bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinical‐Like Cryotherapy in Acute Knee Arthritis Protects Neuromuscular Junctions of Quadriceps and Reduces Joint Inflammation in Mice
Authors: Castro Paula A. T. S. , Machanocker Dafiner H. , Luna Genoveva F. , Barbosa Germanna M. , Cunha Jonathan E. , Cunha Thiago M. , Cunha Fernando Q. , Russo Thiago L. , Salvini Tania F.
Published: January 2022

Rheumatoid arthritis is an autoimmune and inflammatory disease that affects synovial joint tissues and skeletal muscle. Clinical‐like cryotherapy benefits signs of joint inflammation in knee osteoarthritis after 60 days of anterior cruciate ligament transection surgery. However, it is unknown whether it also benefits acute knee arthritis (e.g., reduces inflammatory process and protects neuromuscular junction [NMJ] and muscle fibers). We aimed to analyze the effects of clinical‐like cryotherapy on NMJ and quadriceps muscle fibers in a model of acute knee arthritis. Twenty‐four male C57BL/6 mice (20 to 25 g) were randomly allocated into three groups: control (mice with no intervention), antigen‐induced arthritis (AIA; mice sensitized and immunized with intra‐articular [i.a.] injection of methylated bovine serum albumin [mBSA]), and AIA+cryotherapy (mice sensitized, immunized with i.a. injection of mBSA, and submitted to a clinical‐like cryotherapy protocol). Twenty‐one days after sensitization, arthritis was induced in immunized mice via i.a. injection of mBSA (100 μg/joint). Two clinical‐like cryotherapy sessions (crushed ice pack for 20 min) were applied two hours apart. The first session was applied immediately after i.a. injection of mBSA. The quadriceps was removed two hours after the second clinical‐like cryotherapy session for morphological analysis of muscle fibers (cross‐sectional area), frequency distribution of muscle fiber area (%), and NMJ (area, perimeter, and maximum diameter). Gene expressions of mRNA involved in NMJ signaling (γ‐nAChR, α1‐nAChR, ε‐nAChR, Agrin‐MusK‐Rapsyn, α‐dystrobrevin, and utrophin) and atrophy (muscle RING‐finger protein‐1 and Atrogin‐1) pathways were analyzed. Inflammatory signs were assessed in knee joint (swelling, articular surface temperature, and neutrophil migration in synovial fluid). Regarding morphological analysis of muscle fibers, 180 to 270 and >270 μm2 classes were higher in the AIA+cryotherapy than the AIA group. Area, perimeter, and maximum diameter of NMJ also increased in the AIA+cryotherapy compared with the control group. Agrin mRNA expression increased in the AIA+cryotherapy compared with the control and AIA groups. In the atrophy pathway, Atrogin‐1 increased compared with the control and AIA groups. The AIA+cryotherapy group reduced knee swelling and neutrophil migration compared with the AIA group. In conclusion, clinical‐like cryotherapy increased Agrin expression, contributing to NMJ maintenance and increased Atrogin‐1 expression, thus protecting NMJ and muscle fiber. Furthermore, clinical‐like cryotherapy reduced inflammatory signs (swelling and neutrophil migration) of acute knee arthritis.
Analysis of Rainfall Infiltration Stability of High Liquid Limit Red Clay Roadbed in Africa
Authors: Song Xiao , Li Hong
Published: January 2022

The annual rainfall in tropical rain forests in Africa is concentrated, and the abundant rainfall can easily lead to roadbed landslides. Therefore, it is necessary to analyze the impact of rainfall on the stability of roadbeds. This paper first uses the pore fluid permeability/stress coupling analysis step provided by ABAQUS to calculate the impact of rainfall infiltration on the overall stability of the roadbed slope and then discusses the rainfall infiltration on the slope seepage field, stress field, and displacement combined with the strength reduction method and the influence of field and safety factors. In the end, it is concluded that the 72-hour rainfall with an intensity of 50 mm/d will reduce the safety factor of the roadbed by 4.9% compared with before the rainfall. At the same time, it will increase the internal pore water pressure of the roadbed, reduce the suction of the matrix, and reduce the effective stress, which is caused by various factors. The overall stability of the roadbed is reduced.
Predicting death and confirmed cases of coronavirus
Authors: Abdulraheem Farqad Hamid , Al-Ridha Moatasem Yaseen , Al-Nima Raid Rafi Omar
Published: January 2022

