Miracle-dz/UniFAR-FTUs huggingface dataset:
LDLC encodes a peripheral golgi protein required for normal Golgi function

IdlB and IdlC are two previously isolated classes of CHO cell mutant, with LDL receptor deficiencies and broad glycosylation defects. These mutant cells exhibit a broad set of defects in processing reactions within the Golgi apparatus, affecting virtually all Nand O-linked glycoproteins, and glycolipids. The LDL receptor deficiency in IdlB and IdlC cells is a secondary consequence of the Golgi processing defects. I have conducted a molecular analysis of IdlC mutant cells, to determine how a single defect can affect multiple reactions within the Golgi. I have cloned by complementation a human cDNA (LDLC) that fully corrects the mutant phenotypes when transfected into IdlC cells. The LDLC cDNA did not correct the apparently identical mutant phenotypes in IdlB cells. By Northern blot analysis, the endogenous LDLC mRNA was clearly expressed in wild-type CHO cells but not in IdlC mutant cells, suggesting that the LDLC cDNA is a normal human counterpart to the defective gene of IdlC cells. The LDLC cDNA was shown by sequence analysis to encode a protein (IdlCp) that was not similar in sequence to other known proteins. IdlCp has a predicted size of 83 kilodaltons, and contains no common structural motifs such as transmembrane domains or translocation signal sequences. Site-directed mutations introduced into the LDLC cDNA indicated that an amino-terminal portion of IdlCp may be dispensable for function. A cDNA related to the human LDLC cDNA was cloned from Caenorhabditis elegans, to extend the LDLC sequence analysis. It encodes a distant homolog of IdlCp, indicating that IdlCp mediates conserved cellular functions. This cDNA was physically mapped within the Caenorhabditis elegans genome, and several genetic loci were identified as LDLC candidates. Antibodies were raised against IdlCp, and used for immunofluorescence localization studies. In wild-type CHO cells, IdlCp colocalized with Golgi markers. Localization was disrupted by short treatment with the drug brefeldin A, which dissociates known peripheral proteins such as betaCOP from the Golgi. In IdlB cells, IdlCp was expressed at normal levels but was not localized to the Golgi. Together, these results demonstrate that IdlCp is a peripheral Golgi protein that requires the putative LDLB gene for Golgi localization. Thesis Supervisor: Dr. Monty Krieger Title: Professor of Biology
Ecology, the ascendent perspective

Ecology, Ulanowicz argues, needs a more robust central paradigm, and this book presents one derived from current work in information theory, ecosystem energetics, and complexity theory; the result is a theoretical and empirical tool kit better able to measure the developmental status of any living community. Ranging widely to explore critical issues in the history of science-order, causality, progress, laws-Ulanowicz sets forth a coherent theoretical framework for ecology. He demonstrates that mechanical models can capture behavior of relatively simple, isolated populations, but fail to explain the rich, complex, and sometimes unpredictable mix of order and disorder that characterizes larger systems. A challenge to existing Newtonian and Darwinian paradigms, this book suggests ways to bring ecology from the fringes to the center of science.
Pengenalan Karakter Jawi Tulisan Tangan Menggunakan Fitur Sudut

Abstrak— Karakter Jawi salah satu varian karakter Arab adalah karakter Jawi. Karakter tersebut mengakomodasi penulisan bahasa Melayu. Karakter Jawi banyak digunakan oleh kerajaan Islam di Nusantara sehingga banyak dokumen menggunakan karakter tersebut. Untuk menjaga kelestarian dokumen tersebut maka karakter Jawi tersebut harus di rubah kedalam format digital, salah satu caranya adalah dengan metode Optical Character Recognition (OCR). Salah satu metode OCR dalam mengekstraksi fitur adalah menggunakan sudut yang dibentuk dari bagian utama karakter. Fitur yang dihasilkan dari sudut tersebut digunakan oleh SVM untuk di klasifikasi kedalam karakter Jawi. Dengan menggunakan fitur tersebut, SVM mampu mengklasifikasi karakter Jawi dengan tingkat akurasi rata-rata sebesar 78,86%. Abstract— The Jawi character is one variant of Arabic characters that adopts Malay language writing. The character of Jawi is widely used by the Islamic kingdom in the Archipelago. Many document written using these characters. To preserve the history and the book, the Jawi character need to be converted into digital form, one way is by Optical Character Recognition (OCR) method. One method of OCR in extracting features is to use angles formed by main part of the character. The features generated are used by SVM to be classified into Jawi characters. By using these features, SVM is able to classify Jawi characters with an average level of accuracy of 78.86%.
Concept Paper: A Multidimensional Assessment Approach of Talent Identification in Male Youth Malaysia Football Players

