Miracle-dz/UniFAR-FTUs huggingface dataset:
SILAC-Based Quantification of TGFBR2-Regulated Protein Expression in Extracellular Vesicles of Microsatellite Unstable Colorectal Cancers

Microsatellite unstable (MSI) colorectal cancers (CRCs) are characterized by mutational inactivation of Transforming Growth Factor Beta Receptor Type 2 (TGFBR2). TGFBR2-deficient CRCs present altered target gene and protein expression. Such cellular alterations modulate the content of CRC-derived extracellular vesicles (EVs). EVs function as couriers of proteins, nucleic acids, and lipids in intercellular communication. At a qualitative level, we have previously shown that TGFBR2 deficiency causes overall alterations in the EV protein content. To deepen the basic understanding of altered protein dynamics, this work aimed to determine TGFBR2-dependent EV protein signatures in a quantitative manner. Using a stable isotope labeling with amino acids in cell culture (SILAC) approach for mass spectrometry-based quantification, 48 TGFBR2-regulated proteins were identified in MSI CRC-derived EVs. Overall, TGFBR2 deficiency caused upregulation of several EV proteins related to the extracellular matrix and nucleosome as well as downregulation of proteasome-associated proteins. The present study emphasizes the general overlap of proteins between EVs and their parental CRC cells but also highlights the impact of TGFBR2 deficiency on EV protein composition. From a clinical perspective, TGFBR2-regulated quantitative differences of protein expression in EVs might nominate novel biomarkers for liquid biopsy-based MSI typing in the future.
Factors Affecting Financial Performance of Small and Medium Enterprises ( SMEs ) : A Case of Manufacturing SMEs in Kenya

Small and Medium Enterprises (SMEs) have stake in most economies across the world. SMEs play a major central role in regard to entrepreneur skills, innovation and employment (Kinyua A., 2014). World Bank Group (2015) report indicates that formal SMEs contribute to 45 and 33 percent to total employment and Gross Domestic Product (GDP) respectively in emerging economies. According to World Bank Group (2015), there is approximately 365-445 million Micro, Small and Medium Enterprises (MSMEs) with 285-345 million belonging to informal enterprises.
Localized Treatment with Oncolytic Adenovirus Delta-24-RGDOX Induces Systemic Immunity against Disseminated Subcutaneous and Intracranial Melanomas

Purpose: Intratumoral injection of oncolytic adenovirus Delta-24-RGDOX induces efficacious antiglioma immunity in syngeneic glioma mouse models. We hypothesized that localized treatment with the virus is effective against disseminated melanomas. Experimental Design: We tested the therapeutic effect of injecting Delta-24-RGDOX into primary subcutaneous (s.c.) B16-Red-FLuc tumors in s.c. /s.c. and s.c. /intracranial (i.c.) melanoma models in C57BL/6 mice. Tumor growth and in vivo luciferase-expressing ovalbumin-specific (OT-I/Luc) T cells were monitored with bioluminescence imaging. Cells were profiled for surface markers with flow cytometry. Results: In both s.c. /s.c. and s.c. /i.c. models, 3 injections of Delta-24-RGDOX significantly inhibited the growth of both the virus-injected s.c. tumor and untreated distant s.c. and i.c. tumors, thereby prolonging survival. The surviving mice were protected from rechallenging with the same tumor cells. The virus treatment increased the presence of T cells and the frequency of effector T cells in the virus-injected tumor and mediated the same changes in T cells from peripheral blood, spleen, and brain hemispheres with untreated tumor. Moreover, Delta-24-RGDOX decreased the numbers of exhausted T cells and regulatory T cells in the virus-injected and untreated tumors. Consequently, the virus promoted the in situ expansion of tumor-specific T cells and their migration to tumors expressing the target antigen. Conclusions: Localized intratumoral injection of Delta-24-RGDOX induces an in situ antovaccination of the treated melanoma, the effect of which changes the immune landscape of the treated mice, resulting in systemic immunity against disseminated s.c. and i.c. tumors.
A high-throughput dependency parser