At the end of 2019, a new virus called coronavirus has globally spread causing severe effections. In this paper, an artificial intelligence (AI) method is proposed to predict numbers of death and confirmed coronavirus cases. Efficient machine learning (ML) network named the byesian regularization backpropagation (BRB) is employed. It can estimates numbers of death and confirmed cases from applied population density and date. So, the BRB uses the population density, month and day as inputs, and predicts the new cases per million and new deaths per million as outputs. The network was trained and assessed by using a daily coronavirus recorded dataset known as the our world in data (OWID). The considered dates here are from the 31st of December 2019 to the 13th of October 2020. Furthermore, recorded information from countries over all world are employed. The obtained results provided a good promising performance with a testing mean absolute error (MAE) equal to 0.0218.
Inclusive bidirectional conversion system between Chittagonian and standard Bangla
Authors: Hossain Nahid , Milon Hafizur Rahman , Sabbir Sheikh Nasir Uddin , Inan Azfar
Published: January 2022

In recent years, the Bangla language has come out as a very prominent figure in the world of natural language processing. Many researchers have produced exemplary works on the language, but there has not been any notable work on its highly enriched dialects due to the lack of resources and the diversity and complexity in its grammatical structure. This paper has suggested a bidirectional conversion system for one of the most widely used dialects of Bangla; the Chittagonian dialect. Our method employs a bidirectional lexicon that uses binary search, word-to-word mapping, and morphological transformations. The system has achieved an accuracy rate of 95.86% for Chittagonian to standard Bangla and 93.89% in the case of standard Bangla to Chittagonian. We have also provided an efficient word suggestion module, and it has yielded satisfactory results.
Deployment of e-services based contextual smart agro system using internet of things
Authors: Sattar Abdus , Shampod Yeasin Arafat , Ahmed Md. Tanjid , Akter Nasrin , Mahmud Arif
Published: January 2022

Climate change's effects are becoming more apparent, and farmers are bearing the brunt of the consequences. As a result, by 2050, food production is expected to decline by 18%. Therefore, the study's goal is to develop effective and well-organized roadmap for context-based smart agricultural systems using a pre-determined ICT framework. Following that, this study offers a four-level conceptual framework for an e-services-based smart agro system utilizing internet of things (IoT). Here, each level optimizes the IoT infrastructure to accept e-services based on contextual information supplied by the e-services. Furthermore, the proposed ICTization process intends to broaden the role of ICT technology development. Besides, the system's views decrease misunderstandings about technology, growth, and connectivity while also enhancing raw data, administration, and service synchronization. Farmers, agricultural officers, and network operators, for example, are all included in the proposed roadmap, which includes omnipresent farm treatment services. Precision farming, on the other hand, need new knowledge and innovation in order to achieve an integrated and comprehensive approach to technology.
Development of hi-rail vehicle driven on metre-gauge railway/road in Thailand
Authors: Sukontanakarn Viroch , Sroymuk Paanthong , Pongsatitpat Boonlit
Published: January 2022

This research aims to develop a pickup truck to become a hi-rail vehicle that runs on meter gauge railways in Thailand. It is intended to be used for rails maintenance or response times during train derailments and for accessing inaccessible areas via rails in emergency situations. A hi-rail vehicle can travel both on rails and roads. The guide train steel wheels set is designed to have steel wheels running on rails with the vehicle being raised above the rails using a programmable logic controller for hydraulic cylinders. The results of the road test can run at a normal speed of not more than 90 kilometers per hour. The results of the test run on the rails can run at speed of not more than 30 kilometers per hour. There is a vibration of the hi-rail vehicle due to the designed guide train steel wheels set mechanism that can be accepted.
A novel five-level voltage source inverter interconnected to grid with srf controller for voltage synchronization
Authors: Sirisha Bogimi , Nazeemuddin Mohd Abdul
Published: January 2022

Power utilization from renewable sources with efficient modules is very vital. Maitaining harmonics below specific standard during grid interconnection is also a major objective. A novel five-level voltage source inverter which is controlled by synchronous reference frame (SRF) controller for grid interconnection and synchronized power injection. The input of the converter is integrated with renewable energy source photovoltaic arrays (PVA) for the injection of renewable power into the grid. For constant voltage input, the PVAs are connected to a booster converter controlled by the maximum power point tracking (MPPT) algorithm. The design is analyzed with different operating conditions by changing the load type (static and dynamic) using MATLAB/Simulink software. Graphical comparisons are taken for the analysis with the help of ‘powergui’ toolbox available in the software.
Ide-cabe: chili varieties identification and classification system based leaf
Authors: Suwarningsih Wiwin , Khotimah Purnomo Husnul , Rozie Andri Fachrur , Arisal Andria , Riswantini Dianadewi , Nugraheni Ekasari , Munandar Devi , Kirana Rinda
Published: January 2022

