bluuebunny/crossref_metadata_2025 huggingface dataset:
Collaborative Reengineering and Modularization of Software Systems
Authors: Zirkelbach Christian
Published: November 2021

Software systems evolve over their lifetime. Changing requirements make it inevitable to modify and extend the underlying source code. Understanding software systems embodies a crucial task, which needs to be addressed in an appropriate way to face inevitable challenges while performing software changes.
In this thesis, we introduce three complementary approaches to support the evolution and particularly understanding of software systems in different aspects. Our main contributions are (i) an approach named CORAL for enabling collaborative reengineering and modularization of software systems, (ii) a gesture-based, collaborative, and multi-user-featuring Virtual Reality approach named ExplorViz VR for the software city metaphor, and (iii) a database behavior live-visualization approach named RACCOON for database comprehension of software systems.
An extensive case study shows that our CORAL approach is capable of supporting reengineering and modularization processes. Furthermore, several evaluations demonstrate the high usability,
and efficiency and effectiveness for solving comprehension tasks when using our multi-user VR approach ExplorViz VR.
An ensemble model for predicting therapeutic response to unfractionated heparin therapy (Preprint)
Authors: Abdel-Hafez Ahmad , Scott Ian A. , Falconer Nazanin , Canaris Stephen , Bonilla Oscar , Marxen Sven , Van Garderen Aaron , Barras Michael
Published: November 2021

BACKGROUND

Unfractionated heparin (UFH), is an anticoagulant drug considered a high-risk medication in that an excessive dose can cause bleeding, while an insufficient dose can lead to a recurrent embolic event. Following initiation of intravenous (IV) UFH, the therapeutic response is monitored using a measure of blood clotting time known as the activated partial thromboplastin time (aPTT). Clinicians iteratively adjust the dose of UFH to a target aPTT range, with the usual therapeutic target range between 60 to 100 seconds.

OBJECTIVE

The aim of this study was to develop and validate a ML algorithm to predict, aPTT within 12 hours after a specified bolus and maintenance dose of UFH.

METHODS

This was a retrospective cohort study of 3273 episodes of care from January 2017 to August 2020 using data collected from electronic health records (EHR) of five hospitals in Queensland, Australia. Data from four hospitals were used to build and test ensemble models using cross validation, while the data from the fifth hospital was used for external validation. Modelling was performed using H2O Driverless AI® an automated ML tool, and 17 different experiments were conducted in an iterative process to optimise model accuracy.

RESULTS

In predicting aPTT, the best performing experiment produced an ensemble with 4x LightGBM models with a root mean square error (RMSE) of 31.35. This dataset was re-purposed as a multi-classification task (sub-therapeutic, therapeutic, and supra-therapeutic aPTT result) and achieved a 59.9% accuracy and area under the receiver operating characteristic curve (AUC) of 0.735. External validation yielded similar results: RMSE of 30.52 +/- 1.29 for the prediction model, and accuracy of 56.8% +/- 3.15 and AUC of 0.724 for the multi-classification model.

CONCLUSIONS

According to our knowledge, this is the first study of ML applied to IV UFH dosing that has been developed and externally validated in a multisite adult general medical inpatient setting. We present the processes of data collection, preparation, and feature engineering for purposes of replication.
Peran Kepribadian Kesungguhan terhadap Krisis Usia Seperempat Abad pada Emerging Adulthood dengan Dukungan Sosial sebagai Mediator
Authors: Wijaya Dzikria Afifah Primala , Utami Muhana Sofiati
Published: November 2021

Krisis usia seperempat abad merupakan krisis perkembangan yang terjadi pada masa emerging adulthood. Krisis usia seperempat abad terjadi karena pengaruh beberapa faktor, di antaranya kepribadian kesungguhan dan dukungan sosial. Tujuan dari penelitian ini adalah menguji peran kepribadian kesungguhan terhadap krisis usia seperempat abad pada emerging adulthood dengan dukungan sosial sebagai mediator. Partisipan penelitian ini adalah individu yang berada pada kelompok usia 18-25 tahun sebanyak 286 orang. Terdapat tiga alat ukur yang digunakan, yaitu Skala Quarter-life Crisis, Big-Five Inventory (BFI), dan The Multidimensional Scale of Perceived Social Support (MSPSS). Analisis mediasi menggunakan PROCESS, menunjukkan bahwa dukungan sosial memediasi peran kepribadian kesungguhan terhadap krisis usia seperempat abad sebesar 13% (-0,1286; p < 0,05). Dengan demikian, dapat disimpulkan bahwa dukungan sosial berfungsi sebagai mediator atas peran kepribadian kesungguhan terhadap krisis usia seperempat abad.
The Effect of Academic Resilience and Social Support towards Student Involvement in Online Lecture
Authors: Adhawiyah Rabiatul , Rahayu Diah , Suhesty Aulia
Published: November 2021

The Covid-19 pandemic has made conventional lectures turn to online learning. The lecture system that is carried out by students is expected not to reduce student engagement in every lecture. Student involvement is due to the social support and academic resilience of students. This study aimed to determine the effect of academic resilience and social support on student engagement in online lectures. This study used a quantitative approach. The subjects of this study were 100 students of the Faculty of Social and Political Sciences, Mulawarman University who were selected using a simple random sampling technique. The data collection method used the scales of student engagement, academic resilience, and social support. The results showed that: (1) there is a significant effect of academic resilience and social support on student involvement in online lectures (p < 0.05) and had an influence contribution (R2) of 52%; (2) there is a significant positive effect of academic resilience on student involvement in online lectures (p < 0.05); (3) there is a significant positive effect of social support on student involvement in online lectures (p < 0.05).
Penggunaan Virtual Reality Exposure terhadap Simtom Fobia Sosial pada Mahasiswa Saat Melakukan Public Speaking
Authors: Fatahillah Ar. , Hastjarjo Thomas Dicky
Published: November 2021

