bluuebunny/crossref_metadata_2025 huggingface dataset:
Emergency medical dispatchers’ experiences of managing emergency calls: a qualitative interview study
Authors: Torlén Wennlund Klara , Kurland Lisa , Olanders Knut , Khoshegir Amanda , Kamil Hussein Al , Castrén Maaret , Bohm Katarina
Published: April 2022

Objectives

To explore the emergency medical dispatchers (EMDs) experiences of managing emergency medical calls.

Design

A qualitative interview study with an inductive approach. EMDs were interviewed individually using a semistructured interview guide. The verbatim transcripts were analysed using a qualitative content analysis.

Setting

EMDs, without a professional background as registered nurses, were recruited from emergency medical communication centers (EMCCs) within Sweden.

Participants

To achieve a varied description of EMDs’ experiences, participants were included from several EMCCs nationally, using a convenience sampling. Interviews were performed up until saturation of data, resulting in 13 EMDs from 7 EMCCs being interviewed. All the EMDs were women, ranging in age from 28 to 61 years (mean 42 years), and had worked in emergency medical dispatching between 1 and 13.5 years (mean 6.5 years).

Results

The analysis revealed the main category—to attentively manage a multifaceted, interactive task—made up of three categories: utilize creativity to gather information, continuously process and assess complex information, and engage in the professional role. The content of each category was reflected in several subcategories further described and illustrated with representative quotes.

Conclusions

Managing emergency medical calls was experienced by EMDs to attentively manage a multifaceted interactive task. Core parts were described as: the ability to utilize creativity to gather information, continuously process and asses complex information, and engage in the professional role. Our results could be beneficial for emergency care managers when designing training programmes and organising EMD work and the EMD work environment, including further development of dispatch protocols and implementation of regular feedback sessions. Moreover, the results indicate that aspects such as self-awareness and emotional challenges encountered during EMD work could be important matters to discuss during staff evaluations.
A cohort study of duplicate faecal immunochemical testing in patients at risk of colorectal cancer from North-West England
Authors: Hunt Natalie , Rao Christopher , Logan Robert , Chandrabalan Vishnu , Oakey Jane , Ainsworth Claire , Smith Neil , Banerjee Saswata , Myers Martin
Published: April 2022

Objectives

We sought to investigate if duplicate faecal immunochemical testing (FIT) sampling improves the negative and positive predictive value of patients thought to be at risk of colorectal cancer (CRC). Specifically, we aimed to investigate whether the proportion of FIT-negative CRC missed by a single FIT test in symptomatic patients could be reduced by duplicate FIT testing.

Design

A retrospective service evaluation cohort study of the diagnostic accuracy of duplicate FIT testing.

Setting

Patients referred from primary care with suspected CRC to four secondary care trusts in North-West England.

Participants

28 622 patients over 18-years-old with lower gastrointestinal symptoms suggestive of CRC who completed two FIT samples.

Primary and secondary outcome measures

The performance of duplicate FIT for detecting CRC at a threshold of 10 µgHb/g.

Results

The sensitivity if either test was >10 µgHb/g was 0.978 (0.955–0.989), specificity was 0.662 (0.657–0.668), positive predictive value 0.031 (0.028–0.035) and negative predictive value 1.00 (0.999–1.00). Despite two-thirds of patients (18952) being negative following two tests, at this threshold only seven CRC were missed over a 26-month period. All seven patients had other high-risk features which should have prompted investigation.

Conclusions

This study suggests that in routine NHS practice, a duplicate FIT sample strategy together with clinical evaluation for evidence of anaemia and weight loss is superior to a single FIT sample alone and would allow symptomatic patients to be managed in primary care without the need for urgent referral to secondary care for urgent colonic imaging.
Comparison of prediction methods for treatment continuation of antipsychotics in children and adolescents with schizophrenia
Authors: Jeon Soo Min , Cho Jaehyeong , Lee Dong Yun , Kwon Jin-Won
Published: April 2022

Objective

There is little evidence for finding optimal antipsychotic treatment for schizophrenia, especially in paediatrics. To evaluate the performance and clinical benefit of several prediction methods for 1-year treatment continuation of antipsychotics.

Design and Settings

Population-based prognostic study conducting using the nationwide claims database in Korea.

Participants

5109 patients aged 2–18 years who initiated antipsychotic treatment with risperidone/aripiprazole for schizophrenia between 2010 and 2017 were identified.

Main outcome measures

We used the conventional logistic regression (LR) and common six machine-learning methods (least absolute shrinkage and selection operator, ridge, elstic net, randomforest, gradient boosting machine, and superlearner) to derive predictive models for treatment continuation of antipsychotics. The performance of models was assessed using the Brier score (BS), area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC). The clinical benefit of applying these models was also evaluated by comparing the treatment continuation rate between patients who received the recommended medication by models and patients who did not.

