bluuebunny/crossref_metadata_2025_split huggingface dataset:
Legal Responsibility on Errors of the Artificial Intelligence-based Robots
Authors: Sumantri Viony Kresna 
Published: September 2019

Modern technology is developing rapidly. One branch of industrial technology that is particularly popular at the moment is artificial intelligence (AI) that facilitates society's daily life. On smartphones, artificial intelligence can be found in map applications, personal assistants, shopping websites, and various other applications. Saudi Arabia granted an AI-based robot named Sophia citizenship, and the Shibuya Mirai robot was granted a residence permit by Japan. AI-based technology is used every day and has become a common thing in various parts of the world; however, in Indonesia, legal regulations regarding AI do not yet exist. As a result, a legal vacuum has emerged. When a loss occurs, responsibility can be borne by various parties ranging from consumers, producers, third parties (such as robot trainers or shipping couriers) to the robot itself. Which party will be determined responsible depends upon how a country positions AI. If Indonesia follows in Saudi Arabia's footsteps, then the responsibility will be borne by the AI robot as a citizen. The robot will have the right to sue and be sued, to get the same position before the law, including other rights and obligations, enjoyed by human citizens. Artificial intelligence law-making is a very complicated process and will involve many parties. How Indonesia positions AI is very crucial, particularly in the event of harm or danger caused by AI systems. Various frameworks and concepts can be used, ranging from equating artificial intelligence to living beings, such as humans, pets, or ordinary products to creating entirely new concepts for a legal framework regulating AI-based systems.
Keywords: Artificial Intelligence, Responsibility, AI Law.
LEXICAL ITEMS IN BATAK TOBA LANGUAGE REPRESENTING FAUNA, FLORA, AND SOCIAL ENVIRONMENT: ECOLINGUISTICS STUDY
Authors: Silalahi Mery 
Published: September 2019

<p>In the ecolinguistic view, the relationship between human and nature (ecology) produces a variety of languages (linguistics). Language and environment are two things that influence each other. Change in language, both in the lexicon or grammar, cannot be released from changes in the natural and social environment. On the one hand, environmental changes have an impact on change in language, and on the other hand, the community behavior towards their environment influenced by the language they use. Thus, the dynamics of the existence of the lexicon are affected by changes in the environment of a place the language used. The results of this study prove that there is relationship between language and nature. There are 6 lexicons which be explained in this article.<strong> <em>Horbou</em></strong> <strong>or buffallo</strong> and <strong><em>Dekke</em> or fish: goldfish </strong>are lexical items representing fauna. <strong><em>Boras Sipir ni Tondi </em>or Rice and <em>Demban or Sirih or</em></strong> <strong>betel leaf<em> </em></strong>are lexical items representing flora. And to the lexical items which representing social environment are <strong><em>Ulos</em> or Woven Cloth and <em>Tortor</em></strong> <strong>or Traditional Dance</strong>. The six lexical items which are representing natural (two for fauna and flora respectively) and social environment (two lexical items) contain cultural terms in Batak Toba language. Because it is a cultural term, then it cannot be separated from the history of Batak people. The cutural terms then will be analyzed and compared to the present life in Indonesian culture in general. It could have similarities or even differences to the present life in Indonesia.</p><p> </p>
MicroRNAs in the response of non-heading Chinese cabbage to Hyaloperonospora parasitica (downy mildew) infection
Authors: Sun Chengzhen , Hu Die , Wang Yuan , Tan Huawei , Liu Tongkun , Zhang Changwei , Hou Xilin , Li Ying 
Published: September 2019