Fobia sosial atau kecemasan sosial merupakan rasa takut yang berlebihan pada situasi sosial. Rasa takut ini terkadang menimbulkan permasalahan dalam kehidupan sehari-hari. Penelitian ini bertujuan untuk mengetahui perubahan tingkat fobia sosial dan respons fisiologis yang terjadi pada mahasiswa saat diberikan paparan/eksposur berupa social exposure lingkungan virtual. Hipotesis pada penelitian ini adalah terdapat pengaruh signifikan virtual reality exposure terhadap perubahan respons fisiologis dan tingkat fobia sosial pada mahasiswa pada kelompok yang diberi perlakuan. Metode penelitian menggunakan desain eksperimen pretest-posttest control design dengan rancangan penelitian berupa mixed design. Terdapat 41 partisipan yang memenuhi kriteria penelitian. Partisipan dibagi ke dalam kelompok eksperimen (n= 21) dan kelompok kontrol (n= 20). Instrumen penelitian yang digunakan terdiri dari skala Social Anxiety Disorder Dimensional (SAD-D) dan Self-Statements During Public Speaking (SSPS) serta Biofeedback Procomp5 Infiniti. Analisis data menggunakan teknik mixed ANOVA. Hasil penelitian ini menunjukkan bahwa terjadi peningkatan simtom fobia sosial pada kelompok eksperimen secara tidak signifikan dan terjadi penurunan secara signifikan pada kelompok kontrol (p < 0,05). Implikasi dari penelitian ini diharapkan dapat memberikan informasi kepada penelitian selanjutnya dalam memberikan perlakuan pada partisipan yang mengalami kecemasan sosial dengan metode eksposur lingkungan virtual.
Program KEMAS untuk Menurunkan Kecemasan pada Dewasa Awal di Masa Pandemi Covid-19
Authors: Nabila Syifa , Khairani Maya , Sari Kartika , Faradina Syarifah
Published: November 2021

Tujuan penelitian ini untuk mengetahui pengaruh Program Kemas bagi dewasa awal di masa pandemi Covid-19. Penelitian ini merupakan penelitian praeksperimen dengan desain satu kelompok prates-pascates. Penelitian dilakukan secara daring yang melibatkan 36 subjek yang diperoleh dengan teknik insidental. Data penelitian dikumpulkan melalui subskala kecemasan DASS-21 kemudian dianalisis menggunakan metode non parametrik, yaitu Wilcoxon signed-rank test dengan hasil koefisien (z) = -4,584, dan nilai signifikan (p) = 0,00 (p<0,05). Hasil penelitian menunjukkan bahwa terdapat pengaruh Program KEMAS bagi dewasa awal di masa pandemi Covid-19. Hasil penelitian menunjukkan adanya perubahan kategori kecemasan pada subjek saat sebelum dan sesudah perlakuan, yaitu 80,6% subjek mengalami penurunan skor kecemasan; 13,9% berada pada skor kecemasan yang sama; 5,5% subjek mengalami peningkatan skor kecemasan.
Inovasi Gerakan Gelar Gulung sebagai Solusi Pemenuhan Kebutuhan Pangan Mandiri di Kota Yogyakarta
Authors: Farida Rahmawati  , Hidayah Ana Chusniatul , Faizah Aida Nur , Falahuddin Ahmad , Okuputra M Adryan
Published: November 2021

Gerakan Gelar Gulung merupakan aksi tanggap warga dalam hal pemenuhan kebutuhan pangan masyarakat yang terdampak oleh Pandemi COVID-19 di Desa Tegalweru Kecamatan Tegalrejo Kota Yogyakarta. Tujuan penelitian ini adalah mengeksplorasi aksi dan inovasi yang dilakukan Gerakan Gelar Gulung dalam memenuhi kebutuhan pangan secara mandiri sebagai upaya mitigasi dampak pandemi COVID-19. Analisis dalam penelitian ini dilakukan dengan metode deskriptif melalui pengumpulan data-data kualitatif yang diperoleh melalui metode observasi, wawancara, dan kepustakaan. Hasil penelitian menunjukkan bahwa terdapat 5 aksi dalam Gerakan Gelar Gulung yaitu a) aksi mapping warga mandiri pastisipatif, b) aksi tanggap darurat pangan, c) aksi sosial kemandirian ekonomi, d) aksi jejaring pangupa jiwa, dan e) aksi berkebun lumbung pangan. Implementasi Gerakan Gelar Gulung ini mendapatkan respon positif dari berbagai pihak dikarenakan program yang sedang berjalan ini mampu meningkatkan ketahanan pangan dalam masa pandemi COVID-19 dan mendorong kemandirian ekonomi dalam jangka panjang. 