Results

The gradient boosting machine showed the best performance in predicting treatment continuation for risperidone (BS, 0.121; AUROC, 0.686; AUPRC, 0.269). Among aripiprazole models, GBM for BS (0.114), SuperLearner for AUROC (0.688) and random forest for AUPRC (0.317) showed the best performance. Although LR showed lower performance than machine learnings, the difference was negligible. Patients who received recommended medication by these models showed a 1.2–1.5 times higher treatment continuation rate than those who did not.

Conclusions

All prediction models showed similar performance in predicting the treatment continuation of antipsychotics. Application of prediction models might be helpful for evidence-based decision-making in antipsychotic treatment.
International examples of primary care COVID-19 preparedness and response: a comparison of four countries
Authors: Goodyear-Smith Felicity , Kidd Michael , Oseni Tijani Idris Ahmad , Nashat Nagwa , Mash Robert , Akman Mehmet , Phillips Robert L , van Weel Chris
Published: April 2022

We report the learnings gleaned from a four-country panel (Australia, South Africa, Egypt and Nigeria) sharing their countries’ COVID-19 primary healthcare approaches and implementation of policy at the World Organization of Family Doctor’s World virtual conference in November. The countries differ considerably with respect to size, national economies, average age, unemployment rates and proportion of people living rurally. South Africa has fared the worst with respect to waves of COVID-19 cases and deaths. All countries introduced strategies such as border closure, COVID-19 testing, physical distancing and face masks. Australia and Nigeria mobilised primary care, but the response was mostly public health and hospital-based in South Africa and Egypt. All countries rapidly adopted telehealth. All countries emphasised the critical importance of an integrated response between primary care and public health to conduct surveillance, diagnose cases through testing, provide community-based care unless hospitalisation is required and vaccinate the population to reduce infection spread.
Influence of pin profile on formability of friction stir-welded aluminum tailor-welded blanks: an experimental and finite element simulation analysis
Authors: Battina N. Malleswararao , Hari Krishna Chirala , Vanthala Varaha Siva Prasad
Published: April 2022

In sheet metal forming processes, the forming limit diagram is frequently employed as a criterion for predicting necking initiation. This is one of the most useful and effective methods for the evaluation of the formability of tailor-welded blanks. The goal of this study was to determine the formability of friction stir-welded (FSW) aluminium alloy 6061-temper 6 (AA6061-T6) and aluminium alloy 2017-temper 6 (AA2017-T6) by employing five dissimilar tool pin profiles. To evaluate the limiting dome height, five different combinations of dissimilar blanks were used in experimental and simulation experiments. Material characteristics such as density, elastic modulus, and all multilinear behaviors of blanks were manually assigned for simulation from the test results of true stress versus true strain plots. The punch with die supports was considered as a rigid body, whereas the metallic blanks were considered as plastic material. To carry out the simulation, the entire blank was divided into three zones. The results obtained from the experimental and simulation results showed that the straight square tool pin profile is the optimal tool pin profile for the formability of FSW AA6061-T6 and AA2017-T6. The tested height values obtained from the limiting dome height were 20.5 and 20.9 mm in experimentation and simulation, respectively. The straight cylindrical tool pin profile exhibited the worst formability properties in both experimentation and simulation.
Excitation functions of proton-induced nuclear reactions on $$^{86}$$Sr, with particular emphasis on the formation of isomeric states in $$^{86}$$Y and $$^{85}$$Y
Authors: Uddin M. S. , Basunia M. S. , Sudár S. , Scholten B. , Spellerberg S. , Voyles A. S. , Morrell J. T. , Fox M. B. , Spahn I. , Felden O. , Gebel R. , Bernstein L. A. , Neumaier B. , Qaim S. M.
Published: April 2022

Cross sections of proton-induced nuclear reactions on enriched $$^{\mathrm {86}}$$

86

Sr target were measured by the activation technique up to proton energies of 44  MeV. The isomeric cross-section ratios for $$^{\mathrm {86m,g}}$$

86
m
,
g

Y and $$^{\mathrm {85m,g}}$$

85
m
,
g

Y as a function of projectile energy were deduced from their measured data. The present experimental data for the nuclear reaction products, namely $$^{\mathrm {86m}}$$

86
m

Y, $$^{\mathrm {86g+xm}}$$

86
g
+
xm

Y, $$^{\mathrm {85m}}$$

85
m

Y, $$^{\mathrm {85g}}$$

85
g

Y, $$^{\mathrm {84}}$$

84

Rb and $$^{\mathrm {83}}$$

83

Rb were compared with the results of nuclear model calculations using the code TALYS, which combines the statistical, precompound, and direct interactions. In general, the experimental cross-section data as well as the isomeric cross-section ratios are reproduced well by the model calculations, provided the input model parameters are properly chosen and the level structure of the product nucleus is thoughtfully considered. The quality of the agreement between experimental data and model calculations was numerically quantified. For products formed via emission of a light complex particle as well as multi-nucleons (e.g., $$\alpha $$
α
and 2p2n), the contribution of the latter process starts increasing when its energy threshold is crossed.
A Layered Spiking Neural System for Classification Problems
Authors: Zhang Gexiang , Zhang Xihai , Rong Haina , Paul Prithwineel , Zhu Ming , Neri Ferrante , Ong Yew-Soon
Published: April 2022