Identifying good quality chili varieties can be done by observing their leaves. It is required for seed testing and certification processes. Currently, a manual leaf identification method is used in which human experts inspect a wide range of leaves every one to two months. An automatic method could increase the identification process. Deep learning has proven to be a prominent method for image classification. We investigate the performance of deep CNN models, as: AlexNet, VGG16, Inception-v3 and DenseNet-121; to classify chili variety. In this paper, we took images of leaves aged 10 days. A preprocessing strategy was taken to enrich the dataset and to boost the classification performance and to assess the proposed models’ quality. From this study, we acquired 12 classes of chili leaves dataset. We acquired performance accuracy ranging from 70.18% to 78.37%. Further, the classification results by DenseNet-121 obtained the highest accuracy of 78.37% and recall of 74.83%. The classifiers investigated in this study perform well despite the relatively small number of our dataset. These results encourage the application of such an approach in practice.
Metaheuristics algorithms to identify nonlinear Hammerstein model: a decade survey
Authors: Jui Julakha Jahan , Ahmad Mohd Ashraf , Rashid Muhammad Ikram Mohd
Published: January 2022

Metaheuristics have been acknowledged as an effective solution for many difficult issues related to optimization. The metaheuristics, especially swarm’s intelligence and evolutionary computing algorithms, have gained popularity within a short time over the past two decades. Various metaheuristics algorithms are being introduced on an annual basis and applications that are more new are gradually being discovered. This paper presents a survey for the years 2011-2021 on multiple metaheuristics algorithms, particularly swarm and evolutionary algorithms, to identify a nonlinear block-oriented model called the Hammerstein model, mainly because such model has garnered much interest amidst researchers to identify nonlinear systems. Besides introducing a complete survey on the various population-based algorithms to identify the Hammerstein model, this paper also investigated some empirically verified actual process plants results. As such, this article serves as a guideline on the fundamentals of identifying nonlinear block-oriented models for new practitioners, apart from presenting a comprehensive summary of cutting-edge trends within the context of this topic area.
Colorectal multi-class image classification using deep learning models
Authors: Naga Raju Mallela Siva , Rao Battula Srinivasa
Published: January 2022

Colorectal image classification is a novel application area in medical image processing. Colorectal images are one of the most prevalent malignant tumour disease type in the world. However, due to the complexity of histopathological imaging, the most accurate and effective classification still needs to be addressed. In this work we proposed a novel architecture of convolution neural network with deep learning models for the multiclass classification of histopathology images. We achieved the findings using three deep learning models, including the vgg16 with 96.16% and a modified version of Resnet50 with 97.08%, however the proposed Adaptive Resnet152 model generated the best accuracy of 98.38%. The colorectal image multiclass dataset is publicly available which has 5000 images with 8 classes. In this study we have increased all classes equally, total 15000 images have been generated using image augmentation technique. This dataset consists of 60% training images and 40% testing images. The suggested method in this paper produced better results than the existing histopathology image categorization methods with the lowest error rate. For histopathological image categorization, it is a straightforward, effective, and efficient method. We were able to attain state-of-the-art outcomes by efficiently utilizing the resourced dataset.
Considering the κ − µ fading channels adopted in multiple antennas downlink non-orthogonal multiple access
Authors: Le Chi- Bao , Nguyen Hong- Nhu , Nguyen Ngoc- Long , Voznak Miroslav , Nguyen Nhan Duc
Published: January 2022

Massive connectivity and effective spectrum usage have become more important as the use of wireless communication devices and networks has grown dramatically. The approach of non-orthogonal multiple access (NOMA) is advocated as a viable solution for meeting consumers’ current needs. The signals are overlaid with various power levels for each user in a NOMA-assisted system, and then broadcast to the receiver. SIC (successive interference cancellation) is used by the receiver to discriminate and get the needed signal. Until far, most studies have concentrated on SIC with ideal features, with only a handful focusing on SIC with imperfect qualities (ipSIC). While the perfect SIC (pSIC) represents the ideal condition of no data loss and no external sounds, the ipSIC represents data transfer in a real-time context. In this research, we will assess the system performance metrics of the investigated NOMA system in the presence of ipSIC and compare them to the performance of the same user’s pSIC. We define channels as κ−µ fading distributions, which is more essential. For two destinations, we construct accurate outage probability formulas. Meanwhile, Monte-Carlo simulations are run to ensure that the mathematical expressions derived are genuine.
Comparative characterization of microstrip patch antenna array with defected ground structure for biomedical application
Authors: Santhanam Suganthi , Palavesam Thiruvalar Selvan
Published: January 2022

In this paper, microstrip dual band antenna array with defected ground structure has been proposed for low frequency wearable on-body applications. The array has been simulated with Cotton, Polyimide, Polyester and Teflon (PTFE) flexible materials which are mostly used for biomedical applications. The performance of 2x2 trapezoidal patch array with partial ground, thin slot defection at center has been studied in terms of return loss, VSWR, power handling capability, radiation pattern and surface current distribution. All substrates exhibits acceptable fractional bandwidth below -10 dB and Cotton proves its superiority than other substrates with -20 dB and -48 dB return loss with 16.12% and 7.73% bandwidth at 1.24 GHz and 1.94 GHz respectively. The proper matching of array has been proved with VSWR value below 1.3 for all substrates. The observation of input port impedance shows that, Cotton array has good impedance matching nearly to 50 Ω and PTFE array has 100 Ω poor impedance matching. The proposed four flexible array exhibit omnidirectional pattern in H plane with 1.43 dBi gain and bidirectional pattern in E plane with 1.4 dBi gain which are support for ideal fitness of proposed flexible material array for medical applications.
Comparison of classifiers using robust features for depression detection on Bahasa Malaysia speech
Authors: Nik Hashim Nik Nur Wahidah , Basri Nadzirah Ahmad , Ahmad Ezzi Mugahed Al-Ezzi , Nik Hashim Nik Mohd Hazrul
Published: January 2022

