicate the effective driving pathways of tourists’ environmentally responsible behavior at the practical level. As such, this research provides both theoretical reference and practical guidance for the sustainable development of tourist destinations with diverse cultural heritages.
Exploration of Hydrogeochemical Characterization and Assessment of Organic Pollution Characteristics of Shallow Groundwater near a Chemical Plant That Discharged Sewage Illegally
Authors: Zhan Hao , Wu Qiang , Liu Benhua , Zhou Guangya
Published: January 2022

Groundwater plays a significant role in domestic use and agricultural irrigation in rural areas of northern China. The untreated wastewater from the chemical plant was directly discharged into a seepage well, resulting in the pollution of groundwater. Assessing characteristics of groundwater organic pollution and identifying evolutionary mechanisms of hydrogeochemistry are beneficial for groundwater protection and sustainable management. Statistical methods (correlation analysis (CA) and principal component analysis (PCA)) combined with hydrogeochemical methods including Piper, Gibbs, Gaillardet, and ions binary diagrams and the chloride alkalinity index were employed to explore hydrogeochemical characteristics and evolutionary mechanisms. The results showed that cations were predominantly located at the Ca2+ end and anions were mostly close to the SO42− and Cl− end. The ion concentrations of groundwater were mainly affected by water–rock interactions. The weathering or dissolution of silicate (i.e., aluminosilicate minerals), evaporite (i.e., halite and gypsum), carbonate minerals (i.e., calcite and dolomite), cation exchange, and anthropogenic activities contribute to the chemical compositions of groundwater. Based on CA and PCA, the dissolution of halide minerals and the use of pesticides and fertilizers were the main factors controlling water chemistry. Additionally, the dissolution of sulfur-bearing minerals and gypsum was the key factor controlling the concentrations of Ca2+ and Mg2+. Application of mathematical statistical methods characterized that the exceedance rate of seven organic compounds with high detection rates were as follows: carbon tetrachloride (39.83%) > 1,1,2-trichloroethane (28.81%) > chloroform (10.17%) > trichloroethene (6.78%) > 1,1,2,2-tetrachloroethane (5.93%) > perchloroethylene (5.08%) > trichlorofluoromethane (0.85%). Simultaneously, pollution under the influence of volatilization and diffusion was significantly less than that in the direction of groundwater runoff.
A p-Adic Matter in a Closed Universe
Authors: Dragovich Branko
Published: January 2022

In this paper, we introduce a new type of matter that has origin in p-adic strings, i.e., strings with a p-adic worldsheet. We investigate some properties of this p-adic matter, in particular its cosmological aspects. We start with crossing symmetric scattering amplitudes for p-adic open strings and related effective nonlocal and nonlinear Lagrangian which describes tachyon dynamics at the tree level. Then, we make a slight modification of this Lagrangian and obtain a new Lagrangian for non-tachyonic scalar field. Using this new Lagrangian in the weak field approximation as a matter in Einstein gravity with the cosmological constant, one obtains an exponentially expanding FLRW closed universe. At the end, we discuss the obtained results, i.e., computed mass of the scalar p-adic particle, estimated radius of related closed universe and noted p-adic matter as a possible candidate for dark matter.
An IoT-Based Encapsulated Design System for Rapid Model Identification of Plant Development
Authors: Novak Hrvoje , Ratković Marko , Cahun Mateo , Lešić Vinko
Published: January 2022

Actual and upcoming climate changes will evidently have the largest impact on agriculture crop cultivation in terms of reduced harvest, increased costs, and necessary deviations from traditional farming. The aggravating factor for the successful applications of precision and predictive agriculture is the lack of granulated historical data due to slow, year-round cycles of crops, as a prerequisite for further analysis and modeling. A methodology of plant growth observation with the rapid performance of experiments is presented in this paper. The proposed system enables the collection of data with respect to various climate conditions, which are artificially created and permuted in the encapsulated design, suitable for further correlation with plant development identifiers. The design is equipped with a large number of sensors and connected to the central database in a computer cloud, which enables the interconnection and coordination of multiple geographically distributed devices and related experiments in a remote, autonomous, and real-time manner. Over 40 sensors and up to 24 yearly harvests per device enable the yearly collection of approximately 750,000 correlated database entries, which it is possible to independently stack with higher numbers of devices. Such accumulated data is exploited to develop mathematical models of wheat in different growth stages by applying the concepts of artificial intelligence and utilizing them for the prediction of crop development and harvest.
Contonation and communicative strategy as mechanisms of the 21st century music analysis
Authors: Nikolayevskaya Yuliya
Published: January 2022

The purpose of this study is the experience of actualization of the two chosen concepts from the point of view of the interpretive approach, which is aimed at the subject of music and demonstrates the strengthening of the role of the communicative component.