Biological brains have a natural capacity for resolving certain classification tasks. Studies on biologically plausible spiking neurons, architectures and mechanisms of artificial neural systems that closely match biological observations while giving high classification performance are gaining momentum. Spiking neural P systems (SN P systems) are a class of membrane computing models and third-generation neural networks that are based on the behavior of biological neural cells and have been used in various engineering applications. Furthermore, SN P systems are characterized by a highly flexible structure that enables the design of a machine learning algorithm by mimicking the structure and behavior of biological cells without the over-simplification present in neural networks. Based on this aspect, this paper proposes a novel type of SN P system, namely, layered SN P system (LSN P system), to solve classification problems by supervised learning. The proposed LSN P system consists of a multi-layer network containing multiple weighted fuzzy SN P systems with adaptive weight adjustment rules. The proposed system employs specific ascending dimension techniques and a selection method of output neurons for classification problems. The experimental results obtained using benchmark datasets from the UCI machine learning repository and MNIST dataset demonstrated the feasibility and effectiveness of the proposed LSN P system. More importantly, the proposed LSN P system presents the first SN P system that demonstrates sufficient performance for use in addressing real-world classification problems.
Bootstrapping microcanonical ensemble in classical system
Authors: Nakayama Yu
Published: April 2022

We point out that the bootstrap program in quantum mechanics proposed by Han et al. reduces to a bootstrap study of a microcanonical ensemble of the same Hamiltonian in the [Formula: see text] limit. In the limit, the quantum mechanical archipelago becomes an extremely thin line for an anharmonic oscillator. For a double-well potential, a peninsula in [Formula: see text] appears.
ℐ𝒢,𝒩-Implications Induced from Quasi-Grouping Functions and Negations on Bounded Lattices
Authors: Qiao Junsheng , Zhao Bin
Published: April 2022

Grouping functions, as one new case of not necessarily associative particular binary aggregation functions, have been proposed in the literature for their vast applications in fuzzy community detection problems, image processing and decision making. On the other hand, due to the wide applications in fuzzy reasoning, fuzzy control and approximate reasoning, the investigations of fuzzy implications derived from specific binary aggregation functions become a natural and hot research topic. In this paper, we focus on this research area and consider the [Formula: see text]-implications induced from quasi-grouping functions and negations on bounded lattices. To be precise, firstly, by removing the continuity condition, we extend the notion of grouping functions on the unit closed interval to the so-called quasi-grouping functions on bounded lattices. Secondly, we give some basic properties and two construction methods of quasi-grouping functions on bounded lattices. Finally, we give the concept of [Formula: see text]-implications and focus on the conditions under which they can satisfy the certain algebraic properties possessed by implications on bounded lattices.
Best Option of Investment in Renewable Energy: A Multicriteria Decision-Making Analysis for Iranian Energy Industry
Authors: Norouzi Nima , Bozorgian Alireza , Dehghani Mohammad Ali
Published: April 2022

Electricity production and consumption can be considered as one of the most important factors and necessities in the growth and development of any country. To generate electricity, it is necessary to build power plants. Due to the high exchange rate and the high cost of construction and operation of any new power plant in the electricity industry, it is necessary to select these power plants based on a wide range of criteria. In this research, using economic, environmental, technical, and social criteria, different power plants in Iran are prioritised using Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) fuzzy hierarchical analysis methods for the 2018–2040 period. Indicators of environmental pollution, initial investment per unit of electricity generated, maintenance costs, accessibility, public acceptability, and the possibility of developing and increasing capacity were the main indicators affecting the prioritisation of power plants in Iran. In general, according to all the indicators studied in this study, the level of environmental pollution has the greatest impact on the prioritisation of power plants. Also, the indicators related to the amount of initial investment per kilowatt-hour of electricity generated, maintenance costs, the possibility of expanding and increasing the capacity, and the possibility of easy access to spare parts were the most important factors. The results of multicriteria decision prioritisation show that solar power plants are the first option for the strategic choice of power plants, and wind farms and small-scale biomass are in the next priorities. Therefore, it is suggested that the government and policy institutions, according to the prioritisation of power plants, create the necessary infrastructure to exploit these energies.
Complex dynamics in a Filippov pest control model with group defense
Authors: Hou Xiang , Liu Bing , Wang Yilin , Zhao Zhong
Published: April 2022

In this paper, an integrated pest management Filippov model with group defense behavior is established, which takes the population density of pests as the control index of integrated pest management. First, under the condition that both subsystems have a globally asymptotically stable equilibrium, the dynamics of the established model are systematically analyzed, including the sliding mode dynamics, the existence and global stability of the real, virtual and pseudo equilibrium, as well as boundary-node and boundary-focus bifurcation. Next, we study the complex dynamics in the Filippov model when an unstable node (focus) or a stable limit cycle occurs in the subsystem by using numerical simulations. The results show that although there are no closed orbits in subsystem, a stable periodic solution may exist for Filippov system after switching perturbation. Finally, we conclude that the group defense behavior of pest makes it harder to control.
Reconstruction method of equilibrated flux for a posteriori error estimate of elliptic problems
Authors: Han Feng , Liu Yu , Wang Jianguo
Published: April 2022

