bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection of Self-explosion Defect in electronic insulators based on modified YOLOX
Authors: Li Hong , Zhang PengPeng , Dou Mengshen , Xu Siyu 
Published: August 2022

Abstract
Self-explosion is a common defect of electronic insulators, which usually affects the safety of power transmission. Automatic inspection of insulators is time-saving and efficient. However, it is a detection problem on small object for detecting defects directly in aerial images, which has two parts, insulator positioning and defect detection. Since the insulator is long, the defect detection region obtained by positioning is long and narrow. Though YOLO network is an efficient model for defect dectection, it cannot achieve sufficient performance when the image is long and narrow. To solve this problem, YOLOX is modified by sliding window and CBAM in this paper. Firstly, a novel insulator dataset with long and narrow images was constructed. Secondly, a segmentation network based on sliding windows was utilized for dividing insulator image in the process of inference. Finally, CBAM is introduced into the YOLOX network to enhance defect features. Experiments demonstrate that the AP of the proposed method reaches 92.48\% and the reasoning speed reaches 28FPS.
Application of Ultrasonography to Neuro-COVID-19
Authors: Ruggiero Marco 
Published: August 2022

Abstract
Aim: The aim of this study is to evaluate the role of ultrasonography in diagnosis and treatment of COVID-19, the disease caused by severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2), with particular reference to the symptoms that are frequently observed in Neuro-COVID-19, a term that indicates the plethora of short- and long-term neurologic and psychiatric manifestations caused by, or associated with the disease. In a significant percentage of cases, neuro-psychiatric symptoms persist after recovery and long-term sequelae have been reported. SARS-CoV-2 can infect the brain through different routes and the damage can be direct, that is due to the virus itself, or indirect, that is associated with abnormal immune responses, inflammation, and hypoxia. Methods: In this study, the brain was studied by transcranial ultrasonography. Analysis of brain specimens obtained from autopsy demonstrated the presence of the virus in a minority of cases and this leads to hypothesize that SARS-CoV-2 may hide in sanctuary sites in the central nervous system in analogy with what observed for HIV. The existence of sanctuary sites for SARS-CoV-2 has the potential to decrease the efficacy of antiviral therapies or vaccination and may even prevent complete eradication of SARS-CoV-2 from the infected organism. Results: Transcranial ultrasonography demonstrated significant movements of the brain associated with the respiratory cycle. In 2017, a diagnostic and therapeutic procedure was proposed with the goal of identifying and treating pathogens hiding in sanctuaries that elude diagnosis and therapy. This procedure is based on clinical evaluation, diagnostic ultrasonography, therapeutic ultrasounds, and laboratory analyses. Conclusions: Here, it is demonstrated that application of transcranial ultrasonography to Neuro-COVID-19 requires a specific adaptation that takes into account brain movements synchronous with breathing as well as the sensitivity of SARS-CoV-2 to ultrasounds.
Academic House Style and Acknowledgement Writing: the Case of Two Ghanaian Universities
Authors: Owusu Debrah Cecilia Agyeiwah Agyemang , Nyarko Ansah Alberta Dansoah 
Published: August 2022

This descriptive study sought to examine the structural features of Thesis Acknowledgements (TA) from two disciplines in two Ghanaian Universities. Forty TAs were sampled from the fields of Chemistry and English. Hyland’s (2004) generic move structure was modified in analyzing the sampled TAs. The data was also examined on the basis of the two institutions’ academic style guides for conformity. The findings indicate that the structural features of TAs from the two fields differ. It also revealed that out of the seven steps identified in the obligatory Elaborative Move, DoC writers generally use three steps, and DoE writers mostly use four steps. It is further revealed that while writers from the DoC mostly acknowledged contributors for their technical support, writers from DoE acknowledged their helpers for providing materials for the research. It was revealed that the data followed the institutional style guide. The paper argues that though the contextual difference in the TAs from both fields is minimal, subtle variances and parallels still exist between the two fields. Therefore, it is suggested that these variations in linguistic forms that account for the discursive styles of the TAs should be further examined. Finally, additional analysis by corpus analytic tools applied to large data from the research context could complement this study.
Applications of soft computing techniques for prediction of pollutant removal by environmentally friendly adsorbents (case study: the nitrate adsorption on modified hydrochar)
Authors: Divband Hafshejani Laleh , Naseri Abd Ali , Moradzadeh Mostafa , Daneshvar Ehsan , Bhatnagar Amit 
Published: August 2022

