Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular functions of the androgen receptor and BEX2 in breast cancer

2 CHAPTER 1: GENOMIC STUDIES IN BREAST CANCER 1.1 Methodology for gene expression microarrays 3 1.2 Gene expression profiling in primary breast tumors 4 1.3 Discovery of BEX2 in breast cancer using expression profiling 5 CHAPTER 2: MOLECULAR FUNCTIONS OF BEX2 IN BREAST CANCER 2.1 Molecular functions of BEX2 in apoptosis and cell cycle 8 2.2 BEX2 cross-talk with NF-κB, c-Jun/JNK and ErbB2 signaling 12 2.3 Association of BEX2 expression with clinical and pathological features 16 CHAPTER 3: MOLECULAR FUNCTIONS OF AR IN BREAST CANCER 3.1 Signaling cross-talk between AR and the ErbB2/ERK pathway 19 3.2 AR as a therapeutic target in ER-negative breast cancer 22 3.3 Molecular functions of AR target gene, Prolactin-Induced Protein 24 CHAPTER 4: DISCOVERY OF NOVEL AR TARGET GENES 4.1 Investigation of AR transcriptional network in breast cancer 29 4.2 Coagulation Factor VII is an AR target gene 31 4.3 Discovery of a novel protein, C1orf64 (SRARP), as an AR coregulator 32 CHAPTER 5: IMPACT AND APPLICATIONS 36 APPENDIX A: List of Publications (Numbered-Style) 39 APPENDIX B: Bibliography from other sources (Author-Date Style) 43 APPENDIX C: Abbreviations 50 APPENDIX D: Declarations 52 APPENDIX E: Portfolio of Publications 54 APPENDIX F: FORM UPR16-Research Ethics Review Checklist
A Review of On-Orbit Servicing Robot Teleoperation Control System

On-orbit servicing robots were developed to complete the missions in the uncertain and hazards outer space. The operator controls the remote robot via teleoperation systems, which allows the operator to manipulate the robot at a distance. But, as the existing of communication time-delay affects the whole system stability, transparency and other performance index. Consequently, a proper teleoperation system could help the operator to perform missions more accurate. This paper presents the general scheme of the teleoperation system, compares the four typical control modes and estimates methods of time-delay. At last provides an outlook to future research directions.
Deteksi Bot Spammer pada Twitter Berbasis Sentiment Analysis dan Time Interval Entropy

Abstract. Spam is an abuse of messaging undesired by recipients. Those who send spam are called spammers . Popularity of Twitter has attracted spammers to use it as a means to disseminate spam messages. The spam s are characterized by a neutral emotional sentiment or no particular users’ preference perspective. In addition , the regularity of tweeting behavior periodically shows automation performed by bot. T his study propose s a new method to differentiate between bot spammer and legitimate user accounts by integrating the sentiment analysis (SA) based on emotions and time interval entropy (TIE) . The c ombination of knowledge-based and machine learning-based were used to classify tweet s with positive, negative and neutral sentiments. Furthermore , the collection of timestamp is used to calculate the time interval entropy of each account. The r esult s show that the precision and recall of the proposed method reach up to 83% and 91%. This proves that the merging SA and TIE can optimize overall system performance in detecting Bot Spammer. Keywords: bot spammer, twitter, sentiment analysis, polarity, entropy Abstrak. Spam merupakan penyalahgunaan pengiriman pesan tanpa dikehendaki oleh penerimanya, orang yang mengirimkan spam disebut spammer. Ketenaran Twitter mengundang spammer untuk menggunakannya sebagai sarana menyebarluaskan pesan spam. Karakteristik dari tweet yang dikategorikan spam memiliki sentimen emosi netral atau tidak ada preferensi tertentu terhadap suatu perspektif dari user yang memposting tweet. Selain itu keteraturan waktu perilaku saat memposting tweet secara periodik menunjukkan otomatisasi yang dilakukan bot. Pada penelitian ini diusulkan metode baru untuk mendeteksi antara bot spammer dan legitimate user dengan mengintegrasikan sentimen analysis berdasarkan emosi dan time interval entropy. Pendekatan gabungan knowledge-based dan machine learning-based digunakan untuk mengklasifikasi tweet yang memiliki sentimen positif, negatif dan tweet netral. Selanjutnya kumpulan timestamp digunakan untuk menghitung time interval entropy dari tiap akun. Hasil percobaan menunjukan bahwa precision dan recall dari metode yang diusulkan mencapai 83% dan 91%. Hal ini membuktikan penggabungan Sentiment Analysis ( SA ) dan Time Interval Entropy ( TIE ) dapat mengoptimalkan performa sistem secara keseluruhan dalam mendeteksi Bot Spammer. Kata Kunci: bot spammer, twitter, sentiment analysis, polarity, entropy
Design of campus geographic information system based on MapObjects