Abstract
Background
MicroRNAs (miRNAs) are a subset of endogenous small non-coding ~21 nucleotide RNAs, which are playing important roles in development, abiotic stress, and pathogen responses. Downy mildew, caused by Hyaloperonospora parasitica , is a severe fungal disease in non-heading Chinese cabbage ( Brassica rapa ssp. chinensis ). However, miRNAs and their targets involved in the response of non-heading Chinese cabbage to downy mildew were still unclear.
Results
Here, fifteen small RNA libraries were generated from non-heading Chinese cabbage leaves at different time points after H. parasitica inoculation. By deep sequencing, we identified 197 known miRNAs and 112 novel miRNAs. According to data analysis, 8 known miRNAs and 8 novel miRNAs were found to be responsive to downy mildew infection in non-heading Chinese cabbage. Expression levels of 12 predicted miRNAs target genes were determined by reverse transcription-quantitative polymerase chain reaction (qRT-PCR). In this study, we proposed a regulatory network showing that non-heading Chinese cabbage defense response to downy mildew by repressing cell wall pectin, lipid and cellulose catabolic process ( PME12 , PME17 , PLAIVA and GDPDL4 ) and callose deposition ( CYP79B2 ), repressing indole glucosinolate metabolic process ( CYP81F3 ), repressing respiratory burst ( PUB24 ), repressing programmed cell death ( CRK5 ), and inducing defense related gene expression ( ROS1 , LECRK-VII.2 , BAK7 and WRKY48 ).
Conclusions
This research identified miRNAs associated with downy mildew infection in non-heading Chinese cabbage. Target genes and network analysis contributed to understanding the interaction between plant and pathogen.
A Novel Highly Selective Cannabinoid CB2 Agonist Reduces in vitro Growth and TGF-beta Release of Human Glial Cell Tumors
Authors: Cioni Chiara , Tassi Maristella , Marotta Giuseppe , Mugnaini Claudia , Corelli Federico , Annunziata Pasquale 
Published: September 2019

Background:Cannabinoid receptors have been detected in human gliomas and cannabinoids have been proposed as novel drug candidates in the treatment of brain tumors.Aims:To test the in vitro antitumor activity of COR167, a novel cannabinoid CB2-selective agonist displaying a high binding affinity for human CB2 receptors, on tumor cells isolated from human glioblastoma multiforme and anaplastic astrocytoma.Methods:Glioma cell cultures were established from two glioblastoma multiforme and two anaplastic astrocytomas. Proliferation was measured in the presence or absence of COR167 with a bromodeoxyuridine (BrdU) cell proliferation ELISA assay. CB2 receptor expression was detected by western blotting. Apoptosis was assessed with phycoerythrin (PE) annexin V flow cytometry kit. TGF-beta 1 and 2 levels were analyzed in culture supernatants with commercial ELISAs.Results:COR167 was found to significantly reduce the proliferation of both glioblastoma and anaplastic astrocytoma in a dose-dependent manner at lower doses than other known, less specific CB2 agonists. This activity is independent of apoptosis and is associated with a significant reduction of TGF-beta 1 and 2 levels in supernatants of glioma cell cultures.Conclusion:These findings add to the role of cannabinoid CB2 receptor as a possible pharmacological target to counteract glial tumor growth and encourage further work to explore any other pharmacological effect of this novel CB2 agonist useful in the treatment of human gliomas.
Exploiting Machine Learning Algorithms and Methods for the Prediction of Agitated Delirium After Cardiac Surgery: Models Development and Validation Study
Authors: Mufti Hani Nabeel , Hirsch Gregory Marshal , Abidi Samina Raza , Abidi Syed Sibte Raza 
Published: September 2019

Background
Delirium is a temporary mental disorder that occasionally affects patients undergoing surgery, especially cardiac surgery. It is strongly associated with major adverse events, which in turn leads to increased cost and poor outcomes (eg, need for nursing home due to cognitive impairment, stroke, and death). The ability to foresee patients at risk of delirium will guide the timely initiation of multimodal preventive interventions, which will aid in reducing the burden and negative consequences associated with delirium. Several studies have focused on the prediction of delirium. However, the number of studies in cardiac surgical patients that have used machine learning methods is very limited.

Objective
This study aimed to explore the application of several machine learning predictive models that can pre-emptively predict delirium in patients undergoing cardiac surgery and compare their performance.

Methods
We investigated a number of machine learning methods to develop models that can predict delirium after cardiac surgery. A clinical dataset comprising over 5000 actual patients who underwent cardiac surgery in a single center was used to develop the models using logistic regression, artificial neural networks (ANN), support vector machines (SVM), Bayesian belief networks (BBN), naïve Bayesian, random forest, and decision trees.