The main aim of this study is to identify the factors which influence playing ability performance in the identification process of young football talent as a whole. The evidences from the previous studies, Phase 1 National Football Development Plan:2014-2020 and the Roadmap of Malaysia Football Association: 2019-2030 shows that holistic approach in the process of identifying young talent is the main key in the development of a national football. The three main constraints were tasks, performers’ and the environmental which involve the factors of training history, morphological, functional capacity, motor coordination, technical skills, tactical skills, psychological characteristics, biological maturity status, relative age effect and sociological which provide large influence to the football playing ability performance among the male youth football players. Both Newell (1986) constraint theory and Williams & Reilly (2000) the football expertise prediction model are able to explain the relationship between variables which is related to the multidimensional assessment approach in identifying the young talent of football.
The Current State of Dental Sleep Medicine Practice in Academic Institutions: A
 Questionnaire-Based Study

Study Objectives: The aim of this study is to evaluate the current state of dental sleep medicine practice at the United States and Canada academic institutions. Methods: An electronic survey created in Qualtrics was sent via email. The survey was sent to the 76 dental schools academic institute in the United States and Canada, 16 of which were known to have a dental sleep medicine clinic. The survey was emailed to the program directors of the sleep medicine clinics at these dental schools. For the remaining 60 schools that do not have a dental sleep medicine program, the survey was instead sent to the academic dean. The multiple choice 21-item survey was validated and received Institutional Review Board approval. Results: The response rate was 37% (28 schools), of which 86% were in the United States. Of the respondents, 45% (12 schools) had a dental sleep medicine clinic. The dental sleep medicine clinics were either an independent/ part of diagnostic services (42%) or incorporated with other departments. Almost 33% of the schools that have a sleep medicine clinic reported difficulty integrating sleep medicine into other existing programs. Eighty-three percent of respondents reported the presence of one to two board certified dental sleep medicine faculty members, whereas the remaining schools did not have any. Conclusions: This current study indicates that dental sleep medicine in academic institutions is faced with many obstacles that need to be addressed. Dental sleep medicine is a growing field that needs more attention from educational institutes. Also, the positive effect of having board-certified dental sleep medicine faculty should be noted.
Ameliorative Effects of Spirulina and Chamomile Aqueous Extract against Mice Bearing Ehrlich Solid Tumor Induced Apoptosis

This work was carried out in collaboration among all authors. Authors AEA and ET designed the study, performed the statistical analysis and wrote the protocol. Authors EEE, AM and MAZ the first draft of the manuscript, managed the literature searches and managed the analyses of the study. ‘All authors read and approved the final manuscript. ABSTRACT Aims: Cancer is caused by an imbalance in the rate of proliferation and apoptosis and the positive effect of anticancer therapy is taken into consideration when its ability to initiate apoptosis in cancer cells . In vivo; Results: In the current study; a significant decrease in tumour volume, an decrease in apoptotic P53, Bax and pro apoptotic Caspase 3 expressions and increased in Bcl2 expressions was detected after the treatment of EST with extract of chamomile and spirulina together and spirulina extract only as compared with the tumour volume of EST group. In conclusion, the present study demonstrated that the combination of spirulina and chamomile has a better effect than each of spirulina or chamomile alone against Ehrlich solid tumor in mice. Conclusion: Ehrlich solid tumor induced apoptosis by increased P53, Bax, Caspase 3 and decrease Bcl2; treatment of Ehrlich solid tumor with combination of spirulina and chamomile improved these alterations in apoptosis markers.
Effects of Lippia sidoides Cham. (Verbenaceae) essential oils on the honey bees, Apis mellifera (Apidae: Hymenoptera), foraging