Early detection of depression allows rapid intervention and reduce the escalation of the disorder. Conventional method requires patient to seek diagnosis and treatment by visiting a trained clinician. Bio-sensors technology such as automatic depression detection using speech can be used to assist early diagnosis for detecting remotely those who are at risk. In this research, we focus on detecting depression using Bahasa Malaysia language using speech signals that are recorded remotely via subject’s personal mobile devices. Speech recordings from a total of 43 depressed subjects and 47 healthy subjects were gathered via online platform with diagnosis validation according to the Malay beck depression inventory II (Malay BDI-II), patient health questionnaire (PHQ-9) and subject’s declaration of major depressive disorder (MDD) diagnosis by a trained clinician. Classifier models were compared using time-based and spectrum-based microphone independent feature set with hyperparameter tuning. Random forest performed best for male reading speech with 73% accuracy while support vector machine performed best on both male spontaneous speech and female reading speech with 74% and 73% accuracy, respectively. Automatic depression detection on Bahasa Malaysia language has shown to be promising using machine learning and microphone independent features but larger database is necessary for further validation and improving performance.
Model optimisation of class imbalanced learning using ensemble classifier on over-sampling data
Authors: Kurniawati Yulia Ery , Prabowo Yulius Denny
Published: January 2022

Data imbalance is one of the problems in the application of machine learning and data mining. Often this data imbalance occurs in the most essential and needed case entities. Two approaches to overcome this problem are the data level approach and the algorithm approach. This study aims to get the best model using the pap smear dataset that combined data levels with an algorithmic approach to solve data imbalanced. The laboratory data mostly have few data and imbalance. Almost in every case, the minor entities are the most important and needed. Over-sampling as a data level approach used in this study is the synthetic minority oversampling technique-nominal (SMOTE-N) and adaptive synthetic-nominal (ADASYN-N) algorithms. The algorithm approach used in this study is the ensemble classifier using AdaBoost and bagging with the classification and regression tree (CART) as learner-based. The best model obtained from the experimental results in accuracy, precision, recall, and f-measure using ADASYN-N and AdaBoost-CART.
An efficient resource utilization technique for scheduling scientific workload in cloud computing environment
Authors: Sodinapalli Nagendra Prasad , Kulkarni Subhash , Sharief Nawaz Ahmed , Venkatareddy Prasanth
Published: January 2022

Recently, number of data intensive workflow have been generated with growth of internet of things (IoT’s) technologies. Heterogeneous cloud framework has been emphasized by existing methodologies for executing these data-intensive workflows. Efficient resource scheduling plays a very important role provisioning workload execution on Heterogeneous cloud framework. Building tradeoff model in meeting energy constraint and workload task deadline requirement is challenging. Recently, number of multi-objective-based workload scheduling aimed at minimizing power budget and meeting task deadline constraint. However, these models induce significant overhead when demand and number of processing core increases. For addressing research problem here, the workload is modelled by considering each sub-task require dynamic memory, cache, accessible slots, execution time, and I/O access requirement. Thus, for utilizing resource more efficiently better cache resource management is needed. Here efficient resource utilization (ERU) model is presented. The ERU model is designed to utilize cache resource more efficiently and reduce last level cache failure and meeting workload task deadline prerequisite. The ERU model is very efficient when compared with standard resource management methodology in terms of reducing execution time, power consumption, and energy consumption for execution scientific workloads on heterogeneous cloud platform.
AraBERT transformer model for Arabic comments and reviews analysis
Authors: EL Moubtahij Hicham , Abdelali Hajar , Tazi El Bachir
Published: January 2022

Arabic language is rich and complex in terms of word morphology compared to other Latin languages. Recently, natural language processing (NLP) field emerges with many researches targeting Arabic language understanding (ALU). In this context, this work presents our developed approach based on the Arabic bidirectional encoder representations from transformers (AraBERT) model where the main required steps are presented in detail. We started by the input text pre-processing, which is, then, segmented using the Farasa segmentation technique. In the next step, the AraBERT model is implemented with the pertinent parameters. The performance of our approach has been evaluated using the ARev dataset which contains more than 40,000 comments-remarks records relate to the tourism sector such as hotel reviews, restaurant reviews and others. Moreover, the obtained results are deeply compared with other relevant states of the art methods, and it shows the competitiveness of our approach that gives important results that can serve as a guide for further improvements in this field.
Fingerprint recognition based on collected images using deep learning technology
Authors: Yaseen Althabhawee Ali Fadhil , Chabor Alwawi Bashra Kadhim Oleiwi
Published: January 2022