Results
Only 507 out of 5584 patients (11.4%) developed delirium. We addressed the underlying class imbalance, using random undersampling, in the training dataset. The final prediction performance was validated on a separate test dataset. Owing to the target class imbalance, several measures were used to evaluate algorithm’s performance for the delirium class on the test dataset. Out of the selected algorithms, the SVM algorithm had the best F1 score for positive cases, kappa, and positive predictive value (40.2%, 29.3%, and 29.7%, respectively) with a P=.01, .03, .02, respectively. The ANN had the best receiver-operator area-under the curve (78.2%; P=.03). The BBN had the best precision-recall area-under the curve for detecting positive cases (30.4%; P=.03).

Conclusions
Although delirium is inherently complex, preventive measures to mitigate its negative effect can be applied proactively if patients at risk are prospectively identified. Our results highlight 2 important points: (1) addressing class imbalance on the training dataset will augment machine learning model’s performance in identifying patients likely to develop postoperative delirium, and (2) as the prediction of postoperative delirium is difficult because it is multifactorial and has complex pathophysiology, applying machine learning methods (complex or simple) may improve the prediction by revealing hidden patterns, which will lead to cost reduction by prevention of complications and will optimize patients’ outcomes.
Examining Mobile Technologies to Support Older Adults With Dementia Through the Lens of Personhood and Human Needs: Scoping Review
Authors: Koo Bon Mi , Vizer Lisa M 
Published: September 2019

Background
With the world’s rapidly growing older adult population, there is an increase in the number of people living with dementia. This growth leads to a strain on their caregivers and our health care system and to an increased attention on mitigating strain by using mobile technology to sustain the independence of people with dementia. However, less attention is given to whether these technologies meet the stated and unstated needs of people with dementia.

Objective
The aim of this study was to provide an overview of the current research on mobile technologies for people with dementia, considering the current research through the lens of personhood and human needs, and to identify any gaps that represent research opportunities.

Methods
We performed a systematic search in Medical Literature Analysis and Retrieval System Online (MEDLINE), Web of Science, PsycINFO, Cumulative Index of Nursing and Allied Health Literature (CINAHL), Excerpta Medica dataBASE (EMBASE), and the Cochrane Central Register of Controlled Trials (CENTRAL) in October 2018. We screened 5560 articles and identified 24 that met our inclusion and exclusion criteria. We then performed thematic analysis to organize the articles by the types of support mobile technologies provide and mapped those types of support to human needs to identify the gaps in support.

Results
Articles described research on mobile technologies that support people with dementia to (1) perform daily activities, (2) maintain social interaction, (3) aid memory, (4) engage in leisure activities, (5) track location, and (6) monitor health. At least one type of support mapped to each human need, with most supporting lower-level needs such as physiological and safety needs. Little attention seems to be paid to personhood.

Conclusions
Mobile technologies that support daily activities, relationships, memory, leisure activities, health, and safety can partially compensate for decreased function owing to dementia, but the human needs of people with dementia are often not adequately considered. Most technologies support basic physiological and safety needs, whereas many pay little attention to higher-level needs such as self-esteem and agency. Important research opportunities include using person-centered methods to develop technology to meet higher-level needs and to preserve personhood by incorporating human and psychological needs of people with dementia along with ethical considerations.
AMELIORATIVE EFFECT OF PHOENIX DACTYLIFERA ON ADVERSE EFFECTS OF LINEZOLID IN MALE ALBINO RATS
Authors: ABDO SAID MAHMOUD AHMED , AZIZ SAYED A , ELNABTITY SAMEH M 
Published: September 2019

Objective: This study aimed to investigate the adverse effects of linezolid (LZD) on biochemical and hematological parameters and some organsincluding bone marrow, brain, and kidneys and to investigate the possibility of methanolic extract of Phoenix dactylifera (MEPD) to counteract theadverse effects of LZD.Methods: Forty-eight adult male albino rats were allocated into four equal groups (each of 12 animals). The first group received Tween 80 orally. Thesecond group received was given 0.5 ml of LZD suspension 4% in Tween 80 (100 mg/kg body weight) orally. The third group received the same doseof LZD suspension followed by 1 ml of MEPD orally. The rats in the last group were given 1 ml of MEPD (1000 mg/kg body weight) orally. Rats weresacrificed and blood samples were collected for hematological and biochemical study. Femur bones, brain, and kidneys were dissected and kept in ajar containing 10% formalin to perform the histopathological investigation.Results: The dose of LZD administered for 14 successive days induced a mild-to-moderate hematological abnormalities including decrease inhemoglobin content (7.88±0.18 g/L) on day-1 post-treatment. Significant increase in serum urea (59.75±0.85) and serum creatinine was observed(1.89±0.04). On day-14 post-treatment, LZD induced mild-to-moderate cellular abnormalities in bone marrow, brain, and kidneys. The concurrentoral administration of MEPD and LZD for the same period corrected the hematological, biochemical, and histopathological alterations induced by LZD.
Conclusion: It was concluded that MEPD clearly ameliorated these damaging effects induced by LZD.
Aprendizaje constitucional
Authors: Arato Andrew 
Published: September 2019