The use of plant essential oils has been adopted as less hazardous to the environment and human health than synthetic insecticides used for the control of insects that transmit diseases. Despite of exerting insecticidal activities against several insect disease vectors, the potential impacts on non-target organisms exerted by essential oils extracted from Lippia sidoides (Cham.) have not received adequate attention. Here, we evaluated the susceptibility and potential changes in consumption rates of honey bees, Apis mellifera (L.), when exposed to essential oils extracted from L. sidoides. Was exposed forager bees to honey syrup (50% v/v) containing L. sidoides essential oil for 5 h. After this exposure period, the bees received regular honey syrup for another 19 h period. Six essential oil concentrations was used, namely 1.0, 1.5, 2.0, 2.5, 3.0 and 3.5 µL of essential oil/mL of syrup, and evaluated the syrup consumption and bees mortality in both periods (at the 5th and 24th h). The results reveal that independent of the essential oil concentration, the forager bees fed significantly less on L. sidoides essential oil-containing honey syrup. However, feeding on L. sidoides essential oil-containing honey syrup did not cause significant mortality when compared with bees that were not exposed to the essential oils. Thus, the results demonstrate that L. sidoides essential oils exhibited adequate selectivity against honey bees.
Endotoxin/Lipopolysaccharide Activates NF-κB and Enhances Tumor Cell Adhesion and Invasion Through a β1 Integrin-Dependent Mechanism

β1 integrins play a crucial role in supporting tumor cell attachment to and invasion into the extracellular matrix. Endotoxin/LPS introduced by surgery has been shown to enhance tumor metastasis in a murine model. Here we show the direct effect of LPS on tumor cell adhesion and invasion in extracellular matrix proteins through a β1 integrin-dependent pathway. The human colorectal tumor cell lines SW480 and SW620 constitutively expressed high levels of the β1 subunit, whereas various low levels of α1, α2, α4, and α6 expression were detected. SW480 and SW620 did not express membrane-bound CD14; however, LPS in the presence of soluble CD14 (sCD14) significantly up-regulated β1 integrin expression; enhanced tumor cell attachment to fibronectin, collagen I, and laminin; and strongly promoted tumor cell invasion through the Matrigel. Anti-β1 blocking mAbs (4B4 and 6S6) abrogated LPS- plus sCD14-induced tumor cell adhesion and invasion. Furthermore, LPS, when combined with sCD14, resulted in NF-κB activation in both SW480 and SW620 cells. Inhibition of the NF-κB pathway significantly attenuated LPS-induced up-regulation of β1 integrin expression and prevented tumor cell adhesion and invasion. These results provide direct evidence that although SW480 and SW620 cells do not express membrane-bound CD14, LPS in the presence of sCD14 can activate NF-κB, up-regulate β1 integrin expression, and subsequently promote tumor cell adhesion and invasion. Moreover, LPS-induced tumor cell attachment to and invasion through extracellular matrix proteins is β1 subunit-dependent.
PENGARUH CORPORATE SOCIAL RESPONSIBILITY, UKURAN PERUSAHAAN, LEVERAGE, DAN STRUKTUR KEPEMILIKAN TERHADAP AGRESIVITAS PAJAK

The study aims to examine whether corporate social responsibility, firm size, leverage, foreign and public ownership structure affect on the tax aggressiveness. Tax aggressiveness is downward management of taxable income through tax planning activities. Population in this study are manufacturing companies listed on the Indonesia Stock Exchange (IDX) during the period 2014-2017. Samples in this study are 100 companies, that were collected by using purposive sampling method based on certain criteria. The method of analysis used is multiple regression. The results show that firm size and public ownership have significant effect to the tax aggressiveness. These results prove that the larger of firm size and public ownership, the greater possibility of the company’s tax aggressiveness. On the other hand, corporate social responsibility, leverage, and foreign ownership does not have significant effect to tax aggressiveness. This results indicate that the higher corporate social responsibility, leverage and foreign ownership cause the possibility of companies not to behave aggressively in taxes.
Location Estimation Accuracy of Augmented Arrays for Millimeter-Wave FMCW-MIMO Radar