Kata kunci: Gerakan Gelar Gulung, Pandemi COVID-19, Ketahanan Pangan 

 

Gelar Gulung is a citizen action in terms of fulfilling the food needs of society who affected by COVID-19pandemic. The purpose of the study is exploring what actions and innovations which were carried out by Gelar Gulung action in fulfilling food needs to mitigate the impact of COVID-19 pandemic, especially in Tegalweru Village. The analysis in this study was done using descriptive methods by collecting qualitative data obtained through observation, interview, and literature study. The results showed that there were 5 actions, namely a) participatory mapping, b) food emergency response actions, c) sufficiency economy, d) community leaders’ network actions, and e) urban farming. The implementation of Gelar Gulung action received positive response from the stakeholders as this ongoing program was able to increase food security during the COVID-19pandemic and encourage long-term economic sufficiency. 

Keywords: Gelar Gulung Action, COVID-19 Pandemic, Food Security
Analysis of COVID-19 Chest X-ray Data using an Ensemble of Different Convolutional Architectures
Authors: Sharma Gaurav
Published: November 2021

Abstract: After every 100 years, a pandemic comes and takes a great toll on the global civilization. This time its COVID-19 and the aftereffects are terrifying. As the symptoms for the disease are very common and are similar to common cold and viral influenza, the detection from symptoms is quite difficult. Although there are many methods devised but the detection of COVID19 has been a problem since the start, and we are still struggling to identify whether a person has the disease. This study proposes a unique model to identify the positive and negative cases using X-ray images of an individual as lungs are the first and most critical body part which gets affected by the virus which causes a deprecation in oxygen saturation. The proposed model is an ensemble of different CNN architectures which are Dense Net, NasNet-Large, Resnet-50, Inception Net, EfficientNetB0 and EfficientNetB1. The results show that the model reaches an accuracy of 99.6% on the tested dataset. Keywords: Deep learning, Convolutional Neural Networks, COVID-19, Ensemble Learning, EfficientNet
Prevalence of comorbidities and its impacts in Hospitalized patients with COVID-19
Authors: Khaksar Mohammad Ali , Zanganeh Yousefabadi Elham , Taleb Zadeh Reza , Rashidi Homeira , Maniati Mahmood , Bakhtiari Nima
Published: November 2021

Objective: The purpose of this study is to evaluate the prevalence of comorbidities in hospitalized COVID-19 patients and its effects on the severity of the disease. The coronavirus pandemic has been a challenging problem for health care systems since December 2019.
Methods: This was a retrospective, cross-sectional study analyzing data related to the epidemiological characteristics of COVID-19 patients admitted to Razi Hospital in Ahvaz, Iran from   November 2020 to February 2021. The data on patient demographic characteristics including age, gender, and underlying diseases were collected from patient records. Patients whose data were unavailable or incomplete were excluded from the study.
Results: The mean age of all of the 730 patients studied was 56.30Â±16.36 years, and 53.7% of them were men. Nearly 40% of the patients reported more than one comorbidity, with diabetes mellitus being the most frequent one (37.5%) followed by hypertension (35.3%) and ischemic heart disease (24.9). In addition, 21.5% of the patients required intensive care unit admission. Finally, 11.9% of the patients had respiratory distress and became intubated, and approximately 13.6% of the patients died. Hyperlipidemia, liver failure, tuberculosis, and elevated inflammatory biomarkers are risk factors for ICU admission and death. 
Conclusion: we found that male gender, older age, hyperlipidemia, liver failure, TB, having more than one comorbidity, and elevated inflammatory biomarkers were significantly associated with the risk of severe COVID-19 disease.
Post COVID-19 Subacute thyroiditis: A case report
Authors: Abusaiba Mohammed A. , Hadi Najah R. , Fedacko Jan , Singh Ram B. , Al-Aubaidy Hayder A.
Published: November 2021

Subacute thyroiditis is a non-suppurative inflammation of the thyroid gland, which usually develops after viral infection to the upper respiratory tract, accompanied by pain in the neck radiated to the jaw and fever. This is a case report study for a 43-year-old woman, who developed subacute thyroiditis 6 weeks following coronavirus disease (COVID-19).
Partitioned and Non-Partitioned Regularized Additive Hazard Models with and Without Spatial Dependence
Authors: Omaku Peter Enesi , Oyejola Benjamin Agboola
Published: November 2021

Spatial effects are often simultaneously investigated with non-linear effects of continuous covariates and the usual linear effect. In this work the performance of models with and without spatial dependence in partitioned (PM) and non-partitioned models (NPM) for four (4) censoring percentages, three(3) levels of Weibull baseline variances (WBV), and sample sizes 100, 500 & 1000 were investigated. Hazard models were adapted to the generalized additive predictors and analyses were carried out via MCMC simulation technique. The performances of the models were again assessed when fitted to the diabetic data set. Results suggest that; partition models outperformed the non-partition ones. Models with spatial dependence perform better than models without spatial dependence in denser event times and when WBVs are low. The partition models perform better with spatial dependence than the Non-partitioned models. For the diabetic data set, it is seen that covariates Age and Blood Sugar level (BSL) violates the proportionality assumptions upon test. Further assessment from the graph of coefficient against time; suggest that Age be put to cut-points while BSL was estimated for models with and without Penalized splines for the sake of comparison, since the graph shows just a slight deviation from proportionality. Hazard rates for the time varying Age; indicate that as the time of study rolls by, the hazard of experiencing the event death from the disease increases steadily between intervals but constant within each time interval. A unit change in hazard rate for BSL indicates a decrease for PM implemented for with and without penalized splines. The model without penalized splines was however, seen to be better with smaller DIC (Deviance Information Criteria) value. Marriage is seen to be significant in the management of the disease in comparison to single patients. In addition patients are advised to visit their physicians on a regular basis to run a routine check to keep their BSL in good range. The study provides a means of moving out of non-linear ruts in survival data analysis. Intervals increase sample sizes (pseudoobservations), which in turn improves the modified Partitioned model when they are with or without spatial dependence.
Modelling the Efficiency of TGARCH Model in Nigeria Inflation Rate
Authors: Olayemi Michael Sunday , Olubiyi Adenike Oluwafunmilola , Olajide Oluwamayowa Opeyimika , Ajayi Omolola Felicia
Published: November 2021