El autor realiza un análisis de los problemas que se pueden suscitar en los procesos de elaboración constitucional llevados a cabo por las nuevas democracias emergentes. En un recorrido que nos lleva desde Budapest hasta Filadelfia, pata terminar en Sudáfrica, se discuten los aspectos relacionados con la legitimidad de estos procesos: el aprendizaje, los reglamentos de enmienda, los procedimientos a seguir, la publicidad, el consenso, la pluralidad y la “reflectividad”, es decir, la capacidad de autocontrol y automodificación de una constitución. Se examina el caso de Sudáfrica, al que toma como modelo político con objeto de sortear con éxito los obstáculos que se le presentan al legislador moderno cuando aspira a elaborar una constitución a la altura de las circunstancias y necesidades actuales y futuras de una nación democrática.
kVp, mA, and voxel size effect on 3D voxel-based superimposition
Authors: Eliliwi Manhal , Bazina Mohamed , Palomo Juan Martin 
Published: September 2019

ABSTRACT

Objectives:
To evaluate the effect of changing kVp, mA, and voxel size on the accuracy of voxel-based superimposition on the anterior cranial base.

Materials and Methods:
Cone beam computed tomography (CBCT) scans were taken on a phantom skull using different kVp, mA, and voxel size combinations. CBCT scans were superimposed using commercially available software. Two separate open-source software programs were used to generate a three-dimensional (3D) color map objective assessment of the differences in seven different regions: Nasion, Point A, Zygomatic (right and left), Point B, and Gonial (right and left). Each region had around 200 points that were used to calculate the mean differences between the superimpositions.

Results:
Intraclass correlation showed excellent reliability (0.95). Lowering the kVp made the biggest difference, showing an average discrepancy of 0.7 ± 0.3 mm, and a high mean of 1.4 ± 0.3 in the Right Gonial region. Lowering the mA showed less of a discrepancy, with an average of 0.373 ± 0.2 mm, and the highest discrepancy, also on the Right Gonial Area, of 0.7 ± 0.1 mm. The voxel size had the least impact on the accuracy of registered volumes, with mean discrepancy values of less than 0.2 mm.

Conclusions:
Using different CBCT settings can affect the accuracy of the voxel-based superimposition method. This is particularly the case when using low kVp values, while changes in mA or voxel sizes did not significantly interfere with the superimposition outcome.
Assessment of abbott architect 25-oh vitamin D assay in different levels of vitamin D
Authors: Avci Esin , Demir Süleyman , Aslan Diler , Nar Rukiye , Şenol Hande 
Published: September 2019

Summary

Background
There is increasing requests of Vitamin D test in many clinical settings in recent years. However, immunoassay performance is still a controversial topic. Several diagnostic manufacturers have launched automated 25-hydroxyvitamin D (25-OH D) immunoassays in the past decade. We compared the performance of Abbott Architect 25-OH D Vitamin immunoassay with liquid chromatography-tandem mass spectrometry systems (LC-MS/MS) to evaluate immunoassay performance, especially in deficient groups.

Methods
Eighty human serum samples were analyzed with Architect 25-OH D vitamin kit (Abbott Diagnostics, Lake Forest, IL, USA) and LC-MS/MS systems (Zivak Technology, Istanbul, Turkey). The results of the immunoassay method were compared with the LC-MS/MS using Passing-Bablok regression analysis, Bland-Altman plots and correlation coefficient analysis. We also evaluated results in four levels of D vitamin as a severe deficiency, deficiency, insufficiency, and sufficiency.