In this paper, a method which reconstructs an H(div)-conforming local equilibrated flux is presented for equilibrated flux-based a posteriori error estimate for the finite element method of the second-order elliptic problem. The flux is reconstructed in the lowest-order Raviart–Thomas spaces for finite element approximation. For a simplicial mesh, the reconstruction which performed on every element rather than on the patch of the elements of the mesh or on the dual mesh is achieved by solving a third (or fourth)-order linear equations on every element and a second-order linear equations on every edge or face. So, the amount of computational work is small. Numerical examples demonstratex the effectiveness and improvements of our method.
On the Origin of Religious Values: Does Italian Weather Affect Individualism in Bolivia?
Authors: Davis Lewis
Published: April 2022

In this paper, I advance and empirically support the indigenous religious values hypothesis, which holds that religions espouse values indigenous to the countries in which they developed. To identify the indigenous values of a religion’s homeland, I rely on the negative relationship between individualism and rainfall variation. I find strong empirical support for the hypothesis that contemporary individualism depends on rainfall variation in the homelands of religions to which a country’s population adheres. Indeed, this relationship explains over a quarter of the international variation in individualism. This effect is robust to controls for the role of religion in institutional and technological transfers and the confluence of conversion and colonisation. In keeping with the explicitly religious nature of the mechanism proposed here, I also find that rainfall variation in religion homelands plays a greater role in explaining the values of countries with greater religious freedom and the values of individuals who are more religious or members of religious minorities.
Religiosity, Smoking and Other Risky Behaviors
Authors: Roman Monica , Zimmermann Klaus F. , Plopeanu Aurelian-Petrus
Published: April 2022

While under communism the identity-providing religion was suppressed, religiosity is strong today even among the youth in post-communist countries. This provides an appropriate background to investigate how external and internal religiosity relate to risky behaviors like smoking, drinking, and drugs among the young. This study shows that not religion as such or internal religiosity, but largely observable (external) religiosity prevents them from wallowing in those vices. While this is found strongly for both males and females, those females doubting or reflecting religion show a somewhat smaller risky activity.
Identifying relict periglacial features in watershed landscape and deposits of Borisoglebsk Upland, Central European Russia
Authors: Garankina Ekaterina V. , Lobkov Vasily A. , Shorkunov Ilya G. , Belyaev Vladimir R.
Published: April 2022

Watershed landscapes of the Central Russian Plain, which were subjected to the Late Pleistocene permafrost, bear witness to widespread cryogenic structuring. It is reflected both in semi-regular spots, blocks and polygons in soil and vegetation cover on arable fields and as vertically oriented wedge casts in surficial deposits. This study aimed to identify relict periglacial features in both the landscape and sedimentary sequence of the Borisoglebsk Upland to determine if there is a correspondence of these cast networks to the distribution of landforms and regular patterns of soil and vegetation cover. Combined interpretation of aerial and satellite multi-temporal imagery and detailed investigation of vertical cross-sections in gradually expanding geotechnical trenches including apparent magnetic susceptibility measurements allowed us to reveal and spatially correlate three generations of wedge casts, each buried by well-pronounced sedimentary units, and a specific bulbous type of cast. The type of cryogenesis, erosion and slope mass-movements changed from the Late Pleniglacial to Late Glacial, representing a good proxy in the watershed sedimentary cover for palaeoenvironmental reconstructions. However, regular polygonal patterns caused by these casts are almost erased in the modern topography whereas shallow dry gullies mostly inherit pre-Holocene wider linear depressions with no clear relationship to the buried cryogenic polygons.
GPSClean: A Framework for Cleaning and Repairing GPS Data
Authors: Fang Chenglong , Wang Feng , Yao Bin , Xu Jianqiu
Published: April 2022

The rise of GPS-equipped mobile devices has led to the emergence of big trajectory data. The collected raw data usually contain errors and anomalies information caused by device failure, sensor error, and environment influence. Low-quality data fails to support application requirements and therefore raw data will be comprehensively cleaned before usage. Existing methods are suboptimal to detect GPS data errors and do the repairing. To solve the problem, we propose a framework called
GPSClean
to analyze the anomalies data and develop effective methods to repair the data. There are primarily four modules in
GPSClean
: (i) data preprocessing, (ii) data filling, (iii) data repairing, and (iv) data conversion. For (i), we propose an approach named
MDSort (Maximum Disorder Sorting)
to efficiently solve the issue of data disorder. For (ii), we propose a method named
NNF (Nearest Neighbor Filling)
to fill missing data. For (iii), we design an approach named
RCSWS (Range Constraints and Sliding Window Statistics)
to repair anomalies and also improve the accuracy of data repairing by mak7ing use of driving direction. We use 45 million real trajectory data to evaluate our proposal in a prototype database system SECONDO. Experimental results show that the accuracy of RCSWS is three times higher than an alternative method SCREEN and nearly an order of magnitude higher than an alternative method EWMA.
Sex as a Biological Variable in Nutrition Research: From Human Studies to Animal Models
Authors: Chen Yilin , Kim Minhoo , Paye Sanjana , Benayoun Bérénice A.
Published: April 2022