The fingerprint identification is the most widely used authentication system. The fingerprint uniqueness for each human being provides error-free identification. However, during the scanning process of the fingerprint, the generated image using the fingerprint scanner may differ slightly during each scan. This paper proposes an efficient matching model for fingerprint authentication using deep learning based deep convolutional neural network (CNN or ConvNet). The proposed deep CNN consists of fifteen layers and is classified into two stages. The first stage is preparation stage which includes the fingerprint images collection, augmentation and pre-processing steps, while the second stage is the features extraction and matching stage. Regarding the implantation results, the proposed system provided the best matching for the given fingerprint features. The obtained training accuracy of the proposed model is 100% for training dataset and 100% for validating dataset.
Evolução do consumo de alimentos fora do domicílio no Brasil de 2008–2009 a 2017–2018
Authors: Bezerra Ilana Nogueira , Vasconcelos Thaís M , Cavalcante Jessica Brito , Yokoo Edna Massae , Pereira Rosângela A , Sichieri Rosely
Published: January 2022

OBJETIVO Descrever a evolução do consumo de alimentos fora do domicílio no Brasil no período 2008–2018. MÉTODOS Foram usados dados dos Inquéritos Nacionais de Alimentação (INA) de 2008–2009 e 2017–2018, realizados com 34.003 e 46.164 indivíduos, respectivamente, para estimar a frequência de consumo de alimentos fora de casa e a contribuição desse consumo para alimentos específicos. O consumo de alimentos foi investigado por meio de registros alimentares no INA 2008–2009 e de recordatórios 24 horas em 2017–2018. As estimativas foram geradas para o Brasil como um todo, para áreas urbana e rural, para faixas de idade (adolescente, adulto, idoso) e para faixas de renda. RESULTADOS A frequência de consumo fora de casa diminuiu 8,8% entre os dois inquéritos, sem alteração na área rural, nas regiões Nordeste e Sul e nas menores faixas de renda. Houve leve aumento entre idosos e na região Centro-Oeste. De modo geral, a contribuição do consumo alimentar fora de casa para a ingestão diária de energia também diminuiu (16,3% vs. 12,7%), com exceção da área rural, onde houve redução da diferença em relação à área urbana entre os dois inquéritos. O consumo de alimentos fora de casa foi reduzido para a maioria dos itens avaliados. Os alimentos mais consumidos fora de casa em ambos os inquéritos foram as bebidas alcoólicas, salgadinhos fritos e assados, refrigerantes, pizzas, doces e sanduíches. CONCLUSÃO Em 10 anos, a prevalência de consumo de alimentos e o percentual de contribuição dos alimentos consumidos fora de casa diminuíram no Brasil, mas os alimentos ultraprocessados ainda figuram como o grupo de alimento mais consumido fora de casa.
A New Style of Working: Imposed Teleworking in the Context of the covid-19 Pandemic
Authors: Yildirim Galip Emre
Published: January 2022

In the context of the covid-19 pandemic, teleworking has largely become a useful model of work for many employees, managers and employers. This new style of working can be easily distinguished from traditional telework habits, especially by its imposed character. For this reason, this paper attempts to develop the term “imposed telework,” which has deeply changed the established habitual routines of employees who have never or rarely ever engaged in telework, in order to test the possibility of quasi-permanent teleworking instead of the full-time office-bound work style. Therefore, a generalization of a quasi-permanent teleworking method would be that it is a new, more environmentally-compatible professional mode; however, are employees ready for such change? This research, comprising 73 participants from France, Italy, and Turkey, clearly showed that it is too soon to generalize such a new professional model, owing to the difficulties that the participants faced, such as isolation, absenteeism, work/life conflicts, etc., even if their productivity increment was recorded.
US college women’s understandings of definitions of intimate partner violence
Authors: Rich Rebecca , Evans Jennifer L. , Klimek Sally , Wilson Lucy
Published: January 2022

Objective:

Past research suggests students have differing definitions of sexual assault, violence and intimate partner violence (IPV). To adequately develop violence prevention efforts, it is important to examine how college students understand these terms and associated behaviours. The purpose of this study was to identify which behaviours are categorised as IPV by college women and whether there are any ‘grey areas’ when it comes to IPV.

Design:

A three-phase e-Delphi study was conducted with US college women to reach consensus on the behaviours commonly associated with IPV.

Setting:

The study was conducted in one large, Southeastern USA university.

Method:

In a first phase of work, participants answered open-ended questions about the behaviours they associated with IPV and related terms. In phase 2, participants categorised the behaviours identified in phase 1. In phase 3, consensus was reached by the 12 women who completed all three phases of work.

