bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative Effectiveness of Multiple Psychological Interventions for Psychological Crisis in People Affected by Coronavirus Disease 2019: A Bayesian Network Meta-Analysis
Authors: Yang Yang , Sun Shaodan , Hu Shaowen , Tang Chunzhi , Zhang Yimin , Lin Haibo 
Published: February 2021

Objective: The objective of our current research is to compare the different psychological interventions and distinguish the most effective way to treat psychological crisis according to different clinical manifestations in people affected by coronavirus disease 2019 (COVID-19). No previous systematic review has provided a comprehensive overview by performing a Bayesian network meta-analysis of this current topic.Method: A systematic review and a Bayesian network meta-analysis were conducted on randomized controlled trials (RCTs), non-RCTs, case–control studies, self-controlled case series (SCCS), cohort studies, and cross-sectional studies of all the available interventions for psychological crisis in people affected by COVID-19. We searched the electronic databases EMBASE, PubMed, Web of Science, PsycINFO, and Cochrane Library, as well as the Chinese databases such as Sinomed, Chinese Biomedicine Literature (CBM), Chinese Scientific Journal Database (VIP), WanFang Database, and China National Knowledge Infrastructure (CNKI), from 2019 to April 30, 2020. The main outcomes were self-rating anxiety scale (SAS), self-rating depression scale (SDS), patient health questionnaire (PHQ-9), and symptom checklist (SCL-90). The study is registered with Inplasy, number 202050076.Result: Sixteen self-controlled case series (SCCS) comprising 1,147 participants compared five different psychological interventions with four different measurement scales were included in this study. For effectiveness, all the psychological therapies were significantly more effective than before intervention. Our results showed that supportive therapy (ST), which is adjusted to the COVID-19-related mental crisis, is the best treatment compared with behavioral therapy (BT), nursing-based psychological therapy (NBPT), traditional Chinese medicine therapy (TCMT), and COVID-19-related standard training (CRST) at reducing the anxiety-related symptoms assessed by SAS. When measured by SDS, BT was better than ST and NBPT treatment for reducing the depression symptoms. And ST was better than BT and ST+BT as assessed by PHQ-9. In the end, the last network meta-analysis indicated that NBPT was more effective than ST by the measurement of SCL-90.Conclusion: Our research suggested the potential effectiveness of psychological interventions for decreasing psychological crisis in people affected by COVID-19 and try to introduce the best effective treatment options for clinical practice according to the clinical manifestations of psychological problems, but further confirmation from high-quality RCTs is needed.
Spouse-Appraised Memory Functioning Predicts Memory Decline Better Than Subjective Memory Complaints in Community Dwelling Older Adults at Genetic Risk for Alzheimer's Disease
Authors: Bellaali Youssef , Woodard John L. , Hanseeuw Bernard , Ivanoiu Adrian 
Published: February 2021

Objective: Alzheimer's disease (AD) begins with subtle memory decline, years before dementia onset. The presence of subjective memory complaints (SMC) has been proposed as a marker of preclinical AD. However, recent evidence has demonstrated early and progressive loss of awareness of memory difficulties in non-demented older adults harboring AD pathology. We investigated the respective contributions of SMC and spouse-appraised memory functioning (SAM) to predict memory decline in a large cohort of community dwelling older adults.Methods: The Wisconsin Longitudinal Study collected cognitive data from a community-based cohort of 3,583 participants in both 2005 and 2011. The participant and the participant's spouse were each asked to rate the participant's memory functioning using a Likert scale. We predicted change in objective episodic memory with models including baseline SMC, baseline SAM, or both SMC and SAM. We also evaluated an awareness index (SMC minus SAM). We then tested the interaction between Apolipoprotein E (APOE ε4) carrier status and SMC/SAM to evaluate whether the effects were driven by individuals at-risk for AD pathology.Results: In separate models, SMC (−0.081 ± 0.036, p = 0.025) and SAM (−0.084 ± 0.278, p = 0.003) were both associated with memory decline over ~6 years. However, the AI was not significantly associated with memory decline (0.031 ± 0.024, p = 0.19). When both predictors were included in the same model, SAM (−0.074 ± 0.03, p = 0.0092) was associated with memory decline, while SMC was not significant (−0.061 ± 0.04, p = 0.99). The association between SAM and memory decline was stronger in the APOE ε4 carriers than in the non-carriers (APOE-by-SAM interaction: F = 6.07; p = 0.002), and follow up analyses revealed that SAM was particularly predictive of decline only for APOE ε4 carriers. The association between SMC and memory decline was independent of APOE ε4 carrier status (APOE-by-SMC interaction: F = 2.29; p = 0.13).Conclusions: Spouse-appraised memory functioning was more predictive of memory decline than SMC or an awareness index, particularly in APOE ε4 carriers, who are at increased risk for AD pathology.
Modèles et expériences autogestionnaires au Japon
Authors: Ishikawa Akihiro 
Published: February 2021