Abstract
Artificial intelligence has emerged as a powerful tool for solving real-world problems in various fields. This study investigates the simulation and prediction of nitrate adsorption from an aqueous solution using modified hydrochar prepared from sugarcane bagasse using an artificial neural network (ANN), support vector machine (SVR), and gene expression programming (GEP). Different parameters, such as the solution pH, adsorbent dosage, contact time, and initial nitrate concentration, were introduced to the models as input variables, and adsorption capacity was the predicted variable. The comparison of artificial intelligence models demonstrated that an ANN with a lower root mean square error (0.001) and higher R2 (0.99) value can predict nitrate adsorption onto modified hydrochar of sugarcane bagasse better than other models. In addition, the contact time and initial nitrate concentration revealed a higher correlation between input variables with the adsorption capacity.
Predicting Abnormalities in Laboratory Values of Patients in the Intensive Care Unit Using Different Deep Learning Models: Comparative Study
Authors: Ayad Ahmad , Hallawa Ahmed , Peine Arne , Martin Lukas , Fazlic Lejla Begic , Dartmann Guido , Marx Gernot , Schmeink Anke 
Published: August 2022

Background
In recent years, the volume of medical knowledge and health data has increased rapidly. For example, the increased availability of electronic health records (EHRs) provides accurate, up-to-date, and complete information about patients at the point of care and enables medical staff to have quick access to patient records for more coordinated and efficient care. With this increase in knowledge, the complexity of accurate, evidence-based medicine tends to grow all the time. Health care workers must deal with an increasing amount of data and documentation. Meanwhile, relevant patient data are frequently overshadowed by a layer of less relevant data, causing medical staff to often miss important values or abnormal trends and their importance to the progression of the patient’s case.

Objective
The goal of this work is to analyze the current laboratory results for patients in the intensive care unit (ICU) and classify which of these lab values could be abnormal the next time the test is done. Detecting near-future abnormalities can be useful to support clinicians in their decision-making process in the ICU by drawing their attention to the important values and focus on future lab testing, saving them both time and money. Additionally, it will give doctors more time to spend with patients, rather than skimming through a long list of lab values.

Methods
We used Structured Query Language to extract 25 lab values for mechanically ventilated patients in the ICU from the MIMIC-III and eICU data sets. Additionally, we applied time-windowed sampling and holding, and a support vector machine to fill in the missing values in the sparse time series, as well as the Tukey range to detect and delete anomalies. Then, we used the data to train 4 deep learning models for time series classification, as well as a gradient boosting–based algorithm and compared their performance on both data sets.

Results
The models tested in this work (deep neural networks and gradient boosting), combined with the preprocessing pipeline, achieved an accuracy of at least 80% on the multilabel classification task. Moreover, the model based on the multiple convolutional neural network outperformed the other algorithms on both data sets, with the accuracy exceeding 89%.

Conclusions
In this work, we show that using machine learning and deep neural networks to predict near-future abnormalities in lab values can achieve satisfactory results. Our system was trained, validated, and tested on 2 well-known data sets to ensure that our system bridged the reality gap as much as possible. Finally, the model can be used in combination with our preprocessing pipeline on real-life EHRs to improve patients’ diagnosis and treatment.
Adsorption and release of soil P in andisols under organic and conventional vegetable farming system
Authors: Maritasari Aridinasty , Purwanto Benito Heru , Utami Sri Nuryani Hidayah 
Published: August 2022