In order to help campus administration to work in an informational,scientific and visual way,the method on how to integrate the GIS technology with the campus administration system is studies based on the analysis of the characteristics of the current campus in-formation.Then,campus geographic information system is established based on Mapobjects,and its architecture framework,functional design,database design and implementation technology are also expatiated in detail.At last,combined with the applied example,the method of design and application is proposed.
Brain-Derived Neurotropic Factor Serum Level and Severity Symptom of Bataknese Male Patients with Schizophrenia in North Sumatera, Indonesia

BACKGROUND: Schizophrenia is a severe mental disorder that is multi-causative and multi-factor, generally affecting about 1% of the population. The elevation level of brain-derived neurotrophic factor (BDNF) offers several protections from other neurodegenerative processes that occur in schizophrenia since this deficit of neurotrophic factors can contribute to changes in brain structure and function that underlie the schizophrenia psychopathology. AIM: To analyse the correlation between BDNF serum levels and symptom severity by using the Positive and Negative Syndrome Scale (PANSS) instrument in Bataknese male patients with schizophrenia METHODS: This study was a correlative analytical study with a cross-sectional approach using the Positive and Negative Syndrome Scale (PANSS) instrument to assess symptom severity with 60 subjects of Bataknese male patients with chronic schizophrenia. Moreover, this research was conducted at the Psychiatric Hospital of Prof. Dr M. Ildrem Medan, Indonesia. BDNF serum was analysed with the Quantitative sandwich enzyme immunoassay technique by via Quantikine ELISA Human CXCL8/IL-8 HS. Also, the data analysis was performed through Spearman’s correlative bivariate analytics using SPSS software. RESULTS: A negative correlation between the BDNF serum level and the negative scale PANSS score in men with schizophrenia (r = -0.820, p < 0.001) was found. Moreover, there is a negative correlation between BDNF serum levels and PANSS total scores in men with schizophrenia (r = -0.648, p < 0.001) CONCLUSION: BDNF serum level in Bataknese male patients with schizophrenia has a relationship that affects the severity of symptoms in schizophrenic patients, especially for negative symptoms.
A Complaint from Citizens for Sludge-Free Land

Citizens for Sludge-Free Land has learned that the proceedings of a recent workshop paper, promoting the land application of biosolids,—processed sewage sludge—were published under the imprimatur of the American Society for Microbiology (1). Ignoring mounting evidence that links biosolids-exposure to serious environmental and health problems, the authors argue that biosolids use is safer than non-CAFO animal manure, because the former is highly regulated. This view is increasingly being challenged by the scientific community.
Applications of Chitosan in Pulmonary Drug Delivery

Pulmonary administration is an effective method for treating lung and other diseases. Drugs can be transported directly to the lung by the pulmonary drug delivery system (PDDS). PDDS has the advantages of maintained local drug concentration, reduced side effects, controllable drug release, promoted drug absorption, prolonged drug action time, and improved patient compliance. Polymers have been extensively utilized to prepare novel PDDS. Among these polymers, chitosan (CS) is a natural cationic polysaccharide which is rich in its source. It has many unique physicochemical properties, good biocompatibility, and satisfactory biodegradability. CS has been a popular biomaterial in pharmaceutics for decades and is widely used in drug delivery. CS contains many amino groups. The contained positive charges can interact strongly with the negatively charged mucosa membranes, thereby facilitating CS adsorption on the mucosal surface, avoiding clearance by the cilia, and improving the adhesion and penetration rate on the cell membrane. Moreover, studies have shown that CS could open cell tight junctions, which would promote drug transportation across the epithelial tissue. Thus, CS is an especially suitable material for PDDS. In this chapter, we will focus on the research progress and the applications of CS in PDDS. Many representative and advanced studies on CS-based PDDS are reviewed in detail.
Research on Hearing Errors and Experimental Verification of Operator on Digitalized Human-machine Interface