Podemos distinguir hoy dia 4 modelos de autogestion en Japon, en función de la génesis de cada esperiencia : las pequeñas y medianas empresas recuperadas y administradas por los sindicatos o bajo forma de cooperativas despuès de un a declaración de quiebra, las pequenas y medianas empresas en las que los propietarios capitalistas -en periódos de crecimiento económico favorable - han acordado a los trabajadores ciertos derechos de autogestion, en vista de aumentar la productividad, de estabilizar la mano de obra, etc... ; las actividades de pequenos grupos ubicados a nisei de talleres en las grandes empresas, para aumentar la rentabilidad y mejorar la gestion del personal bajo el control de la dirección y de la jerarquia ; las comunidades « utópicas », agricolas y otras inspiradas por ciertas tendencias religiosas y beneficiando de una tradición antigua.
El articulo estudia cada una de estas experiencias analizando las condiciones internas y externas de su desarrollo.
Penyelesaian Sengketa Konsumen Dalam Perjanjian Jual Beli Terhadap Pelaku Usaha Yang Tidak Beritikad Baik
Authors: Ruslan Milawartati T 
Published: February 2021

Tujuan penelitian ini, yaitu untuk mengetahui dan menganalisis konsep hukum dalam perjanjian jual beli dan untuk menganalisis upaya hukum penyelesaian sengketa konsumen dalam perjanjian jual beli dari tindakan pelaku usaha yang tidak beritikad baik. Permasalahan yang diteliti pada penelitian ini yaitu, bagaimanakah konsep hukum dalam perjanjian jual beli dan bagaimanakah upaya hukum penyelesaian sengketa konsumen dalam perjanjian jual beli dari tindakan pelaku usaha yang tidak beritikad baik? Metode penelitian ini yaitu normatif yang bersumber dari bahan hukum primer, bahan hukum sekunder, dan bahan hukum tersier. Kesimpulan: upaya hukum penyelesaian sengketa konsumen dalam perjanjian jual beli dari tindakan pelaku usaha yang tidak beritikad baik didasarkan pada upaya hukum yang dapat dilakukan oleh konsumen atas kerugian yang dialami yaitu dengan memberikan ruang untuk menyelesaikan sengketa konsumen yaitu melalui litigasi (pengadilan) dan nonlitigasi (diluar pengadilan). Hal ini dapat ditinjau dari aspek hukum perdata, hukum pidana, dan hukum administrasi Negara.
The purpose of this research is to find out and analyze legal concepts in the sale and purchase agreement and to analyze the legal efforts of consumer dispute resolution in the sale and purchase agreement of the actions of business actors who are not in good faith. The problems examined in this study are, how is the legal concept in the sale and purchase agreement and how are the legal efforts to resolve consumer disputes in the sale and purchase agreement of the actions of business actors who are not in good faith? This research method is normative which comes from primary legal materials, secondary legal materials, and tertiary legal materials. Conclusion: consumer dispute resolution efforts in the sale and purchase agreement of the actions of business actors who do not have good intentions are based on legal remedies that can be carried out by consumers for the losses experienced by providing space to resolve consumer disputes namely through litigation (court) and nonlitigation court). This can be viewed from aspects of civil law, criminal law, and state administrative law.
Ketentuan Hukum Perbandingan sistem Pengawasan Terhadap Anggota Lembaga Parlemen Dibeberapa negara
Authors: Patawari Patawari , Bidja Isnanto 
Published: February 2021

