Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of 5-year imatinib treatment of 458 patients with CP-CML in routine clinical practice and prognostic impact of different BCR-ABL cutoff levels

We evaluated responses to the treatment and long‐term outcomes of chronic myeloid leukemia patients treated with imatinib as first‐line treatment in routine clinical setting from two countries with centralized tyrosine kinase inhibitors (TKIs) treatment. We assessed prognostic significance of European LeukemiaNet (ELN) 2006‐ and 2009‐defined responses and the prognostic value of molecular responses at defined time points on 5‐year survivals. Among the cumulative rates of incidence of hematologic, cytogenetic, and molecular responses and all important survival parameters, we evaluated the prognostic significance of different BCR‐ABL transcript‐level ratios (≤1%; >1%–≤10%; >10%) at 3, 6, 12, and 18 months (n = 199). The ELN optimal response criteria and their predictive role were significantly beneficial for event‐free survival at all given time points. We found significant improvement in survivals of patients with BCR‐ABL lower than 10% in the 6th and 12th months. Significantly better outcome was found in patients who achieved major molecular response (MMR) in the 12th month. The cumulative incidences of complete cytogenetic response (CCyR) and MMR were significantly associated with the molecular response in the 3rd month. The ELN response criteria and their predictive role were helpful at given time points; however, the 2009 definition did not significantly alter the prognostic accuracy compared with that of the 2006 definition. The significant value was observed for cytogenetic responses at the 6th and 12th month. Moreover, progression‐free and event‐free survivals were improved with MMR at the 12th month.
A Joint Model of Product Properties, Aspects and Ratings for Online Reviews

Product review mining is an important task that can benefit both businesses and consumers. Lately a number of models combining collaborative filtering and content analysis to model reviews have been proposed, among which the Hidden Factors as Topics (HFT) model is a notable one. In this work, we propose a new model on top of HFT to separate product properties and aspects. Product properties are intrinsic to certain products (e.g. types of cuisines of restaurants) whereas aspects are dimensions along which products in the same category can be compared (e.g. service quality of restaurants). Our proposed model explicitly separates the two types of latent factors but links both to product ratings. Experiments show that our proposed model is effective in separating product properties from aspects.
“Loving Nursing” and “Taking Responsibility”: Strategies for Transitioning to Practice in Lebanon

Transitioning to practice is challenging for baccalaureate nursing students. In baccalaureate nursing programs, the process typically begins in the junior year. A Successful transition depends on how well students apply their developing knowledge during clinical placements. A cross-sectional, multisite, qualitative study was conducted at four universities in Greater Beirut, Lebanon. In total, 35 junior baccalaureate students participated in audio-recorded focus group discussions. Thematic analysis was used to analyze the data. Three themes were sufficient to summarize the students experiences: “being unprepared,” “learning unexpected lessons,” and “taking responsibility. ” Three subthemes, revising expectations, discovering divergence, and self-monitoring, were used to clarify the unexpected lessons students learned during clinical placements and how students responded. “Loving nursing and protecting yourself,” making the most of every day, and doubting future readiness were subthemes within the “taking responsibility” theme. Students troubled by nursing practices that diverged from their expectations monitored themselves to avoid falling into poor practices and kept track of the nursing procedures they performed. Only by taking responsibility for their learning, could students develop the competencies they will need as registered nurses. Faculty, clinical instructors, hospital administrators, nurse managers, and registered nurses need to do more to support students to take control of their learning.
Enhancement of Immune Activation Activities of Spirulina maxima Grown in Deep-Sea Water

In this study, the immuno-modulatory and anticancer activities of marine algae, Spirulina maxima grown in deep-sea water (DSW), were investigated. It was found that the extract of S. maxima, cultured in DSW, effectively suppressed the expression of Bcl2 in A549 cells as well as inhibiting various human cancer cells with concentration dependency, which possibly implies that the extracts may play more important roles in controlling cancer cell growth. The secretion of cytokines IL-6 and TNF-α from human B cells was also greatly increased, compared to those of the extract grown in conventional sea-water. The growth of Human Natural Killer (NK) cells in the presence of the extracts from DSW was significantly higher (12.2 × 104 viable cells/mL) when compared to the control (1.1 × 104 viable cells/mL). Based on HPLC analysis, the increase in the biological activities of the extracts from DSW was caused by considerably high amounts of β-carotene and ascorbic acid because the DSW contained high concentrations and good ratios of several key minerals for biosynthesizing β-carotene and ascorbic acid, as well as maintaining high cell growth.
settlements consolidation: Spatial analysis in an agent-based environment