Results
Architect showed 9.59% bias from LC-MS/MS with smaller mean. Passing-Bablok regression analysis demonstrated the value of 0.95 slope and had a constant bias with an intercept value of -4.25. Concordance correlation coefficient showed moderate agreement with the value of 0.918 (95% CI 0.878–0.945). Two methods revealed good interrater agreement (kappa = 0.738). While the smallest bias determined in deficiency (9.95%) group, the biggest was in insufficiency (15.15%).

Conclusions
Architect 25-OH D vitamin immunoassay can be used in routine measurements but had potential misclassification of vitamin D status in insufficient and deficient groups. Although there are recent standardization attempts in 25-OH D measurements, clinical laboratories must be aware of this method.
Las competencias digitales en docentes y futuros profesionales de la Universidad Central del Ecuador
Authors: Cobos Velasco Juan Carlos , Jaramillo Naranjo Lilian Mercedes , Vinueza Vinueza Santiago 
Published: September 2019

En la actualidad, el rol que desempeñanlosdocentesde educación superior se fortalece con elmanejo de la conectividad,ya que para enseñarasusestudiantes requieren del conocimiento y aplicación de herramientas tecnológicas que ofrece la web 2.0. Por lo que los docentes deben aprestarse no solo a adquirir conocimientos básicos en tecnología, sino a ser competentes para aplicar ésta en sus prácticas didácticas y, para lograrlo, suenseñanza aprendizaje inicial resulta esencial. El objetivo de esta investigación esrealizar una aproximación diagnóstica sobrelas competencias digitales que poseen futuros profesionales y docentes en el ejercicio de su profesión. Para ello, de una población total de 40.000 estudiantesde la Universidad Central del Ecuador se extrajo lamuestra óptima de 1.799, quienes respondieron a un cuestionario de percepción de conocimiento, aplicación y valoración de competencias digitales. Según los resultados, la mayor parte de los futuros profesionales disponen de un nivel básicode competencia digital. En el caso de los docentes se determinó que el uso de las herramientas de la web 2.0 causa dificultad en la incorporacióna susprocesos de enseñanza, mientras que los estudiantes tienen un apego al uso de las mismas.La implementación de recursos tecnológicos en el proceso de enseñanza-aprendizaje, promueve un cambio significativo en instituciones de educación superior, estopermitirá formar profesionales capaces de enfrentar la sociedad actual.
A Pilot Microbiota Study in Parkinson’s Disease Patients versus Control Subjects, and Effects of FTY720 and FTY720-Mitoxy Therapies in Parkinsonian and Multiple System Atrophy Mouse Models
Authors: Vidal-Martinez Guadalupe , Chin Brandon , Camarillo Cynthia , Herrera Gloria V. , Yang Barbara , Sarosiek Irene , Perez Ruth G. 
Published: September 2019

Background: Parkinson’s disease (PD) and multiple system atrophy (MSA) patients often suffer from gastrointestinal (GI) dysfunction and GI dysbiosis (microbial imbalance). GI dysfunction also occurs in mouse models of PD and MSA. Objectives: To assess gut dysfunction and dysbiosis in PD subjects as compared to controls, identify potential shared microbial taxa in humans and mouse models of PD and MSA, and to assess the effects of potential therapies on mouse GI microbiota. Methods: In this human pilot study, GI function was assessed by fecal consistency/frequency measured using the Bristol Stool Form Scale and GI transit time assessed using Sitzmarks pills and abdominal radiology. Human and mouse microbiota were analyzed by extracting fecal genomic DNA followed by 16S rRNA sequencing. Results: In our PD patients genera Akkermansia significantly increased while a trend toward increased Bifidobacterium and decreased Prevotella was observed. Families Bacteroidaceae and Lachnospiraceae and genera Prevotella and Bacteroides were detected in both humans and PD mice, suggesting potential shared biomarkers. In mice treated with the approved multiple sclerosis drug, FTY720, or with our FTY720-Mitoxy-derivative, we saw that FTY720 had little effect while FTY720-Mitoxy increased beneficial Ruminococcus and decreased Rickenellaceae family. Conclusion: Akkermansia and Prevotellaceae data reported by others were replicated in our human pilot study suggesting the use of those taxa as potential biomarkers for PD diagnosis. The effect of FTY720-Mitoxy on taxa Rikenellaceae and Ruminococcus and the relevance of S24-7 await further evaluation. It also remains to be determined if mouse microbiota have predictive power for human subjects.