In general, volatility is known and referred to as variance and it is a degree of spread of a random variable from its mean value. Two volatility models were considered in this paperwork. Nigeria's inflation rate was modeled by applying the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and Threshold GARCH models. Symmetric and asymmetric models captured the most commonly stylized facts about the rate of inflation in Nigeria like leverage effects and irregularities in clustering and were studied. These models are GARCH (1,1) and TGARCH (1,1). This work estimated the comparison of volatility models in term of best fit and forecasting. The result showed that TGARCH (1,1) model outperformed GARCH (1,1) models in term of best fit, because it has the least AIC of 2.590438. We forecasted to see the level of volatility using Theils Inequality Coefficient and the result shows that TGARCH has the highest Theils Inequality Coefficient of 0.065075 which makes the TGARCH model better than the GARCH model in this research. From the initial and modified sample static forecast, it was discovered that the return on inflation is stable and shows that volatility slows towards the end of the month, we can see a downward spiral, which means price reaction to economic crisis led to lower production, lower wages, decreased demand, and still lower prices.
Monitoring Groundwater Quality using Probability Distribution in Gwale, Kano state, Nigeria
Authors: Ibrahim Auwalu , Suleiman Ahmad Abubakar , Abdullahi Usman Aliyu , Suleiman Suleiman Abubakar
Published: November 2021

Groundwater is the water present beneath the earth’s surface in soil pore spaces and the fractures of rock formations. Establishing a probability distribution that provides a good fit to groundwater quality has recently become a topic of interest in the fields of hydrology, meteorology among others. In this paper, three groundwater datasets including calcium, magnesium, and chloride are fitted to the normal, lognormal, gamma, Weibull, logistic, and log-logistic distributions to select the best groundwater model. The measures of goodness of fits such as the Akaike information criterion (AIC), Bayesian information criterion (BIC), and log-likelihood are computed to compare the fitted models. The results show that the gamma distribution gives better fits for calcium and magnesium datasets while the lognormal distribution provides a better fit for the chloride dataset than other competing models. This research describes an application of probability distributions and the best-fitted distribution to a practical problem involving groundwater data analysis. By assuming the distribution of data, analysts can utilize the characteristics of the distribution to make predictions on outcomes.
Diversidad y patrones de actividad de mamíferos silvestres medianos y grandes en la Cordillera de Talamanca, Costa Rica.
Authors: González Tenorio Roger , Eppert Amy A. , Mooring Michael S.
Published: November 2021

Introducción: La Cordillera de Talamanca en el sureste de Costa Rica, es una región prioritaria para la conservación, posee ecosistemas y especies poco conocidas. El estudio de mamíferos silvestres permite comprender la estructura y estado de conservación de los bosques tropicales: uno de los ecosistemas más diversos del planeta. Objetivo: Evaluar la riqueza, abundancia relativa y patrones de actividad de los mamíferos terrestres medianos y grandes en el Parque Internacional de La Amistad y el Corredor Biológico el Quetzal Tres Colinas. Métodos: Entre el 12 de julio del 2018 al 18 de abril del 2021, instalamos 18 estaciones de fototrampeo, cada una conformada por una cámara trampa y un atrayente olfativo. Resultados: Con un esfuerzo de muestreo de 15 335 días cámara trampa, obtuvimos 36 667 registros en los cuales detectamos 27 especies de mamíferos silvestres medianos y grandes; todas están en alguna categoría de riesgo nacional o internacional. Sciurus granatensis, Tapirus bairdii, Sylvilagus dicei y Mazama temama mostraron la distribución más amplia y la mayor abundancia relativa. Ateles geoffroyi, Cebus imitator y Microsciurus alfari tuvieron la menor abundancia y la distribución más restringida. Registramos cinco especies diurnas, seis nocturnas-crepusculares y 14 catemerales. Las especies únicas las detectamos en los pisos altitudinales Subalpino, Premontano y Montano bajo, los dos últimos registraron la mayor riqueza. Ocho especies mostraron fobia lunar, seis mostraron filia lunar y seis no mostraron afinidad al brillo lunar. Conclusión: Estas áreas protegen importantes poblaciones premontanas a subalpinas de mamíferos terrestres medianos y grandes, muchos catemerales o con fobia a la luna, y deben seguir siendo monitoreadas.
Encephalitis associated with cervical lymph nodes tuberculosis in a patient with human immunodeficiency virus infection: A case report
Authors: Pinzon Rizaldy , Kristina Hana
Published: November 2021

The risk of extrapulmonary tuberculosis increases in patients with human
immunodeficiency virus (HIV) infections. Encephalitis is a rare form of
extrapulmonary tuberculosis infection. We report a case of encephalitis
associated with cervical lymph nodes tuberculosis in a patient with
human immunodeficiency virus (HIV) infections.
An Incidental Finding of Unroofed Coronary Sinus During Angiography Confirmed By 3D Echocardiography; A Case Report
Authors: Fazlinezhad Afsoon , Keihanian Faeze , Ahmadi Mostafa , Tayyebi Mohammad
Published: November 2021