In this present paper the development of inner-city squatter settlements is analysed at two complementary scales, through distinct agent based models developed by the author: AxialAgents and Favela. The first one discuss the arising and development of spontaneous settlements in a virtual city centre where some aspects of the typical structure and dynamics of Third World cities are reproduced. In particular, its irregular and fragmented structure, sorted by open spaces (usually non-occupied public land), model processes which are usually the basis for inner-city squatter settlements’ development. This process is analysed according to the relative location of these vacant sites, in relation to the grid structure and to the existence of movement generators, through AxialAgents, an heuristic agent-based model in which decentralised agents run over an axial lines like environment searching for available space to settle. The second approach is developed at a smaller scale, and is related to the development of the squatter settlement itself. For this purpose we use Favelas, an agent based model which simulates, in a heuristic basis, the process of growth and consolidation of squatter settlements according to decentralised agent based movement from the edge (attractive and non-attractive boundaries) of vacant sites. Both models were built with heuristic purposes, based on random walk dynamics and built in StarLogo, a parallel programming tool developed by the Epistemology and Learning Group of the Massachusetts Institute of Technology.
The Dual Role of AQP4 in Cytotoxic and Vasogenic Edema Following Spinal Cord Contusion and Its Possible Association With Energy Metabolism via COX5A

Spinal cord edema, mainly including vasogenic and cytotoxic edema, influences neurological outcome after spinal cord contusion (SCC). Aquaporin 4 (AQP4) is the most ubiquitous water channel in the central nervous system (CNS), which is a rate-limiting factor in vasogenic edema expressing in brain injury, and it contributes to the formation of cytotoxic edema locating in astrocytes. However, little is known about the regulatory mechanism of AQP4 within vasogenic and cytotoxic edema in SCC, and whether the regulation mechanism of AQP4 is related to Cytochrome coxidase (COX5A) affecting energy metabolism. Therefore, the SCC model is established by Allen’s method, and the degree of edema and neuronal area is measured. The motor function of rats is evaluated by the Basso, Beattie, and Bresnahan (BBB) scoring system. Meanwhile, AQP4 and COX5A are detected by real-time quantitative PCR (qRT-PCR) and western blot (WB). The localization of targeted protein is exhibited by immunohistochemical staining (IHC) and immunofluorescence (IF). Additionally, the methodology of AQP4 lentivirus-mediated RNA interference (AQP4-RNAi) is used to reveal the effect on edema of SCC and the regulating molecular mechanism. Firstly, we observe that the tissue water content increases after SCC and decreases after the peak value of tissue water content at 3 days (P < 0.05) with abundant expression of AQP4 protein locating around vascular endothelial cells (VECs), which suggests that the increasing AQP4 promotes water reabsorption and improves vasogenic edema in the early stage of SCC. However, the neuronal area is larger than in the sham group in the 7 days (P < 0.05) with the total water content of spinal cord decrease. Meanwhile, AQP4 migrates from VECs to neuronal cytomembrane, which indicates that AQP4 plays a crucial role in aggravating the formation and development of cytotoxic edema in the middle stages of SCC. Secondly, AQP4-RNAi is used to elucidate the mechanism of AQP4 to edema of SCC. The neuronal area shrinks and the area of cytotoxic edema reduces after AQP4 downregulation. The BBB scores are significantly higher than in the vector group after AQP4-RNAi at 5, 7, and 14 (P < 0.05). There is a relationship between AQP4 and COX5A shown by bioinformatics analysis. After AQP4 inhibition, the expression of COX5A is significantly upregulated in the swelling astrocytes. Therefore, the inhibition of AQP4 expression reduces cytotoxic edema in SCC and improves motor function, which may be associated with upregulation of COX5A via affecting energy metabolism. Moreover, it is not clear how the inhibition of AQP4 directly causes the upregulation of COX5A.
Fast Algorithm for the Lasso based L1-Graph Construction