Phosphorous (P) is strongly adsorbed by soil components, such as soil organic matter and soil amorphous minerals in Andisols, which have been identified as an influential factor in adsorption and release of soil P. The aim of this study was to characterize the pattern of soil P adsorption and release in both organic and conventional vegetable farming systems in Merbabu Mountain area, Indonesia. Soil samples were collected from soil layers (0 cm to 20 cm and 20 cm to 40 cm) in organic and conventional farming systems. The result showed that the highest adsorption rate was found in organic farming systems at a depth of 20 cm to 40 cm. The lowest adsorption rate was found in conventional farming systems with low input of organic matter at a depth of 20 cm to 40 cm. A higher rate of P release was also found in organic farming systems with a low input of organic matter. It can be concluded that vegetable soils in organic farming systems are not only highly capable of adsorbing P but also capable of releasing P rapidly.
Anatomical characteristics of cocoa plant roots as affected by the levels of calcium fertilization
Authors: Lubis Sutan Tarmizi , Putra Eka Tarwaca Susila , Kurniasih Budiastuti 
Published: August 2022

Cocoa plant (Theobroma cacao L.) is one of good annual crops grown in Indonesia. The disadvantages and advantages of Ca in plants can affect morphology and anatomy in plants. This research aimed to identify the effect of Ca on the anatomical performance of the roots of cocoa plants and determine the optimal dose of Ca for the anatomical characteristics of the roots of cocoa plant. The research was conducted at the cocoa plantation owned by PT. Pagilaran at North Segayung Production Unit, Tulis Subdistrict, Batang Regency, Central Java, in October 2019 – February 2021. The observation of root anatomy was carried out by making preparations, and the plant roots were taken destructively and sliced transversely. The field experiment was arranged using a single factor randomized complete block design. The treatments consisted of without fertilizer application and calcium fertilization at a dose of 100 g/tree/year, 200 g/tree/year, 300 g/tree/year, and 400 g/tree/year. The cocoa clone used was clone RCC 71. The results showed that an increase in the dose of CaCl2 fertilizer up to 400 g/tree/year was generally followed by an increase in the size of the xylem and phloem diameters, the thickness of the cork layer, the thickness of secondary cortex, and the diameter of the stele. The quadratic effect of the dose of CaCl2 fertilizer was observed only on the thickness of the root cambium tissues. Thus, it is necessary to conduct further research to determine the optimal dose of Ca fertilizer for the anatomical characteristics of cocoa roots.
Growth and Survival Rate Goldfish (Carassius auratus L.) in Various Dosages of Natural Feed Tubifex sp.
Authors: Risdawati  , Widiastuti Irawati Mei 
Published: August 2022

Ikan mas koki (Carassius auratus L.) termasuk ikan hias air tawar yang populer dibudidayakan di Indonesia. Salah satu kendala dalam usaha budidaya ikan mas koki adalah biaya pakan yang tinggi (60-70%) dari total biaya produksi. Sumber pakan alami untuk ikan mas koki adalah cacing sutera yang mengandung kandungan nutrisi yang cukup tinggi. Penelitian bertujuan mengetahui dosis cacing Tubifex sp. terbaik untuk pertumbuhan dan sintasan benih ikan mas koki (C. auratus L.). Penelitian dilakukan di Laboratorium Kualitas Air dan Biologi Akuatik, Fakultas Peternakan dan Perikanan, Universitas Tadulako selama 2 bulan (Januari - Maret 2020). Desain percobaan menggunakan Rancangan Acak Lengkap (RAL) dengan 5 perlakuan dan 4 kali ulangan. Perlakuan dalam penelitian adalah pemberian Tubifex sp. dengan dosis berbeda (A=6%; B=8%; C=10%; D=12%; E=14%). Variabel yang diukur meliputi pertumbuhan bobot mutlak, sintasan dan kualitas air. Data dianalisis dengan analisis ragam (ANOVA), dengan uji lanjut Beda Nyata Jujur (BNJ) menggunakan program aplikasi Excel 2010 dan Minitab 16. Hasil penelitian menunjukkan bahwa pemberian pakan alami Tubifex sp. menunjukkan pertumbuhan bobot mutlak yang significan, namun tidak berpengaruh terhadap sintasan. Pertumbuhan mutlak benih ikan mas koki tertinggi yaitu pada pemberian pakan Tubifex sp. dengan dosis 12% sebesar 14,82±2,76 g dengan persentase sintasan sebesar 90,63%±6,25. Kualitas air (suhu, pH, oksigen terlarut dan amonia) masih sesuai dengan kebutuhan pertumbuhan benih ikan mas koki.
‘SPEAKING’ VERBS IN MIDDLE ARMENIAN
Authors: AZIZBEKYAN TATEVIK 
Published: August 2022