Results:

Women agreed on a list of 45 behaviours that constitute IPV as well as behaviours that fall into a ‘grey area’, with many of the latter occurring between boyfriends/girlfriends.

Conclusion:

Findings from the study contribute to the current knowledge base concerning IPV among US college students and their understanding of which behaviours are acceptable by intimate partners and which are not. Future research is needed with a larger more representative sample to extend the current findings. However, interim findings can be used to drive future research and may provide some insight into current student perceptions of IPV.
A Cross-Cultural Investigation of Basic Psychological Need Satisfaction at Work in an Indigenous and Non-Indigenous Australian Sample Across Occupation Types
Authors: Magson Natasha R. , Craven Rhonda G. , Ryan Richard M. , Dillon Anthony , Mooney Janet , Blacklock Fabri , Yeung Alexander S. , Kadir Munirah S. , Franklin Alicia
Published: January 2022

Self-determination theory (SDT) posits universality without cross-cultural uniformity of the three basic psychological needs (autonomy, competence, and relatedness) which have been associated with desirable job outcomes. Yet these promising directions in theory and research have not been extended to Indigenous samples and different occupational types. This is unfortunate as Indigenous peoples globally remain the most disadvantaged on all socio-economic indicators, including employment. This study adopted a strengths-based approach to investigating associations between SDT’s need satisfaction and job outcomes in Australian Indigenous and non-Indigenous professionals and non-professionals. Participants included 1,146 Indigenous (48.8%) and non-Indigenous Australians (39.1% men), aged 18 to 81 years ( Mage = 43.54). Structural equation modeling (SEM) revealed that autonomy and competence need satisfaction were associated with multiple positive work outcomes and less job ambiguity, whereas satisfaction of the need for relatedness was associated with increased job satisfaction and greater resilience in the workplace. Moderation by Indigenous status and occupation type revealed few differences in the direction and strength of the associations between need satisfaction and job outcomes. However, non-professionals reported significantly lower satisfaction of all three needs, and Indigenous participants reported significantly lower levels of autonomy need satisfaction. As need satisfaction was shown to be equally beneficial for all workers regardless of culture or occupation type, these findings highlight the need for employers to invest more in cultivating the need satisfaction of their Indigenous and non-professional staff. Overall, the results extend upon previous research by demonstrating that SDT is generalizable to an Australian Indigenous population and that workplace need satisfaction is important for Indigenous and non-professional employee outcomes.
Does Sharing Memories Make Us Feel Closer? The Roles of Memory Type and Culture
Authors: Guan Li , Wang Qi
Published: January 2022

The present research examined the effects of sharing different types of memories on perceived relationship closeness and how that is related to psychological well-being in a cross-cultural context. In two studies, European American and Asian participants (total N = 714) reported their feelings of closeness to a conversation partner in hypothetical situations that involved five types of information sharing: specific and general autobiographical memories, specific and general vicarious memories, and non-person information. Sharing memories led to greater feelings of closeness than sharing non-person information in both groups. Asians felt closer to the conversation partner than European Americans across all types of information sharing. Sharing autobiographical and specific memories led to greater closeness than sharing vicarious and general memories in both groups, although sharing specific autobiographical memories appeared most effective for relationship closeness for European Americans. Perceived relationship closeness following conversational exchanges was positively associated with psychological well-being across cultures.
Analytical Nonlinear Modeling of Rail and Fastener Longitudinal Response
Authors: Dersch Marcus S. , Silva Matheus Trizotto , Edwards J. Riley , de Oliveira Lima Arthur
Published: January 2022

Comparatively little attention has been given to the quantification of fastener demands, especially in the longitudinal direction. Research quantifying fastener demands is justified by the more than 250 FRA reportable derailments on mainlines and sidings in the United States caused by “defective or missing spikes or rail fasteners” over the last 20 years. Failed fasteners are rarely caused by loads acting from a single direction (vertical, lateral, or longitudinal); they occur from a combination of these loads. A literature review identified that though multiple models have been developed for analyzing track, they were not designed to quantify fastener demands, especially those in the longitudinal direction, and some make assumptions that could be improved on based on more recent research into the mechanics of fastening system behavior. This paper advances the mechanistic–empirical (M-E) track analysis and design approach through the development, validation, and application of a 3D nonlinear parametric track model that quantifies longitudinal fastener demands. Key research findings include: bilinear approximations, in combination with considering the interaction between vertical loads and slip, were necessary to accurately quantify fastener forces; ballast and fastener stiffness had a direct logarithmic relationship on fastener load; and for well-supported sleepers, changes in component resistance to slip produced minimal changes in fastener demands because the vertical applied load increased the required load to produce slip. Going forward, this validated model could be used to quantify fastener and track demands for additional loading and operational scenarios to further optimize component design for improved track safety and reliability.
Exploring the relationship between systemic lupus erythematosus and osteoporosis based on bioinformatics
Authors: Han Jie , Ren Guowu , Xu Zhiwei , Qi Wen , Shang Yuzhi , Wen Shuaibo , Luo Yehao
Published: January 2022

Objective

This study aimed to explore the relationship between systemic lupus erythematosus (SLE) and osteoporosis (OP) based on bioinformatics.