Dependency parsing is an important task in NLP, and it is used in many downstream tasks for analyzing the semantic structure of sentences. Analyzing very large corpora in a reasonable amount of time, however, requires a fast parser. In this thesis we develop a transitionbased dependency parser with a neural-network decision function which outperforms spaCy, Stanford CoreNLP, and MALTParser in terms of speed while having a comparable, and in some cases better, accuracy. We also develop several variations of our model to investigate the trade-off between accuracy and speed. This leads to a model with a greatly reduced feature set which is much faster but less accurate, as well as a more complex model involving a BiLSTM simultaneously trained to produce POS tags which is more accurate, but much slower. We compare the accuracy and speed of our different parser models against the three mentioned parsers on the Penn Treebank, Universal Dependencies English, and Ontonotes datasets using two different dependency tree representations to show how our parser competes on data from very different domains. Our experimental results reveal that our main model is much faster than the 3 external parsers while also being more accurate in some cases; our reduced feature set model is significantly faster while remaining competitive in terms of accuracy; and our BiLSTM-using model is somewhat faster than CoreNLP and is significantly more accurate.
Evaluating Integrated Task Based Language Teaching and English Language Learning and Instruction System

This study aimed at evaluating the implementation of integrated TBLT and ELLIS which emphsized on observing, questioning, exploring, and communicating. The integrated learning had been implemented at two different classes of SMPN 1 Banguntapan and SMPM Piyungan in Bantul regency, Yogyakarta. The task resources were selected from ELLIS units involving sixteen units. Of quesionnaires and interviews, the results indicated that the developed tasks had already met the standard of learning competence at the level. Teachers and students responded in several aspects, namely; learning objective, content material, integrated language skill exercise, and self-evaluation availibility. Thus, the integrated tasks conclusively helped the students achieve better and easier understanding, promotes learning interest, and evaluate their own learning and progress, inasmuch as these tasks equipped with the individual and group exercises. This study implies that combination of TBLT and ELLIS generated better opportunities to create more innovative English teaching.
HOMOGENEOUS COMPLETELY SIMPLE SEMIGROUPS

A semigroup is completely simple if it has no proper ideals and contains a primitive idempotent. We say that a completely simple semigroup $S$ is a homogeneous completely simple semigroup if any isomorphism between finitely generated completely simple subsemigroups of $S$ extends to an automorphism of $S$. Motivated by the study of homogeneous completely regular semigroups, we obtain a complete classification of homogeneous completely simple semigroups, modulo the group case. As a consequence, all finite regular homogeneous semigroups are described, thus extending the work of Cherlin on homogeneous finite groups.
Metagenomic analysis reveals a rich bacterial content in high‐risk prostate tumors from African men

Inflammation is a hallmark of prostate cancer (PCa), yet no pathogenic agent has been identified. Men from Africa are at increased risk for both aggressive prostate disease and infection. We hypothesize that pathogenic microbes may be contributing, at least in part, to high‐risk PCa presentation within Africa and in turn the observed ethnic disparity.
Learning non-smooth models: instrumental variable quantile regressions and related problems

This paper proposes computationally efficient methods that can be used for instrumental variable quantile regressions (IVQR) and related methods with statistical guarantees. This is much needed when we investigate heterogenous treatment effects since interactions between the endogenous treatment and control variables lead to an increased number of endogenous covariates. We prove that the GMM formulation of IVQR is NP-hard and finding an approximate solution is also NP-hard. Hence, solving the problem from a purely computational perspective seems unlikely. Instead, we aim to obtain an estimate that has good statistical properties and is not necessarily the global solution of any optimization problem. The proposal consists of employing $k$-step correction on an initial estimate. The initial estimate exploits the latest advances in mixed integer linear programming and can be computed within seconds. One theoretical contribution is that such initial estimators and Jacobian of the moment condition used in the k-step correction need not be even consistent and merely $k=4\log n$ fast iterations are needed to obtain an efficient estimator. The overall proposal scales well to handle extremely large sample sizes because lack of consistency requirement allows one to use a very small subsample to obtain the initial estimate and the k-step iterations on the full sample can be implemented efficiently. Another contribution that is of independent interest is to propose a tuning-free estimation for the Jacobian matrix, whose definition nvolves conditional densities. This Jacobian estimator generalizes bootstrap quantile standard errors and can be efficiently computed via closed-end solutions. We evaluate the performance of the proposal in simulations and an empirical example on the heterogeneous treatment effect of Job Training Partnership Act.
The Extent of Extemporaneous Preparation and Regulatory Framework of Extemporaneous Compounding in Latvia