Unroofed Coronary Sinus (UCS) is an uncommon congenital heart anomaly
and the most unusual type of Atrial Septal Defect.This report presents
a-71-year-old female with palpitation and dyspnea following an emotional
stress, who was referred for ablation of typical atrial flutter.Finally
diagnosed with a partially UCS causing a bidirectional shunt.
Artificial Intelligence Enabled Reagent-free Imaging Hematology Analyzer
Authors: Shu Xin , Sansare Sameera , Jin Di , Zhang Xiangxiang , Tong Kai-Yu , Pandey Rishikesh , Zhou Renjie
Published: November 2021

Leukocyte differential test is a widely performed clinical procedure for
screening infectious diseases. Existing hematology analyzers require
labor-intensive work and a panel of expensive reagents. Here we report
an artificial-intelligence enabled reagent-free imaging hematology
analyzer (AIRFIHA) modality that can accurately classify subpopulations
of leukocytes with minimal sample preparation. AIRFIHA is realized
through training a two-step residual neural network using label-free
images of isolated leukocytes acquired from a custom-built quantitative
phase microscope. By leveraging the rich information contained in
quantitative phase images, we not only achieved high accuracy in
differentiating B and T lymphocytes, but also classified CD4 and CD8
cells, therefore outperforming the classification accuracy of most
current hematology analyzers. We validated the performance of AIRFIHA in
a randomly selected test set and cross-validated it across all blood
donors. Owing to its easy operation, low cost, and accurate discerning
capability of complex leukocyte subpopulations, we envision AIRFIHA is
clinically translatable and can also be deployed in resource-limited
settings, e.g., during pandemic situations for the rapid screening of
infectious diseases.

Corresponding author(s) Email:    rjzhou@cuhk.edu.hk, 
rishikesh.pandey@uconn.edu
Global Change and Emerging Infectious Diseases
Authors: Nova Nicole , Athni Tejas S , Childs Marissa L , Mandle Lisa , Mordecai Erin A
Published: November 2021

Our world is undergoing rapid planetary changes driven by human
activities, often mediated by economic incentives and resource
management, affecting all life on Earth. Concurrently, many infectious
diseases have recently emerged or spread into new populations. Mounting
evidence suggests that global change-including climate change, land-use
change, urbanization, and global movement of individuals, species, and
goods-may be accelerating disease emergence by reshaping ecological
systems in concert with socioeconomic factors. Here, we review insights,
approaches, and mechanisms by which global change drives disease
emergence from a disease ecology perspective. We aim to spur more
interdisciplinary collaboration with economists and identification of
more effective and sustainable interventions to prevent disease
emergence. While almost all infectious diseases change in response to
global change, the mechanisms and directions of these effects are system
specific, requiring new, integrated approaches to disease control that
recognize linkages between environmental and economic sustainability,
and human and planetary health.
Effect of PDYN rs2281285, rs2235749 and rs910080 gene polymorphisms on the intensity of depression symptoms and negative craving in heroin addicts
Authors: Kaya-Akyüzlü Dilek , Özkan-Kotiloğlu Selin , Yalçın-Şahiner Şafak , Ayaz Nagihan
Published: November 2021

The present study was undertaken to explore whether prodynorphin (PDYN) polymorphisms have an effect on the intensity of depressive symptoms and negative craving in heroin addicts in a sample of 100 heroin addicts and 108 controls. PDYN rs2281285, rs2225749 and rs910080 polymorphisms were analyzed by PCR-RFLP. Craving and the intensity of depressive symptoms were measured by the Substance Craving Scale and the Beck Depression Inventory-II, respectively. A significant association between depression severity and PDYN rs2281285 (P=0.026) and rs2225749 (P=0.038) polymorphisms was detected. PDYN rs2225749 variation showed a trend association with increased negative craving (P=0.066). We also examined the associations between heroin dependence and PDYN rs2281285, rs2225749 and rs910080 gene polymorphisms at the gene and haplotype levels. The AAA haplotype was more frequent in heroin addicts and shown to be significantly associated with increased risk for heroin dependence (OR, 8.922; 95% CI, 1.116-71.313; P<0.05). PDYN rs2281285 and rs2225749 variations affected the intensity of depressive symptoms, and PDYN rs2225749 polymorphism may contribute to the induction of negative craving in heroin addicts. Haplotype analysis revealed for the first time that addicts with the AAA haplotype of PDYN gene may be more prone to heroin dependence.
Explainable information retrieval using deep learning for medical images
Authors: Singh Apoorva , Pannu Husanbir , Malhi Avleen
Published: November 2021

Image segmentation is useful to extract valuable information for an efficient analysis on the region of interest. Mostly, the number of images generated from a real life situation such as streaming video, is large and not ideal for traditional segmentation with machine learning algorithms. This is due to the following factors (a) numerous image features (b) complex distribution of shapes, colors and textures (c) imbalance data ratio of underlying classes (d) movements of the camera, objects and (e) variations in luminance for site capture. So, we have proposed an efficient deep learning model for image classification and the proof-of-concept has been the case studied on gastrointestinal images for bleeding detection. The Explainable Artificial Intelligence (XAI) module has been utilised to reverse engineer the test results for the impact of features on a given test dataset. The architecture is generally applicable in other areas of image classification. The proposed method has been compared with state-of-the-art including Logistic Regression, Support Vector Machine, Artificial Neural Network and Random Forest. It has reported F1 score of 0.76 on the real world streaming dataset which is comparatively better than traditional methods.
Hyper-parameter optimization of convolutional neural networks for classifying COVID-19 X-ray images
Authors: Vrbacic Grega , Pecnik Spela , Podgorelec Vili
Published: November 2021