Identifying specific weight of verbs in the Armenian grammatical system, semantic diversity, communicative value, and communicative abilities, it is imperative to analyze the semantic grouping of verbs and the connective features of lexical groups, which will contribute to the discovery of lexical meaning and syntactic-conjunctive interrelationships. The purpose of this article is to show the boundaries, features, and linguistic potential of the most diversified collection of verbs in the lexicon-proverbial verbs.
The analysis of verbs denoting ‘speaking’ in Middle Armenian brings to the conclusion that these verbs possess a common quality - that of telling information. Based upon this fact one can say that there are two subgroups within these verbs: a) single-stream and b) reciprocal verbs denoting speaking. Within the studied verbs, the stylistically neutral verb ‘say’ which is the most frequently used one due to its polysemy. As a rule, the verbs denoting speaking or other verbs used in the same meaning possess or gain the transitivity with two objects, one of which is presupposed or imposed by the grammatical rank of the verb (direct object) and the second – by the meaning of the verb (indirect object). In other words, the verbs of the studied group take two objects.
STATUS AND PECULIARITIES OF THE DEVELOPMENT OF NON-FORMAL AND INFORMAL EDUCATION IN THE REPUBLIC OF ARMENIA
Authors: Ispiryan MARIAM , VARDANYAN MARIA 
Published: August 2022

The article reveals trends in organizing educational process on the principles of formal, non-formal and informal models. Nowadays non-formal and informal education is becoming relevant. Unlike formal education, these forms are free from strict rules and regulations, can satisfy educational needs of citizens to a greater extent, regardless of their age, gender, educational level. They also expand professional competences, realizing the most important human need for impressions, for personal development, which leads to professional growth of a person. The article substantiates the idea that non-formal and informal models of education are available to people of all ages, are important part of socialization of a person, help master new social roles, contribute to spiritual development.
During the study, interest and preferences in various forms of adult education were revealed. The article touches upon the issues of evaluation, recognition and certification (accreditation) of the results of non-formal and informal education in Armenia. The obtained results show that interest in various forms of adult education is growing both from science and from practitioners, especially in the era of information society. Recognized results may be a sufficient condition to enter the labor market, realize a particular job or occupation.
Image denoising model based on improved fractional calculus mathematical equation
Authors: Li Kai , Wang Xinke 
Published: August 2022

Abstract
Aiming at the problems of image edge blur and detail loss in most image denoising models, an image denoising model based on improved fractional calculus is proposed. Through the classification of image noise, the integer order PDE model is discussed. Based on the mathematical theory of fractional calculus, the fractional PDE model is discussed. The model is improved by combining texture detection operator, gray value detection operator, smoothing factor and fast algorithm. The simulation experiment of the model is carried out based on MATLAB simulation platform. The results show that the improved model is significantly better than other comparison models in image denoising effect, and the operation efficiency is higher.
Allometric models for estimating aboveground biomass of young Norway spruce trees in the Western Carpathians, Slovakia
Authors: Pajtík Jozef , Konôpka Bohdan , Šebeň Vladimír 
Published: August 2022

Abstract
In the period of climate change, it is necessary to have biomass models for trees of all sizes to make precise estimations of biomass forest stocks to quantify carbon sequestration by forest cover. Therefore, we created allometric models of aboveground biomass in young Norway spruce (Picea abies [L.] Karst.) trees including main components, i.e. stem, branches and needles. The models used 200 sampled trees from 10 sites located in the central part of the Western Carpathians in Slovakia. The models, i.e. allometric regression relations implemented stem base diameter (diameter d0) and/or tree height. Moreover, using the derived allometric relations and a constant annual diameter increment of 10 mm, we calculated quasi-annual aboveground biomass production with regard to diameter d0. While stem had the largest contribution to aboveground biomass, followed by needles and branches, a different situation was revealed for the annual aboveground biomass production with the largest share of needles followed by stem and branches. Finally, we implemented the allometric models in a specific forest stand, where repetitive measurements were performed within 14 consecutive years. The results showed for example nearly 650 kg of the aboveground biomass per 102 m2 at the stand age of 10 years. The new biomass models can be applied to estimate the aboveground biomass stock in Norway spruce dominating stands in the Western Carpathians. Since the models are based on both diameter d0 and tree height a user can choose which variable is more suitable for particular conditions.
Long-term soil water content dynamics under different land uses in a small agricultural catchment
Authors: Horel Ágota , Zsigmond Tibor , Molnár Sándor , Zagyva Imre , Bakacsi Zsófia 
Published: August 2022