Biological sex is a fundamental source of phenotypic variability across species. Males and females have different nutritional needs and exhibit differences in nutrient digestion and utilization, leading to different health outcomes throughout life. With personalized nutrition gaining popularity in scientific research and clinical practice, it is important to understand the fundamentals of sex differences in nutrition research. Here, we review key studies that investigate sex dimorphism in nutrition research: sex differences in nutrient intake and metabolism, sex-dimorphic response in nutrient-restricted conditions, and sex differences in diet and gut microbiome interactions. Within each area above, factors from sex chromosomes, sex hormones, and sex-specific loci are highlighted.
Advancing Health Equity Efforts to Reduce Obesity: Changing the Course
Authors: Kumanyika Shiriki K.
Published: April 2022

Population-based solutions are needed to stabilize and then reverse the continued upward trends in obesity prevalence in the US population and worldwide. This review focuses on the related, urgent issue of disparities in obesity prevalence affecting US racial/ethnic minority and other socially marginalized populations. The review provides background on these disparities from a health equity perspective and highlights evidence of progress in equity-focused obesity efforts. Five recommendations for advancing equity efforts are offered as potential approaches to build on progress to date: ( a) give equity issues higher priority, ( b) adopt a health equity lens, ( c) strengthen approaches by using health equity frameworks, ( d) broaden the types of policies considered, and ( e) emphasize implementation science concepts and tools. Potential challenges and opportunities are identified, including the prospect of longer-term, transformative solutions that integrate global and national initiatives to address obesity, undernutrition, and climate change.
Plasma-Induced Modifications on High Density Polyethylene and Polyethylene Terephthalate
Authors: Abdeltwab E. , Atta A.
Published: April 2022

This work presents comprehensive study of high density polyethylene (HDPE) and polyethylene terephthalate (PET) surface properties after exposed to 1.5, 3, 4.5 and 6 min oxygen (O2) plasma. The polymer surface structure is analyzed by Raman spectroscopy, which revealed surface restructuring modifications. The contact angle of HDPE and PET decreased gradually, and the work of adhesion is improved with O2 plasma. The water contact angle is reduced from 61.6° to 36.3° for HDPE and from 72.4° to 37.5° for PET by increasing plasma time from 1.5 to 6 min. The surface free energy is enhanced from 27.8 mJ m−2 to 69.0 mJ m−2 for HDPE and from 29.8 mJ m−2 to 67.2 mJ m−2 for PET, when the plasma time increased from 0 to 6 min. The polar groups significantly reduced the hydrophobicity of the irradiated films, and consequently the surface wettability is improved. The results showed observed improvement in surface properties of HDPE and PET polymeric films to be use in different applications such as printings, coatings and optoelectronics.
A Mixture of Clayton, Gumbel, and Frank Copulas: A Complete Dependence Model
Authors: Boateng M. A. , Omari-Sasu A. Y. , Avuglah R. K. , Frempong N. K.
Published: April 2022

Knowledge of the dependence between random variables is necessary in the area of risk assessment and evaluation. Some of the existing Archimedean copulas, namely the Clayton and the Gumbel copulas, allow for higher correlations on the extreme left and right, respectively. In this study, we use the idea of convex combinations to build a hybrid Clayton–Gumbel–Frank copula that provides all dependence scenarios from existing Archimedean copulas. The corresponding density and conditional distribution functions of the derived models for two random variables, as well as an estimator for the proportion parameter associated with the proposed model, are also derived. The results show that the proposed model is able to show any case of dependence by providing coefficients for the upper tail and lower tail dependence.
Effect of Low-Cost Perovskite Based Lean NOx Trap to Reduce the NOx Emission for CRDI Engine
Authors: Kombiah Chinnadurai , Pachamuthu Senthil Kumar , Rajappa Bharathan
Published: April 2022