In this paper, we examine the performance of location estimation with various estimation methods for the millimeter-wave frequency modulated continuous wave (FMCW)-MIMO radar. We do not aim for any novel estimation method but evaluate the resolution of angle and distance estimation in great detail through simulation and experiments. We found through our simulation and experimental results that Khatri-Rao (KR) product extension is often effective for the radar and can well improve the accuracy of location estimation. We clarify the properties and drawbacks of the location estimation methods through our simulation and experimental results.
Prediction of bird community composition based on point‐occurrence data and inferential algorithms: a valuable tool in biodiversity assessments

Local biological communities are made up of species, each of which has its own particular relationship with the environment. To the extent that these autecological niches limit species’ distributions, and by extension community composition, models of species’ ecological niches can predict species composition at particular sites, or at least provide a null hypothesis of potential species composition in the absence of effects of species interactions. We developed distributional predictions (ecological niche models) for 89 species occurring in dry tropical forest in the Balsas Basin of south-western Mexico using an interpolation technique, and predicted the species likely to occur at 8 sites across the region. Onsite field inventory data were then used to test the community predictions, all of which were statistically significant. These results suggest that inventory efforts can be made more efficient by development beforehand of hypotheses that focus onsite collecting and inventory.
Fine resolution 30-year climatic wind energy dataset over China for renewable energy assessment and operation via Weather Research and Forecasting model hindcast

One of the greatest obstacles in the exploitation of wind and solar energy is their intermittency and fluctuation. Long-term dataset of wind energy resource, which is built on basis of atmospheric numerical models, has been proved to be the most effective approach for wind energy resource assessment in wide area, on grid level and in fine resolution, as well as renewable energy electric energy capability forecast, site planning and dispatch/ operation schedule making of power system. To improve the accuracy of wind energy resource dataset by numerical models, the Weather Research and Forecasting model (WRF) and the Climate Four-Dimensional Data Assimilation (CFDDA) are adopted to conduct a sensitivity experiment, in 9 km spatial resolution, to distinguish a reliable model configuration in this study. Based on the statistics between WRF-CFDDA model output in hub-height wind speed and in-situ observations (sited on typical wind farms in Gansu, Xinjiang and Jilin province, 2010-2013), it has been confirmed that the model configuration with MERRA2 background field, Topowind topographic correction method and smoothed VASSO (VAriance of Sub-grid Scale Orography) terrain data is the most reasonable one, with a correlation coefficient 0.79 and RMSE 1.62 for 10-m height wind speed. Following this configuration, with assimilating all 30-year (1987-2016) ground-based meteorological observation from Chinese international exchange sites, the wind energy resource from 1987 to 2016 around China has been hindcasted and assessed in a resolution of 9 km, 15 min. The hindcast is capable to reproduce the characteristics in temporal and spatial distribution. This model system can be a reliable tool for reproducing decades of reanalyzed climatology and finer resolution assessment on hub-height wind energy, moreover, for reconstruction of typical wind power output curve.
Theta, Alpha and Beta Activity in the Occipital Based on EEG Signals for Mental Fatigue in High School Students

Excessive physical and cognitive activity is believed to be the cause of a person experiencing mental fatigue. Meanwhile, one of the factors that cause acute illness is mental fatigue. Thus mental fatigue has been identified as one of the life-threatening factors in the human population, especially in high school students. In this paper, we use the EEG signal to analyze mental fatigue conditions in the occipital region. We also develop cognitive tasks as stimuli for mental fatigue. Theta, alpha, and beta waves activity from EEG signals are used to compare mental fatigue conditions with normal conditions in each subject. Afterward, the time domain is analyzed using the standard deviation and the mean absolute value (MAV). Meanwhile, the IOWA Fatigue Scale (IFS) questionnaire was used as a subjective reference. Finally, it was found that when the subject suffered mental fatigue an increase in the 2 features of the EEG signal was greater than normal conditions, between the pre-task and post-task in the occipital O1 and O2 channels. In general, an increase in the 2 features of the EEG signal occurs in theta, alpha, and beta waves. From this study by analyzing brain waves in the occipital area, it was concluded that high school students who attend school for approximately 8 hours a day have the potential to experience mental fatigue.
Internet of Things & Cloud Computing Internet of Things as a Service Approach