Methods

The expression profiles of SLE and OP gene chips were searched through the GEO database, and the differentially expressed genes (DEGs) were screened out to obtain the intersection. Then, the Funrich software was used to predict the upstream miRNAs of the intersection genes, and the miRNA–mRNA relationship network was constructed. Afterward, the String database and Cytoscape software were used to construct the protein interaction network of the intersection genes to screen out the key genes. Finally, the functions and related pathways of key genes were analyzed by using the DAVID database.

Results

①A total of 140 intersection genes of SLE and OP were obtained; ②There were 217 miRNAs regulating the intersection genes; ③IL-4, FOS, TLR1, TLR6, CD40LG, CCR1 were the key genes in the protein interaction network; ④The DAVID enrichment analysis mainly covered the positive regulation of cytokine production, the regulation of osteoclast differentiation, macrophage activation and other biological processes, involving Toll-like receptor signaling pathway, T cell receptor signaling pathway, Th1, Th2, and Th17 cells Differentiation, IL-17 signaling pathway.

Conclusions

SLE and OP still have some highly overlapping differential gene expressions under the background of complex gene networks. The gene functions and signaling pathways involved can simultaneously regulate the two diseases, suggesting that there is a close relationship between the molecular mechanisms of the two diseases, and that it may be a target of drugs that interfere with two diseases at the same time.
Societal Costs and Outcomes of Medical and Recreational Marijuana Policies in the United States: A Systematic Review
Authors: French Michael T. , Zukerberg Julia , Lewandowski Tara E. , Piccolo Katrina B. , Mortensen Karoline
Published: January 2022

Significant support exists in the United States for legalization of marijuana/cannabis. As of 2021, 36 states and four territories approved the legalization of medical cannabis via medical marijuana laws (MMLs), and 15 states and District of Columbia (DC) have adopted recreational marijuana laws (RMLs). We performed structured and systematic searches of articles published from 2010 through September 2021. We assess the literature pertaining to adolescent marijuana use; opioid use and opioid-related outcomes; alcohol use; tobacco use; illicit and other drug use; marijuana growing and cultivation; employment, earnings, and other workplace outcomes; academic achievement and performance; criminal activity; perceived harmfulness; traffic and road safety; and suicide and sexual activity. Overall, 113 articles satisfied our inclusion criteria. Except for opioids, studies on use of other substances (illicit drugs, tobacco, and alcohol) were inconclusive. MMLs and RMLs do not generate negative outcomes in the labor market, lead to greater criminal activity, or reduce traffic and road safety.
Friendship quality among autistic and non-autistic (pre-) adolescents: Protective or risk factor for mental health?
Authors: O’Connor Rachel A.G. , van den Bedem Neeltje , Blijd-Hoogewys Els M.A. , Stockmann Lex , Rieffe Carolien
Published: January 2022

Autistic (pre-) adolescents are often misunderstood by their peers, which can lead to challenges within their friendships. Yet, friendships play an important role in our psychological wellbeing, whereby in the non-autistic population good quality friendships usually protect against mental health difficulties, whereas conflictual friendships increase the risk. The present study investigated positive and negative friendship quality in autistic and non-autistic (pre-) adolescents. Furthermore, the relations between positive friendship quality and negative friendship quality with anxiety and depressive symptoms were examined. Participants were 306 autistic and non-autistic (pre-) adolescents aged 9–16 ( M = 11.69 years; SD = 1.33 years). Our results demonstrated that autistic (pre-) adolescents reported lower positive friendship quality than their non-autistic peers, while no group or gender differences were observed for negative friendship quality than non-autistic boys. For the whole sample, positive friendship quality was associated with fewer depressive symptoms, while the opposite was true for negative friendship quality. For autistic girls only, higher positive friendship quality was related to more symptoms of anxiety. These outcomes seem to emphasize the need for supporting the friendships of autistic young people, perhaps by educating non-autistic young people around how to be supportive friends to their autistic peers.