Pelaksanaan tugas dan fungsinya anggota parlemen, diperlukan adanya ketentuan pengawasan terhada anggota pada lembaga parlemen, sehingga di dalam menjalankan fungsinya maka anggota DPR berkesesuaian antara perencanaan, tugas dan fungsinya, dan tujuan yang hendak dicapai. Maka tentunya pengawas tersebut adalah memiliki kompetensi yang cukup untuk memahami tugas dan fungsi anggota DPR (yang diawasi). Paling tidak, sebagai pengawas lebih memahami dari pada tugas dan fungsi anggota DPR, hal tersebut yang dimaksud dengan kompetensi. Sedangkan kompetensi dapat tercipta dari proses akademik, pengalaman dan suatu kewenangan yang diberikan. Anggota dalam lembaga Parlemen, merupakan orang orang yang direkrut oleh partai politik untuk menjadi anggota parlemen, melalui proses seleksi sosial (konstituen) yang dipilih melalui pemilihan umum, hingga terpilih dan diberikan tugas dan fungsinya dan bekerja secara kolektifitas dengan ketentuan, yang memegang kekuasaan dalam pementukan perundang undangan, melakukan pengawasan dan melaksanakan fungsi budgeting.
The implementation of the duties and functions of parliamentarians requires the provision of oversight to members of parliamentary institutions, so that in carrying out their functions the members of the House of Representatives agree between their planning, duties and functions, and the objectives to be achieved. Then of course these supervisors have sufficient competence to understand the duties and functions of DPR members (supervised). At the very least, as supervisors understand better than the duties and functions of DPR members, this is meant by competence. While competence can be created from the academic process, experience and a given authority. Members in the Parliamentary institution, are people who are recruited by political parties to become members of parliament, through a process of social selection (constituents) elected through general elections, to be elected and given their duties and functions and work collectively with the provisions, who hold power in the formation legislation, supervise and carry out the budgeting function.
Implementasi Sistem Merit Dalam Manajemen Aparatur Sipil Negara Kementerian Agama Sulawesi Selatan
Authors: Sefullah Andi , Fahmal A Muin , Said Muhammad Fachri 
Published: February 2021

Undang-undang No.5 Tahun 2014 tentang Aparatur Sipil Negara (ASN) merupakan wujud dari kelanjutan pelaksanaan Reformasi Birokrasi, menuju profesionalisme pegawai. Merit sistem merupakan cerminan manajemen kepegawaian yang profesional dimana penempatan pegawai dan pejabat menggunakan kompetensi kinerja dan track record sebagai alat ukur pengangkatan Tujuan penelitian ini untuk mengevaluasi implementasi sistem merit dalam Manajemen ASN pada Kantor Wilayah Kementerian Agama Prov. Sulawesi Selatan dan melihat faktor-faktor yang mempengaruhi implementasi sitem tersebut. Penelitian ini merupakan penelitian normatif empiris dengan menggunakan pendekatan kualitatif dengan tujuan mengetahui bagaimana implementasi sistem merit dalam manajemen ASN serta faktor-faktor yang mempengaruhi implementasi tersebut. Sehingga diharapkan dapat memberikan sumbangan pemikiran terhadap pemerintah dalam pengkajian dan pelaksanaan sistem merit kearah yang lebih baik.
The implementation of the Act Number 5, Year 2014 on The Civil State Apparatus is entity of a sustainable successful implementation of bureaucracy reform head to officers professionalism. The Merit System is a reflection of professional staffing management. The merit system is performance assessment based on work performance. The purpose of this research is to evaluate the implementation of merit system to officers development according to the needs of South Celebes Regional Office the Ministry of Religions and the factors affecting of its implementations. It is a normatif-empiric method with qualitative approach. It is hoped to describe the implementation of merit system in civil state management and and the factors affecting of its implementations. So that it is expected to contribute ideas to the government in the study and implementation of a better Merit System.
Analisis Numerik Part Bulkhead Pada Sub System Wing To Fuselage Joinner Assembly Pesawat Aerobatik Menggunakan Metode Elemen Hingga
Authors: Enggar Kristian  , Suprianto Agus , Pramana Nurhadi , Afandi Sahril , Yuniarti Endah 
Published: February 2021