This article makes a experimental validation study on hearing error of operator on digitalized human-machine interface.The experiment set up a control group and an experimental group,the experimental group is divided into visual interference and manual interference,while the visual interference includes digital interference,graph interference and color interference.The experiment results show that the control group's hearing error rate is 0.02%,average reaction time is 6.51s;while on digital interference,the hearing error rate is 0.33%,average reaction time is 14.81s;on graph interference,the hearing error rate is 0.15%,average reaction time is 12.32s;on color interference,the hearing error rate is 0.04%,average reaction time is 9.07s;on manual interference,the hearing error rate is 0.58%,average reaction time is 7.89 s.On the basis of SPSS analysis,we find the results that different interference have significant influence on hearing error and reaction time.
Antimicrobial resistant superbug warning watch: a newly emerged Klebsiella pneumoniae and Mycoplasma genitalium joining the group

One of the Gram-negative bacteria that may turn into a harmful organism is known as Klebsiella pneumoniae. K. pneumoniae is a normal intestinal flora in human, but it can cause dangerous infections if it reaches other parts of the body such as lungs, blood, or wounds. The risk of infection from this microbe may increase with people with specific health conditions or troubles ex. cancer, lung diseases, alcoholism, liver problems and kidney failure. This microorganism may turn into a superbug that can resist the most commonly known antibiotics [3]. Recently fatal cases have been reported in hospitals where hyper-virulent and hyper-resistant strains of K. pneumoniae were isolated [4, 5]. Even some strains have been shown to be almost resistant to all antibiotics, others are flesh eating and may cause blindness and meningitis [The wire, https://thewire.in/health/superbug-india, Last accessed on 13/12/2018; Telegraph, https://www.telegraph. co.uk/news/2018/12/07/dangerous-new-superbug-confirmed-india-antibioticresistance/, Last accessed on 13/12/2018]. The frequency of this trend of resistance and virulence seems to be rising with time globally.
Research on Face Recognition Based on Back Propagation Neural Network

A new method, face recognition based on back propagation neural network, is presented in this paper. The proposed method extracts feature from face image with differential projection and geometrical features into eigenvector which is classified by back propagation neural network. Besides our method, the principal component analysis (PCA)-based method, the linear discriminated analysis (LDA)-based method and the Markov Random Fields (MRF)-based method were also tested for comparisons. The experimental results on ORL face database show that the proposed method achieves an average recognition accuracy of over 98% by using only 13 features. Moreover, the recognition accuracy is enhanced effectively, and the computational complexity and feature dimensions are reduced greatly.
Multilevel Methods for Sparsification and Linear Arrangement Problems on Networks

The computation of network properties such as diameter, centrality indices, and paths on networks may become a major bottleneck in the analysis of network if the network is large. Scalable approximation algorithms, heuristics and structure preserving network sparsification methods play an important role in modern network analysis. In the first part of this thesis, we develop a robust network sparsification method that enables filtering of either, so called, longand short-range edges or both. Edges are first ranked by their algebraic distances and then sampled. Furthermore, we also combine this method with a multilevel framework to provide a multilevel sparsification framework that can control the sparsification process at different coarsegrained resolutions. Experimental results demonstrate an effectiveness of the proposed methods without significant loss in a quality of computed network properties. In the second part of the thesis, we introduce asymmetric coarsening schemes for multilevel algorithms developed for linear arrangement problems. Effectiveness of the set of coarse variables, and the corresponding interpolation matrix is the central problem in any multigrid algorithm. We are pushing the boundaries of fast maximum weighted matching algorithms for coarsening schemes on graphs by introducing novel ideas for asymmetric coupling between coarse and fine variables of the problem.
A prospective study on emergency laparoscopic or open cholecystectomy in acute cholecystitis in a tertiary care hospital