Lay abstract

Autistic young people are often misunderstood by non-autistic young people, and this can lead to difficulties in their friendships. We know that friendship is very important for our mental health. For non-autistic young people, having good friendships is linked to better mental health and having problems in friendship can cause mental health problems. This study aimed to compare the positive and negative features of friendship that autistic non-autistic young people experience. The study also aimed to understand if having positive or negative friendship features is related to signs of mental health problems (anxiety and depression). 306 young people aged 9–16 took part in this study. These were 86 autistic boys, 18 autistic girls, 91 non-autistic boys and 111 non-autistic girls. The findings of this study showed that autistic young people have less positive friendship features than non-autistic young people. For all young people in the study, having more positive friendship features was related to fewer signs of depression, while having more negative friendship features was related to more signs of depression. Just for autistic girls, having more positive friendship features was related to more signs of anxiety. These findings show that support is needed to help autistic young people have more positive friendships. For example, by teaching non-autistic young people how to be supportive friends to their autistic peers.
‘We are merely furniture’: Palestinian actors and actresses react to rationalization and racialization processes in the Israeli TV market
Authors: Lavie Noa , Jamal Amal
Published: January 2022

This study aims to explore Palestinian-Israeli actors’ and actresses’ experiences in the Israeli TV market and their understanding of the rationalization/racialization processes taking place in the global television industry, which is dominated by Streaming Video On Demand platforms. The study is based on observations and interviews. The observations were conducted on the set of the internationally successful action drama Fauda during its second season. Fauda is a co-production of Netflix and the Israeli satellite conglomerate YES. It portrays the Palestinian-Israeli conflict in a way that some see as Zionist and hegemonic. The interviews were conducted with the Palestinian-Israeli actors and actresses. Our analysis of their experiences on the set of Fauda shows a dialectical and complex reality in which self-exploitation, which results in justifying playing terrorists and villains for the sake of money or art, resolves itself into an antithesis of subversion.
Needs of carers participating in support groups and caring for a person with dementia: A focused ethnographic study
Authors: Lauritzen Jette , Sørensen Erik E , Pedersen Preben U , Bjerrum Merete B
Published: January 2022

Aims

The aim is to explore and understand how support group participation meets carers’ perceived needs for information and social and emotional support when caring for a person with dementia who lives at home.

Design

Focused ethnographic design.

Methods

Participant observations and semi-structured interviews with 25 carers were conducted. An inductive content analysis of the data was performed.

Findings

Two themes were identified: “Strengthening the sense of self” and “Managing uncertain benefits.”

Conclusion

Carers’ level of information about dementia was partly met, thereby strengthening their sense of self and joy. Maintaining shared decision-making in financial matters was viewed as an expression of respect and reciprocity. Getting acquainted with peers and dementia coordinators was viewed as emotional and social support but was also used strategically to gain easier access to health care services. By fulfilling their needs, support group meetings became meaningful, which motivated carers to continue providing care.
On the use of Vibrational Hill Charts for improved condition monitoring and diagnosis of hydraulic turbines
Authors: Zhao Weiqiang , Presas Alexandre , Egusquiza Mònica , Valentín David , Egusquiza Eduard , Valero Carme
Published: January 2022

To cope with the intermittent power supply of the new renewable energies and demand fluctuations, Francis turbines are required to operate more and more in an extended operating range, far away from the design point. With this operating behavior, it is very complex to interpret the trend of vibration parameters typically used in Condition Monitoring and to define reasonable alarm and trip levels valid for all the operating range of the unit working in steady conditions. As in the efficiency curves of Francis turbines represented as a function of net head and load (Hill Chart), in this paper we propose to represent the most relevant vibration parameters in surfaces, called Vibrational Hill Charts, which allow a more accurate evaluation of the indicators and their trends and a better classification of abnormal values. To show the potential of Vibrational Hill Charts, a complete database obtained after 2 years of monitoring a large Francis Unit (444 MW rated power) has been used. The mapping of the relevant vibration parameters has been performed by means of Artificial Neural Networks. It is shown that by setting the action levels based on the resulting maps, rather than a constant value, a better diagnosis capacity is achieved as the Receiver Operating Characteristic will be improved. Furthermore, phenomena such as erosive cavitation, which is hard to be detected, could be also assessed with the use of multidimensional analysis based on the Vibrational Hill Chart. As a conclusion, with the Vibrational Hill Chart, the condition monitoring and diagnosis of hydraulic turbines could be improved.
Digital Mixed Content Analysis for the Study of Digital Platform Social Data: An Illustration from the Analysis of COVID-19 Risk Perception in the Italian Twittersphere
Authors: Punziano Gabriella , De Falco Ciro C. , Trezza Domenico
Published: January 2022

The explosion of platform social data as digital secondary data, collectable through sophisticated and automatized query systems or algorithms, makes it possible to accumulate huge amounts of dense and miscellaneous data. The challenge for social researchers becomes how to extract meaning and not only trends in a quantitative and in a qualitative manner. Through the application of a digital mixed content analysis design, we present the potentiality of a hybrid digitalized approach to social content applied to a very tricky question: the recognition of risk perception during the first phase of COVID-19 in the Italian Twittersphere. The contribution of our article to mixed methods research consists in the extension of the existing definitions of content analysis as a mixed approach by combining hermeneutic and automated procedures, and by creating a design model with vast application potential, especially when applied to the digital scenario.