Background and objectives: Extemporaneous preparations are pharmaceutical preparations individually prepared for a specific patient or patient group, but also high-risk products accompanied by doubts regarding their safety and quality. Legislation regulating the compounding of extemporaneous preparations is not harmonized among European countries. This problem is partially resolved by Resolution CM/Res(2016)1 on quality and safety assurance requirements for medicinal products prepared in pharmacies for the special needs of patients. In order to understand the relevance of extemporaneous compounding in Latvia and the fulfillment of the abovementioned resolution’s requirements, it is essential to get information about the volume and breakdown of sales of extemporaneous medicinal products in community pharmacies. The purpose of this survey is to identify the sales volume of extemporaneous preparations in community pharmacies in Latvia in 2017 by analyzing unpublished data of the State Agency of Medicines (SAM), as well as comparing Latvian laws with the requirements of the resolution. Materials and Methods: A separate Microsoft Excel spreadsheet was prepared for each statistical region in order to summarize the unpublished information of SAM on the turnover of extemporaneous preparations in 2017 in all Latvian statistical regions. In order to compare the regulatory framework in Latvia with the resolution, the Latvian Pharmaceutical Law and the Cabinet of Ministers Regulations regulating prescription, compounding and control of extemporaneous preparations in community pharmacies were analyzed. Results: Only 280 of 384 pharmacies submitted a report of sales of extemporaneous preparations for 2017 to the SAM. These pharmacies represented all Latvian statistical regions. Extemporaneous preparations were mostly sold in Riga (78.93%). The Latvian regulation does not include all paragraphs of the resolution. Most of the paragraphs of the resolution are described in Latvian regulatory enactments only partially. Conclusions: The total number of compounding pharmacies evidence that the service is needed. Latvian example highlights a necessity for European Union countries to compare their national legislation with the requirements of the resolution’s last version and, if necessary, implement relevant amendments.
Prey Preference and Switching Behaviour of Coccinella septempunctata L . ( Coleoptera : Coccinellidae )

The relationship between the predator and their prey was evaluated in the laboratory on feeding three prey species Myzus persicae, Rohpalosiphum padi and Bravicoryne brassicae. Mixed instars of each prey were supplied in the individual arena to a single adult Coccinella septempunctata. The prey consumption and rate of egg production were significantly higher when feeding on M. persicae in comparison with two other prey species. The development rate was significantly inferior when the predator fed on B. brassicae. The predators innate factors determined a significantly higher oviposition rate on natural host than non host. The morphological factor of the host prey had great influence on the prey preference and switching behaviour of the predator.
CASIA-SURF: A Large-Scale Multi-Modal Benchmark for Face Anti-Spoofing

Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face anti-spoofing benchmark datasets in recent years. However, existing face anti-spoofing benchmarks have limited number of subjects (≤170) and modalities (≤2), which hinder the further development of the academic community. To facilitate face anti-spoofing research, we introduce a large-scale multi-modal dataset, namely CASIA-SURF, which is the largest publicly available dataset for face anti-spoofing in terms of both subjects and modalities. Specifically, it consists of 1,000 subjects with 21,000 videos and each sample has 3 modalities (i.e., RGB, Depth and IR). We also provide comprehensive evaluation metrics, diverse evaluation protocols, training/validation/testing subsets and a measurement tool, developing a new benchmark for face anti-spoofing. Moreover, we present a novel multi-modal multi-scale fusion method as a strong baseline, which performs feature re-weighting to select the more informative channel features while suppressing the less useful ones for each modality across different scales. Extensive experiments have been conducted on the proposed dataset to verify its significance and generalization capability. The dataset is available at https://sites.google. com/qq.com/face-anti-spoofing/welcome/challengecvpr2019? authuser=0.
Effect of Ostomy Care Team Intervention on Patients With Ileal Conduit