The lasso-based L1-graph is used in many applications since it can effectively model a set of data points as a graph. The lasso is a popular regression approach and the L1-graph represents data points as nodes by using the regression result. More specifically, by solving the L1-optimization problem of the lasso, the sparse regression coefficients are used to obtain the weights of the edges in the graph. Conventional graph structures such as k-NN graph use two steps, adjacency searching and weight selection, for constructing the graph whereas the lasso-based L1-graph derives the adjacency structure as well as the edge weights simultaneously by using a coordinate descent. However, the construction cost of the lasso-based L1-graph is impractical for large data sets since the coordinate descent iteratively updates the weights of all edges until convergence. Our proposal, Castnet, can efficiently construct the lasso-based L1-graph. In order to avoid updating the weights of all edges, we prune edges that cannot have nonzero weights before entering the iterations. In addition, we update edge weights only if they are nonzero in the iterations. Experiments show that Castnet is significantly faster than existing approaches.
Melatonin Suppresses Microglial Necroptosis by Regulating Deubiquitinating Enzyme A20 After Intracerebral Hemorrhage

Cell death is deeply involved in pathophysiology of brain injury after intracerebral hemorrhage (ICH). Necroptosis, one of the recently discovered forms of cell death, plays an important role in various diseases, including ICH. Previous studies have suggested that a considerable number of neurons undergoes necroptosis after ICH. However, necroptosis of microglia after ICH has not been reported to date. The present study demonstrated for the first time that necroptosis occurred in the microglia surrounding the hematoma after ICH in C57 mice, and melatonin, a hormone that is predominantly synthesized in and secreted from the pineal gland, exerted a neuroprotective effect by suppressing this process. When we further explored the potential underlying mechanism, we found that melatonin inhibits RIP3-mediated necroptosis by regulating the deubiquitinating enzyme A20 (also known as TNFAIP3) expression after ICH. In summary, we have demonstrated the role of microglial necroptosis in the pathogenesis of ICH. More importantly, A20 was identified as a novel target of melatonin, which opens perspectives for future research.
A Predominance of Clade 17 Candida albicans Isolated From Hemocultures in a Tertiary Care Hospital in Thailand

Candida albicans is one of the most common human fungal pathogens. Candidemia has significant mortality globally. No epidemiological study of C. albicans based on multilocus sequence typing (MLST) has been conducted in Thailand. Therefore, MLST was used to study the molecular epidemiology of C. albicans blood strains in a large Thai teaching hospital. In vitro virulence phenotypes and antifungal susceptibility testing by broth microdilution were also conducted. Forty-six C. albicans blood strains from 37 patients were collected from the Department of Microbiology, Siriraj Hospital, in 2016 and 2017. Most patients (71.8%) were more than 60 years old, and the case fatality rate was 54.8%. The male-to-female ratio was 5:3. Thirty-four diploid sequence types (DSTs), including six new DSTs, were identified, with DST2514 (8.7%) and DST2876 (8.7%) as the most common DSTs. Strains were clustered into nine clades. Unlike other studies of C. albicans blood strains in Asia, clade 17 was the most common (13 strains, 28.3%). Sequential allelic changes were evident in sequential strains from one patient. All strains produced phospholipase and hemolysin, while none produced proteinase. The ability to form biofilm was found in 82.6% of the strains. Clade 17 strains showed significantly stronger hemolytic activity than non–clade 17 strains (69.2% versus 27.3%; p = 0.022). However, no significant association existed between clades and patient mortalities. All were susceptible or wild type to anidulafungin (MIC range = 0.015–0.12 and GM = 0.030), micafungin (MIC range = ≤ 0.008–0.015 and GM = 0.008), caspofungin (MIC range = 0.008–0.12 and GM = 0.036), and amphotericin B (MIC range = 0.25–0.5 and GM = 0.381). Only one strain was resistant to voriconazole (MIC range = ≤ 0.008 to ≥ 8 and GM = 0.010) and fluconazole (MIC range = 0.12–16 and GM = 0.398). In conclusion, a high prevalence of clade 17 C. albicans blood strains was found in Thailand, in contrast to other Asian countries. This unique finding might be explained by the strong hemolytic activity that is required for bloodstream infection of C. albicans.
Learning Relative Similarity by Stochastic Dual Coordinate Ascent