Lean NOx trap (LNT) is an after-treatment technology that targets NOx emissions from an IC Engine and reduces it by using fuel as the reductant. The main mechanisms involved in this process are (i) oxidation of NO into NO2, (ii) Entrapment of NO2 over an alkali Earth metal in the form of nitrates, and (iii) Regeneration and reduction of NO2. The oxidation and reduction reactions are usually performed over rare Platinum Group Metals (PGM). The alternate cycling of operation modes helps in the regeneration and reduction stage due to the presence of unburnt hydrocarbons and carbon monoxides. These HC and CO generated during profitable operation can reduce agents similar to ammonia in SCR (Selective Catalytic Reduction). In the case of LNT, the fuel-injected for reduction imposes a penalty on the system. Cobalt-based perovskites with the chemical formula “ACoO3” (where “A” denotes Ba, Sr, etc.) show excellent absorption and reduction tendencies towards NOx and are highly suited for LNT as they have higher NO oxidation capacity. This research experimented with two different coating procedures (with and without binder) with three other perovskite catalysts–BaCoO3, SrCoO3, and Ba0.5Sr0.5CoO3. Both the coatings were tested for their adherence, and it revealed that the binder-less layer had only 4% coating loss after 2 hrs of sonication. BaCoO3 showed higher NOx absorption due to the higher electropositive nature of barium. The peak conversion efficiency attained in this experiment was 84% at a catalyst temperature of 350°C and 40% load condition.
Stress‐Induced Structural Phase Transition in Polystyrene/NaYF4: Eu3+ Photoluminescent Electrospun Nanofibers
Authors: Kumar Sanjeev , Jain Garima , Kumar Kuldeep , Gupta Ashish , Tawale J. S. , Singh B. P. , Dhakate S. R. , Sahare P. D.
Published: April 2022

Polystyrene (PS) composite nanofibers were successfully fabricated by embedding NaYF4: Eu3+ nanophosphor into the PS matrix via electrospinning. The photoluminescence spectra, surface morphology and crystal structure of nanofibers were characterized by photoluminescence spectroscopy, scanning electron microscopy, and X‐ray diffractometer, respectively. Stress‐induced α‐NaYF4: Eu3+ (cubic) to β‐NaYF4: Eu3+(hexagonal) structural phase transformation was observed in the nanofibers. The stress‐induced phase transformation provides enough space for tailoring the properties of novel nanostructures. The composite nanofibers exhibited blue emission with 239 nm excitation wavelength. The XRD pattern of espun nanofibers confirmed the successful incorporation of 5% NaYF4: Eu3+ nanophosphors into the PS matrix. Brilliant values of the chromaticity coordinates of the prepared photoluminescent nanofibers (PLNs) predict their possible use in blue solid‐state lighting applications.
Personality Privacy Protection Method of Social Users Based on Generative Adversarial Networks
Authors: Sui Yi , Wang Xiujuan , Zheng Kangfeng , Shi Yutong , Cao Siwei
Published: April 2022

Obscuring or otherwise minimizing the release of personality information from potential victims of social engineering attacks effectively interferes with an attacker’s personality analysis and reduces the success rate of social engineering attacks. We propose a text transformation method named PerTransGAN using generative adversarial networks (GANs) to protect the personality privacy hidden in text data. Making use of reinforcement learning, we use the output of the discriminator as a reward signal to guide the training of the generator. Moreover, the model extracts text features from the discriminator network as additional semantic guidance signals. And the loss function of the generator adds a penalty item to reduce the weight of words that contribute more to personality information in the real text so as to hide the user’s personality privacy. In addition, the semantic and personality modules are designed to calculate the semantic similarity and personality distribution distance between the real text and the generated text as a part of the objective function. Experiments show that the self-attention module and semantic module in the generator improved the content retention of the text by 0.11 compared with the baseline model and obtained the highest BLEU score. In addition, with the addition of penalty item and personality module, compared with the classification accuracy of the original data, the accuracy of the generated text in the personality classifier decreased by 20%. PerTransGAN model preserves users’ personality privacy as found in user data by transforming the text and preserving semantic similarity while blocking privacy theft by attackers.
Sentimental Analysis of Twitter Users from Turkish Content with Natural Language Processing
Authors: Balli Cagla , Guzel Mehmet Serdar , Bostanci Erkan , Mishra Alok
Published: April 2022

Artificial Intelligence has guided technological progress in recent years; it has shown significant development with increased academic studies on Machine Learning and the high demand for this field in the sector. In addition to the advancement of technology day by day, the pandemic, which has become a part of our lives since early 2020, has led to social media occupying a larger place in the lives of individuals. Therefore, social media posts have become an excellent data source for the field of sentiment analysis. The main contribution of this study is based on the Natural Language Processing method, which is one of the machine learning topics in the literature. Sentiment analysis classification is a solid example for machine learning tasks that belongs to human-machine interaction. It is essential to make the computer understand people emotional situation with classifiers. There are a limited number of Turkish language studies in the literature. Turkish language has different types of linguistic features from English. Since Turkish is an agglutinative language, it is challenging to make sentiment analysis with that language. This paper aims to perform sentiment analysis of several machine learning algorithms on Turkish language datasets that are collected from Twitter. In this research, besides using public dataset that belongs to Beyaz (2021) to get more general results, another dataset is created to understand the impact of the pandemic on people and to learn about public opinions. Therefore, a custom dataset, namely, SentimentSet (Balli 2021), was created, consisting of Turkish tweets that were filtered with words such as pandemic and corona by manually marking as positive, negative, or neutral. Besides, SentimentSet could be used in future researches as benchmark dataset. Results show classification accuracy of not only up to ∼87% with test data from datasets of both datasets and trained models, but also up to ∼84% with small “Sample Test Data” generated by the same methods as SentimentSet dataset. These research results contributed to indicating Turkish language specific sentiment analysis that is dependent on language specifications.
Artificial Intelligence Algorithms for Multisensor Information Fusion Based on Deep Learning Algorithms
Authors: Jiang Lan
Published: April 2022