Analisis rancangan bulkhead dilakukan untuk memperoleh geometri terbaik untuk mencari berat yang efisien dengan mengubah geometri bentuk pada bulkhead yang merupakan sub system wing to fuselage untuk pesawat berkategori aerobatik dan berat yang optimal yang memenuhi persyaratan regulasi FAR 23 dan mengetahui respon distribusi tegangan, bending yang dihasilkan dan kriteria kegagalan struktur berdasarkan variasi geometri bentuk bulkhead. Pada penelitian ini untuk analisis statik bulkhead untuk pesawat berkategori aerobatik menggunakan material Aluminium Alloy 7075-T6 dan menggunakan metode pendekatan Schrenk untuk menghitung beban eksternal distrbusi gaya angkat pada sayap. Selain itu dilakukan proses optimisasi berat bulkhead berdasarkan metode pendekatan topologi yaitu perubahan geometri bentuk pada bulkhead untuk mereduksi berat, sudut insiden spar yang berbeda dan menghitung magin of safety. Proses penyelesaian masalah menggunakan perangkat lunak metode elemen hingga (Abaqus CAE). Optimisasi topologi pada part bulkhead sudut insidet 0° dan 4° menghasilkan volume yang berkurang pada benda sehingga mereduksi berat, tetapi nilai dari margin of safety MS = 0.
The bulkhead design analysis was carried out to obtain the best geometry to find an efficient weight by changing the shape geometry of the bulkhead which is a sub-system of the wing to the fuselage for an aircraft categorized as aerobatics and an optimal weight that meets the requirements of FAR 23 regulations and sees the stress distribution response, the resulting bending and structural failure criteria based on the geometric variation of bulkhead shapes. In this study, to analyze the bulkhead static for an aerobatic category aircraft using Aluminum Alloy 7075-T6 material and using the Schrenk Approximation method to calculate the external distribution load of lift force on the wing. In addition, the optimization of bulkhead weight based on the topological approach method is to change the shape geometry of the bulkhead to reduce weight, in different spar incidents and calculate margin of safety. The problem solving process uses finite element method software (Abaqus CAE). Topological optimization of the bulkhead part with an incidence angle of 0 ° and 4 ° results in a reduced volume of the object so that it reduces weight, but the value of the margin of safety MS = 0.
Evaluation of Empirical Approach for Gearbox Diagnosis in the Construction Equipment
Authors: Kim Keon 
Published: February 2021

A planetary gearbox is one of the most important components in rotating machinery. In construction equipment, it is mainly used for swing and traveling devices due to huge torque capability and good torque transmission. Unexpected failure of the planetary gearbox can cause increased idle time, unnecessary cost due to inability of the construction site and safety hazards such as an operator isolation in a remote area. For these reasons, the need for timely prediction of unexpected failure becomes increasingly important in the field of construction machinery. In general, studies on fault diagnosis and condition monitoring of planetary gearboxes have been carried out in fields such as aircraft, wind-turbines and power plants. Researches in the above-mentioned fields usually require high performance computing power, and the burden of cost for diagnosis is relatively small. In addition, construction machinery also faces difficulties due to various uncertainties such as uncertain operating conditions that affect the vibration characteristics of gearboxes.
This study focuses on an approach to the vibration-based fault diagnosis methodology that can distinguish gear faults in a planetary gearbox in an excavator using vehicle-based test. First, we analyze the types of gear faults and the parts where failures occur mainly through the database of field failures. From this result, several fault types to be used in the experiment are selected, and an arbitrary fault is applied to gears. Secondly, since the vibration data is acquired directly from the excavator, the signal processing method that can remove the noise as much as possible and distinguish the fault is selected. Finally, optimized features are selected to minimize the uncertainty impacts that cannot be eliminated or unknown. Through this study, we confirmed the effect of the signal processing method which can be used in the planetary gearbox of the excavator as follows: 1) Several kinds of fault can be distinguished. 2) Faults and methodologies that can be distinguished in the constant speed condition 3) Faults and methodologies that can be distinguished in the transition speed condition.
Automatic detection of rare observations during production tests using statistical models
Authors: Mourer Alex , Lacaille Jérôme , Olteanu Madalina , Chavent Marie 
Published: February 2021