Background: Gallstones are among one of the most common diseases affecting the digestive system requiring hospitalisation with a prevalence of 11% to 36%. Until 2 decades ago, patients presenting with acute cholecystitis were treated conservatively and a delayed interval cholecystectomy was performed after 6 weeks, now a days laparoscopic cholecystectomy was gaining popularity in acute cholecystitis. It cannot be said with certainty preoperatively whether the cholecystectomy is going to be easy or difficult. The aim of the study was to evaluate safety and outcomes of emergency laparoscopic or open cholecystectomy in acute cholecystitis.Methods: This is a prospective, observational, single centre study conducted in the Department of General Surgery, S.V. Medical College/ SVRRGG hospital, Tirupati, for a period of one year from the time of approval of IEC. All patients undergoing emergency laparoscopic or open cholecystectomy for acute cholecystitis and its related complications are studied for various clinical, radiological and other variables.Results: Total 100 patients who presented with acute cholecystitis and undergone cholecystectomy are studied. Age, sex, BMI, comorbities, clinical and usg criteria and intra-operative findings and post-operative complications are analysed.Conclusions: Difficult dissection in cholecystectomy can be predicted using pre-operative parameters like increasing age, male gender, multiple attacks in the past, gallbladder wall thickness >3 mm, and presence of pericholecystic fluid. Surgery performed within 72 hrs had good prognosis and few intra op complications due to good place of dissection due to inflammation.
Concurrent SHORT syndrome and 3q duplication syndrome

Patients with an extremely rare missense mutation in the phosphoinositide-3-kinase, regulatory subunit 1 (PIK3R1) gene present with an array of symptoms described as SHORT syndrome [1]. SHORT is a mnemonic representing six manifestations of the syndrome: short stature, hyperextensibility of joints, inguinal hernia, ocular depression, Rieger anomaly (malformation of the anterior chamber of the eyeball), and teething delay [2]. Other primary features of SHORT syndrome not included in the mnemonic are lipodystrophy, intrauterine growth restriction (IUGR), hearing loss, vision loss, insulin resistance, delayed growth, and facial gestalt. The facial gestalt of SHORT syndrome is comprised of a combination of slightly varying case-specific facial features including triangular face, prominent forehead, hypoplastic alae nasi, midface hypoplasia, micrognathia, large low-set ears, thin lip with downturned mouth, and progeroid face. The condition has a worldwide incidence of <1/1,000,000 and there have been less than 50 cases of SHORT syndrome reported in literature since the recognition and naming of the
Simple spike dynamics of Purkinje cells in the macaque vestibulo-cerebellum reflect sensory prediction error

Theories of cerebellar functions posit that the cerebellum implements forward models for online correction of motor actions and sensory estimation. As an example of such computations, a forward model compensates for a sensory ambiguity where the peripheral otolith organs in the inner ear sense both head tilts and translations. Here we exploit the response dynamics of two functionally-coupled Purkinje cell types in the caudal vermis to understand their role in this computation. We find that one population encodes tilt velocity, whereas the other, translation-selective, population encodes linear acceleration. Using a dynamical model, we further show that these signals likely represent sensory prediction error for the on-line updating of tilt and translation estimates. These properties also reveal the need for temporal integration between the tilt-selective velocity and translation-selective acceleration population signals. We show that a simple model incorporating a biologically plausible short time constant can mediate the required temporal integration.
Anesthetic Considerations for Liver Transplantation in a Patient with Mitochondrial Neurogastrointestinal Encephalopathy Syndrome

Mitochondrial neurogastrointestinal encephalopathy (MNGIE) is a rare, complex mitochondrial disorder with variable phenotypes caused by a defect in the TYMP gene that codes for the thymidine phosphorylase enzyme. Orthotopic liver transplantation (OLT) has been proposed as a curative option for patients by using the liver as a source to restore thymidine phosphorylase levels in the body. Anesthetic considerations for this syndrome have not been clearly outlined in the past. We describe the clinical presentation of a young woman with MNGIE, her perioperative assessment, and intraoperative management during liver transplantation.
Urinary NGAL and KIM-1 Are the Early Detecting Biomarkers of Preterm Infants with Acute Kidney Injury