PURPOSE: The purpose of this study was to investigate the effect of a nurse-led multicomponent intervention on ostomy-related complications, self-efficacy, and health-related quality of life in patients with an ileal conduit. DESIGN: Randomized controlled trial. SAMPLE AND SETTING: Forty-six patients who underwent radical cystectomy and creation of an ileal conduit participated in the trial; data were collected over a 6-month period. The study setting was Shanghai Pudong Hospital, affiliated with Fudan University, located in Shanghai, China. METHODS: Participants were randomly allocated to an experimental or control group. Participants in the control group received routine care over a 6-month period following ostomy surgery, while those in the experimental group received a nurse-led, multicomponent, structured intervention delivered by an ostomy care team. The Chinese language versions of the Stoma Self-Efficacy Scale (SSES) and the City of Hope Quality of Life-Ostomy (COHQOL-O) questionnaire were used to assess self-efficacy in stoma care and health-related quality of life. Ostomy-related complications including peristomal moisture-associated skin damage and uric acid crystal deposits in the peristomal area were also assessed. Fisher's exact test was used to compare the incidence of ostomy-related complications between the 2 groups. Independent-samples t tests were used to compare SSES and COHQOL-O scores. RESULTS: No statistically significant differences were found between demographic characteristics of the control and experimental groups. After 6 months, the incidence of complications was significantly lower in the experimental group as compared to the control group (4.35% vs 30.43%, P = .047). In addition, the mean SSES score was significantly higher in the experimental group (indicating greater self-efficacy in stoma care) (107.13 ± 11.87 vs 85.65 ± 12.87, P = .000), and the mean COHQOL-O score was also significantly higher in the experimental group, indicating higher health-related quality of life (154.48 ± 16.01 vs 138.26 ± 13.42, P = .001). CONCLUSION: The nurse-led multicomponent intervention provided by the ostomy care team reduced ostomy-related complications and improved the self-efficacy level and health-related quality of life in persons with a new urostomy.
Optimal Ship Maintenance Scheduling Under Restricted Conditions and Constrained Resources

OPTIMAL SHIP MAINTENANCE SCHEDULING UNDER RESTRICTED CONDITIONS AND CONSTRAINED RESOURCES Vi Hong Nguyen Old Dominion University, 2017 Director: Dr. Han Bao The research presented in this dissertation addresses the application of evolution algorithms, i.e. Genetic Algorithm (GA) and Differential Evolution algorithm (DE) to scheduling problems in the presence of restricted conditions and resource limitations. This research is motivated by the scheduling of engineering design tasks in shop scheduling problems and ship maintenance scheduling problems to minimize total completion time. The thesis consists of two major parts; the first corresponds to the first appended paper and deals with the computational complexity of mixed shop scheduling problems. A modified Genetic algorithm is proposed to solve the problem. Computational experiments, conducted to evaluate its performance against known optimal solutions for different sized problems, show its superiority in computation time and the high applicability in practical mixed shop scheduling problems. The second part considers the major theme in the second appended paper and is related to the ship maintenance scheduling problem and the extended research on the multi-mode resource-constrained ship scheduling problem. A heuristic Differential Evolution is developed and applied to solve these problems. A mathematical optimization model is also formulated for the multi-mode resourceconstrained ship scheduling problem. Through the computed results, DE proves its effectiveness and efficiency in addressing both single and multi-objective ship maintenance scheduling problems.
Acute and Chronic Pain Learning and Teaching in Medical School—An Observational Cross-Sectional Study Regarding Preparation and Self-Confidence of Clinical and Pre-Clinical Medical Students