Engines are verified through production tests before delivering them to customers. During those tests, lot of measures are taken on different parts of the engine, considering multiple physical parameters. Unexpected measures can be observed. For this very reason, it is important to assess if these unusual observations are statistically significant.
However, anomaly detection is a difficult problem in unsupervised learning. The obvious reason is that, unlike supervised classification, there is no ground truth against which we could evaluate results. Therefore, we propose a methodology based on two independent statistical algorithms to double check our results. One approach is the Isolation Forest (IF) model which is specific to anomaly detection and able to handle a large number of variables. The goal of the algorithm is to find rare items, events or observations which raise suspicions by differing significantly from the majority of the data and, at the same time, it discriminates non-informative variables to improve. One main issue of IF is its lack of interpretability. Within this scope, we extend the shapley values, interpretation indicators, to the unsupervised context to interpret the model outputs.
The second approach is the Self-Organizing Map (SOM) model which has nice properties for data mining by providing both clustering and visual representation. The performance of the method and its interpretability depends on the chosen subset of variables. In this respect, we first implement a sparse-weighted K-means to reduce the input space, allowing the SOM to give an interpretable discretized representation.
We apply the two methodologies on data on aircraft engines measurements. Both approaches show similar results which are easily interpretable and exploitable by the experts.
Text Classification and Tagging of United States Army Ground Vehicle Fault Descriptions in Support of Data-Driven Prognostics
Authors: Hansen Brandon , Coleman Cody , Zhang Yi , Seale Maria 
Published: February 2021

The manner in which a prognostics problem is framed is critical for enabling its solution by the proper method. Recently, data-driven prognostics techniques have demonstrated enormous potential when used alone, or as part of a hybrid solution in conjunction with physics-based models. Historical maintenance data constitutes a critical element for the use of a data-driven approach to prognostics, such as supervised machine learning. The historical data is used to create training and testing data sets to develop the machine learning model. Categorical classes for prediction are required for machine learning methods; however, faults of interest in US Army Ground Vehicle Maintenance Records appear as natural language text descriptions rather than a finite set of discrete labels.
Transforming linguistically complex data into a set of prognostics classes is necessary for utilizing supervised machine learning approaches for prognostics. Manually labeling fault description instances is effective, but extremely time-consuming; thus, an automated approach to labelling is preferred. The approach described in this paper examines key aspects of the fault text relevant to enabling automatic labeling. A method was developed based on the hypothesis that a given fault description could be generalized into a category. This method uses various natural language processing (NLP) techniques and a priori knowledge of ground vehicle faults to assign classes to the maintenance fault descriptions.
The core component of the method used in this paper is a Word2Vec word-embedding model. Word embeddings are used in conjunction with a token-oriented rule-based data structure for document classification. This methodology tags text with user-provided classes using a corpus of similar text fields as its training set. With classes of faults reliably assigned to a given description, supervised machine learning with these classes can be applied using related maintenance information that preceded the fault.
This method was developed for labeling US Army Ground Vehicle Maintenance Records, but is general enough to be applied to any natural language data sets accompanied with a priori knowledge of its contents for consistent labeling. In addition to applications in machine learning, generated labels are also conducive to general summarization and case-by-case analysis of faults. The maintenance components of interest for this current application are alternators and gaskets, with future development directed towards determining the RUL of these components based on the labeled data.