Background: Acute kidney injury (AKI) is common in neonates. However, early diagnosis is difficult. Different biomarkers for early diagnosis of AKI, such as NGAL, KIM-1, Cys-C, IL-18, β2-microglobulin have been proposed. But regarding premature infant, there is very little research that has been reported. Objectives: To investigate the role of urinary NGAL and Kim-1 biomarkers for early diagnosis of AKI in premature neonates. Methods: Eighty cases were divided into experimental group (60 cases) and controls group (20 cases). Of 60 cases, 24 patients met the criteria for AKI group; the remaining 36 were non-AKI group. Blood and urine samples, 1 ml each, were collected from all subjects at first day, second day, third day and seventh day of life. Urine NGAL and KIM-1 were measured by ELISA. Results: The urinary NGAL and KIM-1 are significantly higher in AKI group than Non-AKI group and normal control group in the first three days. They present earlier than classical Scr. Conclusion: Urinay NGAL and Kim-1 are beneficial biomarkers for the early diagnosis of AKI in preterm neonates.
Enterovirus 71 3C Protease Does Not Disrupt Interferon Type I Signaling Pathway

Background: The 3C protease is one of the most important proteases in enteroviruses which is responsible for several cleavages on viral polyproteins and maturation processes. Some reports indicated that this protease disrupts the interferon (IFN) signaling pathway; however, another report shows that 3C protease does not have such inhibitory effects on IFN signaling. Objectives: In this study, a construction was designed consisting of 3C protease to test its effects on Interferon type I signaling
Translation of openmp to dataflow execution model for data locality and efficient parallel execution

OpenMP has become widely accepted for shared-memory programming. It is not only easier for a non-expert programmer to develop a parallel application under OpenMP than in the de facto message-passing standard MPI, but it is also possible to incrementally develop portable OpenMP applications. However, it is up to the user to ensure that performance does not suffer as a result of poor cache locality or high synchronization overheads: poor data locality and barrier synchronizations have a particularly large impact on the performance of applications on cache coherent Non-Uniform Memory Access (ccNUMA) machines. Moreover, most OpenMP compilers perform little or no optimization. In this dissertation, we propose the translation of OpenMP to a data flow execution model realized by using the SMARTS runtime system instead of translating it directly to a multi-threaded program as most compilers do. Our goal is to perform analyses that will enable us to improve the data locality as well as reduce synchronization overheads. The compiler transforms an OpenMP code to a collection of sequential tasks and a task graph that indicates their execution constraints. It then specifies the mapping of tasks to processors (or equivalently, to threads that are bound to processors). Eliminating constraints in the task graph, and finding a good compile-time mapping of nodes of the task graph to the processors for data locality reuse, are the main components of the transformation. Our experimental results show that our strategy can outperform straightforward OpenMP code, and that the resulting code also scales well.
Factors Associated With Osteoporosis Care of Men Hospitalized for Hip Fracture: A Retrospective Cohort Study

Rates of postfracture DXA and pharmacotherapy appear to be declining despite their known benefits in fracture reduction. We sought to identify factors associated with osteoporosis care among male veterans aged 50 years and older after hip fracture and to evaluate trends in rates of care with an observational cohort design using US Department of Veterans Affairs’ (VA) inpatient, pharmacy, and outpatient encounters and Centers for Medicare and Medicaid Services outpatient pharmacy claims (2007 to 2014) from men aged 50 years and older treated for hip fracture (N = 7317). We used the Cox proportional hazards model with random effects for the admitting facility. A sensitivity analysis was performed for a subset of patients aged 65 to 99 dually enrolled in Medicare ( N = 5821). Overall, approximately 13% of patients had evidence of osteoporosis care within one year of fracture. In the adjusted model, rural residence was associated with lower likelihood of care, and several comorbidities were associated with higher likelihood of receiving care. In sensitivity analyses of patients dually enrolled in Medicare, rural residence remained associated with lower likelihood of osteoporosis care. Overall rates of care decreased over time, but rates of DXA in the VA remained stable. These findings highlight the ongoing problem of low rates of postfracture care among a population with the highest risk of future fracture and its associated morbidity and mortality. The rural disparity in care and differences in rates of care across healthcare delivery systems illustrates the importance of healthcare delivery systems in promoting pharmacotherapy and DXA after sentinel events. Because the VA removes a majority of cost barriers to care, this integrated healthcare system may outperform the private sector in access to care. However, declining rates of pharmacotherapy imply knowledge gaps that undermine quality care. © 2019 The Authors. JBMR Plus is published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.