Abstract
Longer term monitoring of soil water content at a catchment scale is a key to understanding its dynamics, which can assist stakeholders in decision making processes, such as land use change or irrigation programs. Soil water monitoring in agriculturally dominated catchments can help in developing soil water retention measurements, for assessment of land use change, or adaptation of specific land management systems to climate change. The present study was carried out in the Pannonian region (Upper-Balaton, Hungary) on Cambisols and Calcisols between 2015 and 2021. Soil water content (SWC) dynamics were investigated under different land use types (vineyard, grassland, and forest) at three depths (15, 40, and 70 cm). The meteorological data show a continuous decrease in cumulative precipitation over time during the study with an average of 26% decrease observed between 2016 and 2020, while average air temperatures were similar for all the studied years. Corresponding to the lower precipitation amounts, a clear decrease in the average SWC was observed at all the land use sites, with 13.4%, 37.7%, and 29.3% lower average SWC for the grassland, forest, and vineyard sites, respectively, from 2016 to 2020 (measured at the 15 cm depth of the soil). Significant differences in SWC were observed between the annual and seasonal numbers within a given land use (p < 0.05). The lowest average SWC was observed at the grassland (11.7%) and the highest at the vineyard (28.3%). The data showed an increasing average soil temperature, with an average 6.3% higher value in 2020 compared to 2016. The grassland showed the highest (11.3 °C) and the forest soil the lowest (9.7 °C) average soil temperatures during the monitoring period. The grassland had the highest number of days with the SWC below the wilting point, while the forest had the highest number of days with the SWC optimal for the plants.
A new small-scale experimental device for testing backward erosion piping
Authors: Petrula Lubomír , Říha Jaromír 
Published: August 2022

Abstract
Backward erosion piping is driven by seepage forces acting on the soil grains at the downstream end of the seepage path. A new device for the laboratory testing of backward erosion progression was developed and tested. The device consists of a plexiglass prism at which the seepage path has been predefined. The prism was equipped with an inflow consisting of gravel separated from tested sand by a strainer. The hydraulic gradient along the seepage pipe was observed by a set of piezometers and pressure cells, and the seepage discharge was measured volumetrically. The transported sediment was trapped in a vertical cone located downstream from the device. The progression of the seepage path, the piezometric heads and the trapped material was observed by two synchronous cameras. 15 trial tests have been carried out to date, and from these, the interim results are presented.
Reflecting on the Efficiency of Design Thinking and Lean Startup
Authors: Bätz Kerstin , Siegfried Patrick 
Published: August 2022

Abstract

Objective: In this article, the methods used to simplify the business modelling and founding of new companies are presented and critically reflected. Furthermore, it is discussed to what extent a specific method is advantageous, disadvantageous, applicable, not applicable, or even contradictory.

Methodology: The theoretical analysis is underpinned by a qualitative interview study asking company founders about applying the methods mentioned above. The work is based on scientific papers and books and is complemented by the data originating from a specially designed study.

Findings: The results conclude that business model founding instruments provide strategic guidelines favouring entrepreneurs, yet they turn out to be minor in its real-life significance as numerous factors rooted in different fields of expertise play in.

Value Added: The added value of this paper is in the elaboration of efficiency bringing and risk-minimizing components of the methods, respectively. Accordingly, managers and entrepreneurs of all industries are intended to be equipped with sufficient information content that eases the decision for or against one of the methods as realistic expectations considering the application are likely to emerge.

Recommendations: The limitations of this study are rooted in the chosen qualitative research since every interviewee is a subject to their individual perception.