For more than a year the COVID-19 epidemic is threatening people all over the world. Numerous researchers are looking for all possible insights into the new corona virus SARS-CoV-2. One of the possibilities is an in-depth analysis of Xray images from COVID-19 patients, commonly conducted by a radiologist, which are due to high demand facing with overload. With the latest achievements in the field of deep learning, the approaches using transfer learning proved to be successful when tackling such problem. However, when utilizing deep learning methods, we are commonly facing the problem of hyper-parameter settings. In this research, we adapted and generalized transfer learning based classification method for detecting COVID-19 from X-ray images and employed different optimization algorithms for solving the task of hyper-parameter settings. Utilizing different optimization algorithms our method was evaluated on a dataset of 1446 X-ray images, with the overall accuracy of 84.44%, outperforming both conventional CNN method as well as the compared baseline transfer learning method. Besides quantitative analysis, we also conducted a qualitative in-depth analysis using the local interpretable modelagnostic explanations method and gain some in-depth view of COVID-19 characteristics and the predictive model perception.
An approach for selecting countermeasures against harmful information based on uncertainty management
Authors: Kotenko Igor , Saenko Igor , Parashchuk Igor , Doynikova Elena
Published: November 2021

Currently, one of the big problems in the Internet is the counteraction against the spread of harmful information. The paper considers models, algorithms and a common technique for choosing measures to counter harmful information, based on an assessment of the semantic content of information objects under conditions of uncertainty. Methods of processing incomplete, contradictory and fuzzy knowledge are used. Two cases of the algorithm implementation to eliminate the uncertainties in the assessment and categorization of the semantic content of information objects are analyzed. The first case is focused on processing fuzzy data. The second case is based on using an artificial neural network. An experimental evaluation of the proposed technique have shown that the use of both cases makes it possible to eliminate uncertainties of any type and, thereby, to increase the efficiency of choosing measures to counter harmful information.
How MCDM method and the number of comparisons influence the priority vector
Authors: Srdjevic Zorica , Srdjevic Bojan , Zdero Senka , Ilic Milica
Published: November 2021

One of the most important issues in multi-criteria decision making is the number of requited judgments decision-maker/analyst has to perform. This paper presents a comparison of the results obtained by standard analytic hierarchy process (AHP), limited AHP, and best-worst method (BWM) if the number of criteria is 6, 7, and 8. The examples show that BWM's results are comparable with the results if standard AHP is used, while the limited version of AHP is generally inferior to the other two methods.
A study on optimally constructed compactly supported orthogonal wavelet filters
Authors: Fan Yongkai , Hu Qian , Pan Yun , Huang Chaosheng , Chen Chao , Li Kuan-Ching , Lin Weiguo , Wu Xingang , Li Yaxuan , Shang Wenqian
Published: November 2021

Compactly supported orthogonal wavelet filters are extensively applied to the analysis and description of abrupt signals in fields such as multimedia. Based on the application of an elementary method for compactly supported orthogonal wavelet filters and the construction of a system of nonlinear equations for filter coefficients, we design compactly supported orthogonal wavelet filters, in which both the scaling and wavelet functions have many vanishing moments, by approximately solving the system of nonlinear equations. However, when solving such a system about filter coefficients of compactly supported wavelets, the most widely used method, the Newton Iteration method, cannot converge to the solution if the selected initial value is not near the exact solution. For such, we propose optimization algorithms for the Gauss-Newton type method that expand the selection range of initial values. The proposed method is optimal and promising when compared to other works, by analyzing the experimental results obtained in terms of accuracy, iteration times, solution speed, and complexity
IS ANTI-SECTARIANISM A DESIDERATUM OF A PUBLIC REASON VIEW?
Authors: Tahzib Collis
Published: November 2021

Public reason liberals hold that laws and institutions must be in some sense justifiable to all reasonable citizens. Public reason liberals have developed different accounts of the constituency of reasonable citizens to whom justification is owed. Recently, a number of theorists have suggested that public reason views with less “sectarian” accounts of reasonableness are in one way better than public reason views with more “sectarian” accounts of reasonableness. Yet despite being used to tremendous effect to motivate particular theories of public reason, this anti-sectarianism desideratum has not received focused treatment, and hardly any detailed arguments have been offered for it. In this paper, I fill this gap by considering the case for the anti-sectarian desideratum. I find that there is no good reason to regard less sectarian public reason views as in one way better than more sectarian views.
Linking Cybersecurity and Accounting: An Event, Impact, Response Framework
Authors: Janvrin Diane J. , Wang Tawei
Published: November 2021

SYNOPSIS

Due to recent high-profile cybersecurity breaches and increased practitioner and regulatory attention, organizations are under pressure to consider the accounting implications of these attacks and develop appropriate responses. Specifically, cybersecurity events may affect organizations' operations, financial and non-financial performance, and ultimately its stakeholders. To address how cybersecurity issues may affect accounting, this paper presents an Event, Impact, Response Framework to discuss current research and consider implications for both practitioners and researchers. The Framework highlights how practitioners may rely on research findings to better assess cybersecurity threats, understand their impact, and develop response strategies. Results encourage additional research examining how (1) organizations identify cybersecurity threats, incidents, and breaches, (2) cybersecurity affects different risks, and (3) management responses to cybersecurity risks and events. Further, the Framework suggests the need for cybersecurity research to extend beyond the AIS community to areas such as financial accounting, managerial accounting, and auditing.
Prevalence and Associated Factors of Alexithymia in Patients with Hidradenitis Suppurativa: A Cross-sectional Study
Authors: Głowaczewska Amelia , Szepietowski Jacek C. , Matusiak Łukasz
Published: November 2021