Artificial intelligence (AI) has been widely used all over the world. AI can be applied not only in mechanical learning and expert system but also in knowledge engineering and intelligent information retrieval and has achieved amazing results. This article aims to study the relevant knowledge of deep learning algorithms and multisensor information fusion and how to use deep learning algorithms and multisensor information fusion to study AI algorithms. This paper raises the question of whether the improved multisensor information fusion will affect the AI algorithm. From the data in the experiment of this article, the accuracy of the neural network before the improvement was 4.1%. With the development of society, the traditional algorithm finally dropped to 1.3%. The accuracy of the multisensor information fusion algorithm before the improvement was 3.1% at the beginning; with the development of society, it finally dropped to 1%; it can be known that the accuracy of the improved neural network is 4.6%, and with continuous improvement, it finally increased to 9.8%. The improved multisensor information fusion algorithm is the same, the accuracy at the beginning was 3.9%, and gradually increased to 9.5%. From this set of data, it can be known that the improved convolutional neural network (CNN) algorithm, and the improved multisensor information fusion algorithm should be used to study AI algorithms.
Characteristics and Antioxidant Activity of Fucoidan from Sargassum hystrix: Effect of Extraction Method
Authors: Husni Amir , Izmi Nuzulia , Ayunani Fatimah Zahra , Kartini Aprilia , Husnayain Naila , Isnansetyo Alim
Published: April 2022

Fucoidan is a bioactive compound of brown seaweed with antioxidant characteristics. This study examined the aftermath of the extraction method on the yield, fucose content, xylose content, sulfate content, total sugar, antioxidant activity, and functional groups of fucoidan from Sargassum hystrix. The brown seaweed was extracted using 4 methods, namely, A (0.1 N HCl, room temperature, 24 h), B (2% CaCl2, 85°C, 4 h), C (85% ethanol, room temperature, 12 h), and D (0.5% EDTA, 70°C, 3 h). The antioxidant activity testing was carried out using the 2,2-diphenyl-1-picrylhydrazyl (DPPH), Ferric-Reducing Antioxidant Power (FRAP), and Hydroxyl Radical Scavenging Activity (HRSA). The yield for methods of A, B, C, and D was

2.46
±
0.30

,

0.68
±
0.34

,

1.18
±
0.15

, and

0.62
±
0.25
%

, with fucose content of

39.97
±
4.82

,

26.72
±
3.38

,

41.08
±
9.49

, and

40.62
±
8.59
%

, xylose content of

8.07
±
0.92

,

5.63
±
0.40

,

6.80
±
0.83

, and

7.83
±
1.83
%

, and the sulfate content of

11.47
±
2.20

,

15.31
±
2.47

,

30.62
±
2.76

, and

27.80
±
3.59
%

. The result indicated the occurrence of a sulfate ester group in the functional group analysis with numerous similarities with the commercial fucoidan. The highest antioxidant activity of fucoidan from S. hystrix was found in method C, which was influenced by sulfate levels. Therefore, the extraction method of fucoidan from S. hystrix affects the characteristics and antioxidant activity.
Numerical Analysis of a Small Pneumatic Hammer Performance Based on Evaluation Method of Friction Force
Authors: Yang Un Hyok , Han Tok Hyong , Han Un Chol , Tae Il Gwang , Hong Ryo Myong , Kim Song Chol
Published: April 2022

Mechanical power loss in pneumatic hammers comes from the friction between parts in relative motion, and wear is among the failure mechanisms of the top hammer. Therefore, it is important for high performance and a longer service life of pneumatic hammers to reduce the friction force between parts in relative motion. This study presented a novel approach to quantitatively determine the friction force and consider it in the simulation model of pneumatic hammer. First, the friction force between piston and cylinder in a small pneumatic hammer was measured using an experimental setup at different inlet pressures. We could find from the experimental result that the friction force was about 0.8 N under the horizontal installation when there was no pressure supply, but it increased significantly, was 20 times greater than that without pressure supply, due to aerodynamic action by compressed air leaked from the annular gaps between the cylindrical matching surfaces of the components. In addition, it increased from 10.27 to 16.7 N due to an increase in inlet pressure and mechanical power loss in the pneumatic hammer that was about 10% of impact energy. Then, numerical analysis for a small pneumatic hammer performance was performed by a model considered the friction force using AMESim software. Finally, it can be seen from the simulation results that the proposed approach could significantly reduce the error between the simulated and the measured values for the impact energy because of ignoring the friction force. This approach will be used to predict service life of piston and find a low friction piston of pneumatic hammer in practical engineering.
Internet of Things Online Course Construction of Multimedia Technology
Authors: Zhang Jingbin
Published: April 2022