this paper discusses the challenges that arise from Internet of Things and Cloud Computing Integration. We propose a general architecture called Internet of Things as a Service that address these challenges and offers a comprehensive solution for different Internet of Things applications. The architecture utilizes the current cloud services or suggests adding new ones to support various applications. To validate the architecture, we apply use cases from smart city scenarios.
Energy Recovery Study by the Anaerobic Digestion of Dairy Dludge from Moroccan Industry

Food chains in general and dairy industries in particular increase from one year to the other; which generates enormous waste, the management of these waste concerned producers. The aim of this study is the energy estimation of the dairy industry sludge. Anaerobic digestion of the dairy sludge (DS) is conducted in a CSTR digester (continuous stirred tank reactor) at mesophilic temperature conditions (37C°) with a retention time of 45 days. The results obtained show that this dairy sludge(DS) has an encouraging proportion of volatile solids around 88 %, the maximum methanogenic yield potential reached 434 (NmL / g VS added) and the biodegradability recorded was 96 % at these conditions. In this context, one tone of dairy sludge could generate approximately 57kwh/year of electric power through the anaerobic digestion process. This will reduce considerably the industries of electrical energy consumption.
Detection of PD Activities in XLPE Cable Using UHF Antennas

Underground cables are widely used in urban areas for electrical power transfer, and some of those cables are very old. These cable insulations are often subjected to partial discharges due to aging which, gradually degrades dielectric strength of the insulation and ultimately results in complete failure. Therefore, detection of partial discharge (PD) within the insulation of cross-linked polyethylene (XLPE) cable may help to get an early warning about the fault condition. This paper reports about initial results obtained from the measurement of PD activities within XLPE cable using standard electrical method and UHF method.
Evaluating and Boosting Reinforcement Learning for Intra-Domain Routing

The success of machine learning in domains such as computer vision and computer games has triggered a surge of interest in applying machine learning in computer networks. This paper tries to answer a broadly-debated question: can we improve the performance of intradomain routing, one of the most fundamental blocks in the Internet, with reinforcement learning (RL)? Due to the complex network traffic conditions and the large action space in routing, it is difficult to give a definite answer for existing RL-based routing solutions. To gain an in-depth understanding on the challenges of RL-based routing, we systematically classify different RL-based routing solutions and investigate the performance of several representative approaches, in terms of scalability, stability, robustness, and convergence. With the lessons learned in evaluating various RL-based routing solutions, we propose two methods, called supervised Q-network routing (SQR) and discrete link weight-based routing (DLWR), which boost the performance of RL-based routing and outperform the de facto shortest path intradomain routing.
Real-Time Vehicle Traffic Analysis using Long Short Term Memory Networks in Apache Spark

Escalating traffic congestion in large and rapidly evolving metropolitan areas all around the world is one of the inescapable problems in our daily lives. In light of this situation, traffic monitoring and analytics is becoming the need of the hour. Real-time traffic analysis requires the processing of data streams that are generated continuously to gain quick insights. In order to processes stream data at a faster rate, we need technologies with high computing capacity. Big data frameworks such as Apache Hadoop, Spark and Kafka, with their capability of processing a massive amount of data, have made it possible to develop advanced and efficient data stream processing systems. The challenge of analyzing data streams for real-time prediction can be overcome by exploiting deep learning techniques. Taking this as a motivation, this work aims at developing a real-time data stream processing model for forecasting vehicle traffic, using Long Short-Term Memory (LSTM) networks to learn and train itself from traffic data. In the proposed analytical framework, the traffic data from an API is streamed using a distributed streaming platform called Kafka into the machine learning model in Apache Spark for analysis. The proposed model is aimed at predicting traffic flow information by integrating Spark and Kafka along with deep neural networks, that will be of great value to the citizens as well as the government by reducing the travel time, cost and energy, thus having a positive impact on the environment and the society.