Abstract is missing (Short communication)
Does the Duncan-Ely test predict abnormal activity of the rectus femoris in stroke survivors with a stiff knee gait?
Authors: Tenniglo Martin J. B. , Nederhand Marc J. , Fleuren Judith F. , Rietman Johan S. , Buurke Jaap H. , Prinsen Erik C.
Published: November 2021

Objective: To determine the diagnostic value of the Duncan-Ely test in predicting abnormal rectus femoris activity during gait in stroke survivors walking with a stiff knee gait.
Design: Cross-sectional diagnostic study.
Subjects: A total of 95 patients with chronic stroke.
Methods: During physical examination, the Duncan-Ely test was performed and scored. Surface electromyography of the rectus femoris was then recorded during dynamic gait. To determine the diagnostic value, the results of the Duncan-Ely test and surface electromyography recordings (gold standard) were compared.
Results: The Duncan-Ely test had a sensitivity of 73%, a specificity of 29%, a positive predictive value of 60%, and a negative predictive value of 42%. The area under the curve was 0.488 ([AQ1] CI 0.355–0.621, p = 0.862), showing that the Duncan-Ely test is not better than random guessing.
Conclusion: The Duncan-Ely test has no predictive value for determining abnormal activity of the rectus femoris during gait. Using this test can lead to incorrect identification of abnormal rectus femoris activity, which might hamper the selection of optimal treatment options. We recommend stopping use of the Duncan-Ely test to predict rectus femoris overactivity during swing, and instead use surface electromyography.
Process And Materials Effect In Organic Coating Of Architectural Steels
Authors:   , Mugabo Sara L
Published: November 2021

Coil roll coating is an industrially mature process to produce pre-coated steels at high speeds.30% sales by revenue for Tata steel colors, UK is attributed to the manufacture of architectural steels which is primarily used for composite panels for cladding systems. A research programme has been carried out which has examined the mechanisms by which the coating is picked up from the coating trough by the roll, with a reference to a defect where an insufficient coating is transferred leading to a defect named paint misses (PMD). A comprehensive study of a pair of coatings, one which demonstrated PMD and one which did not identify that their performance difference could be attributed to differences in rheology. The coating extensional viscosity and elasticity were identified as indicators of the behaviour. The identification of these primary rheological characteristics was corroborated through a blind test of a further pair of coatings where PMD had been observed on the coating line. The ability of the pickup roller to pull the coating from the trough and apparent wall slip (AWS) near the surface were identified as the dominant mechanisms. These mechanisms were also identified in a laboratory-scale simulation of the pickup cylinder rotating in the coating trough. Model PVC coatings were manufactured where the pigment concentration and solvent level was varied independently to develop the further underlying relationship between material rheology and coating pick up. The Mooney analysis method used to examine the slip behaviour was found to be inadequate for describing the behaviour of the liquid coatings. The deviation between idealised and real behaviour increased as polymer and pigment mass fraction increased. The quantity of coating picked up by the roll was found to be difficult to measure accurately due to the presence of the ribbing phenomena, which was particularly evident on the commercial coating systems. Additionally, liquid coating pickup tended to reduce with roll speeds and decreased with increasing pigment fraction (and hence viscosity). The study recommends an updated Quality Control (QC) system for checking the liquid coatings prior to being introduced to the process coating line.
On the Empiricism of Logical Empiricism
Authors: Uebel Thomas
Published: November 2021

This paper warns against misunderstanding the logical empiricists’ take on the concepts of experience and empiricism. Far from expressing traditionalist way-of-ideas conceptions, these concepts were themselves rethought and refashioned to accord with their overall aim of making contemporary philosophy of science fit for purpose. To this end, this paper disarms the supposed counter-examples of Schlick’s foundationalism and Carnap’s Aufbau and exemplifies the aimed for understanding by examples of the physialist theorising of Carnap and Neurath.
ANALYSIS OF STUDENTS’ REPORT WRITING FROM SFL-GP PERSPECTIVE AND ITS RELATION TO STUDENTS’ PROFICIENCY
Authors: Pasaribu Monalisa , Lumban Tiurma Lumban , Samosir Hernawati
Published: November 2021

Academic writing is one of important skill to have students in tertiary education, including students of Information Technology Diploma. Using Systemic Functional Linguistics Genre Pedagogy (SFL GP), the students report writings are investigated, his research aims at investigating how students comprehend SFL GP in their report writing and find out the relationship between students’ knowledge of SFL GP with their language proficiency. The texts are analyzed using the genre division by Rose and Martin. The results of the analysis will be used to investigate if the knowledge of genre writing for technology-based students is related to their language proficiency. This research contributes to better use of genre pedagogy for science students, more specifically, students of Information Technology.
ЛЕЧЕБНЫЕ ГЛИНЫ В ТРУДАХ АНТИЧНЫХ И СРЕДНЕВЕКОВЫХ АВТОРОВ
Authors: Полтавец Юрий
Published: November 2021