Background and objectives: Adequate pain management is a major challenge of public health. The majority of students graduating from medical schools has insufficient education and experience with patients suffering pain. Not enough is being taught regarding pain in non-verbal patients (children, critically ill in the intensive care unit, demented). Chronic pain is the most difficult to optimize and requires appropriate preparation at the level of medical school. Our aim was to evaluate attitudes, expectations and the actual knowledge of medical students at different levels of their career path regarding the assessment and treatment of acute and chronic pain. Materials and Methods: We performed an observational cross-sectional study that was based on a survey distributed among medical students of pre-clinical and post-clinical years at the Pomeranian Medical University in Szczecin, Poland. The survey included: demographic data, number of hours of formal pain teaching, actual knowledge of pain assessment, and pain treatment options in adults and children. Results: We received responses from 77/364 (21.15%) students and 79.2% of them rated the need to obtain knowledge regarding pain as very important (10/10 points). Post-clinical group declared having on average 11.51 h of acute pain teaching as compared to the 7.4 h reported by the pre-clinical group (p = 0.012). Graduating students also reported having significantly more classes regarding the treatment of chronic pain (6.08 h vs. 3.79 h, p = 0.007). The average level of comfort in the post-clinical group regarding treatment of acute pain was higher than in the pre-clinical group (6.05 vs. 4.26, p = 0.006), similarly with chronic pain treatment in adults (4.33 vs. 2.97, p = 0.021) and with pain treatment in children (3.14 vs. 1.97, p = 0.026). Conclusions: This study shows that education about pain management is a priority to medical students. Despite this, there continues to be a discrepancy between students’ expectations and the actual teaching and knowledge regarding effective pain management, including the vulnerable groups: chronic pain patients, children, and critically ill people.
Integrative Meta-Assembly Pipeline (IMAP): Chromosome-level genome assembler combining multiple de novo assemblies

Background Genomic data have become major resources to understand complex mechanisms at fine-scale temporal and spatial resolution in functional and evolutionary genetic studies, including human diseases, such as cancers. Recently, a large number of whole genomes of evolving populations of yeast (Saccharomyces cerevisiae W303 strain) were sequenced in a time-dependent manner to identify temporal evolutionary patterns. For this type of study, a chromosome-level sequence assembly of the strain or population at time zero is required to compare with the genomes derived later. However, there is no fully automated computational approach in experimental evolution studies to establish the chromosome-level genome assembly using unique features of sequencing data. Methods and results In this study, we developed a new software pipeline, the integrative meta-assembly pipeline (IMAP), to build chromosome-level genome sequence assemblies by generating and combining multiple initial assemblies using three de novo assemblers from short-read sequencing data. We significantly improved the continuity and accuracy of the genome assembly using a large collection of sequencing data and hybrid assembly approaches. We validated our pipeline by generating chromosome-level assemblies of yeast strains W303 and SK1, and compared our results with assemblies built using long-read sequencing and various assembly evaluation metrics. We also constructed chromosome-level sequence assemblies of S. cerevisiae strain Sigma1278b, and three commonly used fungal strains: Aspergillus nidulans A713, Neurospora crassa 73, and Thielavia terrestris CBS 492.74, for which long-read sequencing data are not yet available. Finally, we examined the effect of IMAP parameters, such as reference and resolution, on the quality of the final assembly of the yeast strains W303 and SK1. Conclusions We developed a cost-effective pipeline to generate chromosome-level sequence assemblies using only short-read sequencing data. Our pipeline combines the strengths of reference-guided and meta-assembly approaches. Our pipeline is available online at http://github.com/jkimlab/IMAP including a Docker image, as well as a Perl script, to help users install the IMAP package, including several prerequisite programs. Users can use IMAP to easily build the chromosome-level assembly for the genome of their interest.