The advancement of modern multimedia and internet education systems has enriched the presentation and dissemination methods of educational resources and changed people’s learning methods and behavior habits. Online learning has become a way of life and a hotspot of the times, and optimizing the quality of online education services has gradually become a common demand of society. IoT is the sense of relating all things to the Internet. It is another type of network that has been extended and expanded by accelerated improvements in network infrastructure. It has powerful communication, data storage, modification, and computing functions for related logic and data. From the perspective of online course construction, this paper proposes a research direction of IoT online courses based on multimedia technology. Firstly, a brief introduction to the theoretical overview of online courses is given, and then, an in-depth study of the IoT technology is carried out. Then, through the theoretical analysis of the online course mode, combined with the characteristics and functions of the IoT of multimedia technology, the design method of the online course system is proposed. Finally, a comparative experiment is conducted between the IoT online course of multimedia technology and the traditional online course. The experimental results show that the overall mean of the students’ two test scores under the IoT online course teaching of multimedia technology is 6.675 points higher than that under the traditional online course teaching. It shows that the teaching of IoT online courses based on multimedia technology is more conducive to improving students’ learning ability and level, thereby improving the quality of teaching.
Numerical Study on the Water Entry Impact Forces of an Air-Launched Underwater Glider under Wave Conditions
Authors: Wu Xiangcheng , Chang Xin , Liu Shewen , Yu Pengyao , Zhou Lilei , Tian Wei
Published: April 2022

In this study, the water entry of an air-launched underwater glider under wave conditions is numerically simulated by the computational fluid dynamics method. The numerical model is validated by the comparison of nondimensional water entry impact force with published experimental and numerical results. And the influence of water entry points, water entry angles, and water entry attack angles on impact force is studied, which provides guidance for the design of air-launched underwater gliders. The results show that the water entry point has a great influence on the peak value of vertical impact force. In the present study, the peak value of the maximum vertical impact force at different water entry points is almost twice the minimum peak value with the same water entry velocity. The water entry angle at the same water entry point has great influence on the peak value of horizontal impact force, which is mainly related to the horizontal component of the impact velocity. The greater the horizontal component of impact velocity, the greater the peak value of impact force. In addition, the attack angle hardly affects the water entry impact force of the glider with hemispherical head.
Efficacy and Safety of Xiaoyao Recipe in the Treatment of Poststroke Depression: A Systematic Review and Meta-Analysis
Authors: Wang Dou , Li Tao , Ron Jie , Mao Meiling , Yang Yifan , Feng Yalun , Yan Yongmei
Published: April 2022

Background. Poststroke depression (PSD) is a common neuropsychiatric disorder that affects the disability, mortality, functional recovery, and quality of daily life of patients. Xiaoyao Recipe (XYR) is often used to treat PSD and has achieved good clinical effects, but it lacks reliable evidence. Objective. This study aims to evaluate the effectiveness and safety of XYR on PSD through meta-analysis. Methods. A comprehensive literature search was carried out in multiple databases, including PubMed, the Cochrane Library, Chinese Biomedical Literature Service System, China National Knowledge Infrastructure, Wanfang Database, VIP Database, and ClinicalTrials, from inception to July 1, 2021, to collect randomized controlled trials that applied XYR for patients with PSD. For a controlled trial, the search time limit was set from the time of the database’s establishment to July 2021. Two experienced researchers independently screened the literature according to the inclusion and exclusion criteria, extracted data, evaluated the quality of the literature, and used RevMan 5.3 software for meta-analysis. Results. A total of 12 studies were included in this study, involving 882 patients with PSD who were hospitalized or outpatients. The meta-analysis results showed that the total effective rate (

p
<
0.00001

) of the test group (XYR or XYR combined with antidepressants) after treatment was high; Hamilton’s Depression Scale score (

p
<
0.000001

), Scandinavian Stroke Scale score (

p
=
0.004
<
0.05

), and Barthel index (

p
<
0.00001

) were improved; the incidence of adverse reactions (

p
<
0.00001

) was low; and the serum serotonin content (

p
<
0.00001

) was high. Conclusion. Compared with antidepressant drugs, XYR is more effective and safer in the treatment of PSD patients. However, more high-quality studies are needed to further support the above conclusions.
The Theoretical Research on Grey Catastrophe Model of Traffic System
Authors: Guo Huan , Zhang Yunxin , Zhang Hongmao
Published: April 2022

As we all know, it is difficult for traditional traffic models to deal with the phenomenon of “catastrophes” in traffic state and the traffic problem with incomplete information at the same time. Aiming at the traffic congestion, this paper firstly takes traffic volume as a state variable, speed, and density as control variables to establish the system potential function and theoretically clarifies that the structure of the traffic system has catastrophe characteristics. Secondly, combined with the grey characteristics of traffic system, we construct the grey catastrophe model for traffic system and obtain the traffic potential function with the system time as the state variable by substituting the variables of the model. Finally, the traffic stability is analyzed theoretically based on the potential function. In this paper, the rationality of the grey catastrophe model of traffic system is expounded theoretically, and the grey model theory is well expanded.