В представленной работе проведен анализ литературного наследия античных и средневековых авторов: Гален, Диоскорид, Цельс, Авиценна, Амирдовлат Амасиаци. В статье представлено описание применения медицинской глины в античности и средневековье. Результаты содержат описание медицинских глин, их свойств и географическую справку о происхождения глин.
The Influence of Beauty Vloggers, Brand Image, and Product Quality on Lipstick Purchase Decisions
Authors: Malini Helma
Published: November 2021

Abstract—Women place a high value on their appearance. We can see in everyday life that most women are unable to live without cosmetics. Cosmetics have become a necessity for women to support their appearance while going about their daily activities in order to make them more attractive and confident. Women's lipstick is one of the most popular cosmetics. Consumers consider brand image and product quality when purchasing cosmetics, particularly lipsticks. The goal of this study is to see if the image of Beauty Vloggers and the quality of their products have an impact on purchase decisions. The sample size for this study was 100 people. Explanatory research methods are used. Multiple linear regression analysis with IBM SPSS Statistics 25 was used to analyze the data. The findings of this study show that in Indonesia, Beauty Vlogger Brand Image has no significant impact on Emina Cosmetics Lipstick Product Purchase Decisions, while Product Quality has a significant impact on Emina Cosmetics Lipstick Product Purchase Decisions.

Keywords: beauty vlogger, brand image, product quality, purchase decision

Abstrak—Wanita menempatkan nilai tinggi pada penampilan mereka. Kita dapat melihat dalam kehidupan sehari-hari bahwa kebanyakan wanita tidak dapat hidup tanpa kosmetik. Kosmetik sudah menjadi kebutuhan bagi wanita untuk menunjang penampilan saat menjalani aktivitas sehari-hari agar lebih menarik dan percaya diri. Lipstik wanita adalah salah satu kosmetik paling populer. Konsumen mempertimbangkan citra merek dan kualitas produk saat membeli kosmetik, khususnya lipstik. Tujuan dari penelitian ini adalah untuk melihat apakah citra Beauty Vlogger dan kualitas produknya berpengaruh terhadap keputusan pembelian. Besar sampel untuk penelitian ini adalah 100 orang. Metode penelitian eksplanatori digunakan. Analisis regresi linier berganda dengan IBM SPSS Statistics 25 digunakan untuk menganalisis data. Temuan penelitian ini menunjukkan bahwa di Indonesia, Brand Image Beauty Vlogger tidak berpengaruh signifikan terhadap Keputusan Pembelian Produk Lipstik Emina Cosmetics, sedangkan Kualitas Produk berpengaruh signifikan terhadap Keputusan Pembelian Produk Lipstik Emina Cosmetics.

Kata kunci: beauty vloggre, citra merek, kualitas produk, keputusan membeli
Review Essay: Comparing Demographic and Sociological Imaginations
Authors: Pearson David
Published: November 2021

Paul Spoonley’s wide-ranging survey of what he sees as new local population challenges is described and assessed. This is followed by an examination of Richard Alba’s critical analysis of how the misuse of demographic statistics influenced recent American political upheavals and distorts an understanding of ethno-relations in the United States. Whether his theory of new non-zero assimilation can be applied to New Zealand is then tentatively explored. Finally, some reflections on the relationship between demography and sociology and the enduring dangers of categoricalism are presented.
Review of Julie Spray’s (2020) The Children in Child Health: Negotiating Young Lives and Health in New Zealand. Rutgers University Press.
Authors: De Francesco Adriano
Published: November 2021

Review of Julie Spray’s (2020) The Children in Child Health: Negotiating Young Lives and Health in New Zealand. Rutgers University Press.
The Social Demography of Covid-19 Delta
Authors: Crothers Charles
Published: November 2021

Publically available information concerning the scanning, testing, vaccination, covid-catching are examined both to describe the over-time patterns but also to indicate possibly causal linkages to underlying social patterns.
The Natural Potential as a Premise for the Development of Tourism in Sălaj County, Romania
Authors: Rusu Raularian , Dezsi Ștefan , Dolean Bogdan Eugen , Man Titus , Moldovan Ciprian
Published: November 2021

"The tourism resources integrate the totality of attractive elements within a territory. The natural attractions of Sălaj County have been approached in this paper by analysing the four categories that are long-established in the scientific literature: morphological, climatic, hydrological and biogeographical tourist attractions. The geographical location of Sălaj County provides a privileged situation and a relative geographical unity, marked by a complex and complementary natural environment derived from the presence of a varied morphology. The karst morphology includes caves (Cuciulat, Măgurici), gorges (Babei Gorges), karst springs (Barcău Springs), and other attractions. The alternation of hard rocks and softer rocks, more friable and less resistant to erosion, led to the emergence of interesting forms, the result of differential erosion, such as the Dragons’ Garden (Grădina Zmeilor), the Devil’s Rock (Stânca Dracului), ”The Old Man and the Old Woman” (”Moșu și Baba”). Mineral and thermal waters are used for curative purposes at Băile Boghiș, Băile Bizușa, Jibou and Șimleu Silvaniei. The biogeographical potential is represented mainly by the vegetation cover, which is very diverse, including both forests and valuable flowering plants. Sălaj County has a significant natural potential, which is yet to be capitalized from the perspective of tourism, because natural attractions in Sălaj County are still little known to tourists, even in Romania.

Keywords: Sălaj County, tourism potential, natural attractions, Romania.
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