Learning relative similarity from pairwise instances is an important problem in machine learning and has a wide range of applications. Despite being studied for years, some existing methods solved by Stochastic Gradient Descent (SGD) techniques generally suffer from slow convergence. In this paper, we investigate the application of Stochastic Dual Coordinate Ascent (SDCA) technique to tackle the optimization task of relative similarity learning by extending from vector to matrix parameters. Theoretically, we prove the optimal linear convergence rate for the proposed SDCA algorithm, beating the well-known sublinear convergence rate by the previous best metric learning algorithms. Empirically, we conduct extensive experiments on both standard and large-scale data sets to validate the effectiveness of the proposed algorithm for retrieval tasks.
New generation of multi-step Doherty amplifier

This contribution presents an innovative solution to drastically increase the output power range in which the Doherty Power Amplifier shows a high and flat efficiency behaviour. The proposed topology and its main theoretical guidelines are shown and discussed. Moreover, the potentialities of the new idea and how it can solve some drawbacks in applications that manage signals with a peak to average power ratio greater than 7–8 dB are listened. The proposed idea has been validated performing several experimental measurements on an X-Band GaAs MMIC Doherty amplifier. In particular, the region of high and flat efficiency has been extended from 6dB to 11dB of output power back-off, without affecting gain and reached output power levels. As a result, a real average efficiency improvement of about 81% in the added 5dB of output back-off has been achieved.
Selling Hope and College: Merit, Markets, and Recruitment in an Unranked School

they had avoided gangs in their old neighborhoods, the complex geography of gang rivalry could put them in danger in their new neighborhoods. Reflecting their growing conviction that housing should be bundled with social services, Popkin and colleagues launched another intervention, the Housing Opportunities and Services Together (HOST), to develop a two-generation model of service delivery for families with children in distressed communities. Over the past two decades many cities have revitalized, attracting population and investment and defining an appealing new vision of sustainable urban life. HOPE VI was a key instrument of this transformation. Popkin’s careful case study illuminates the human consequences of this policy for public housing residents, many of whom were deeply wounded by the segregation and social engineering of an earlier day and who are now dispersed across the city. No Simple Solutions skillfully integrates quantitative and qualitative evidence with political and institutional detail. Vignettes of public housing residents are woven through the book, giving nuance and humanity to people who appear too often in public debate as stock figures. Popkin’s own personal experience appears as well; she ruefully acknowledges her moments of naiveté in dealing with the press and politicians. That she could maintain access in such a contentious legal and political environment is a testament to her credibility and sound judgment. Her book will be instructive not only for specialists in housing and social policy but also for those concerned more broadly with inequality in the changing American city. Selling Hope and College: Merit, Markets, and Recruitment in an Unranked School, by Alex Posecznick. Ithaca, NY: ILR Press, 2017. 213 pp. $19.95 paper. ISBN: 9781501709821.
Evaluation of the Treatment Process of Landfill Leachate Using the Toxicity Assessment Method

Landfill leachate is composed of a complex composition with strong biological toxicity. The combined treatment process of coagulation and sedimentation, anaerobics, electrolysis, and aerobics was set up to treat landfill leachate. This paper explores the effect of different operational parameters of coagulation and sedimentation tanks and electrolytic cells, while investigating the combined process for the removal efficiency of physicochemical indices after processing the landfill leachate. Meanwhile, a battery of toxicity tests with Vibrio fischeri, zebrafish larvae, and embryos were conducted to evaluate acute toxicity and calculated the toxicity reduction efficiency after each treatment process. The combined treatment process resulted in a 100% removal efficiency of Cu, Cd and Zn, and a 93.50% and an 87.44% removal efficiency of Ni and Cr, respectively. The overall removal efficiency of chemical oxygen demand (COD), ammonium nitrogen (NH4+-N), and total nitrogen (TN) were 93.57%, 97.46% and 73.60%, respectively. In addition, toxicity test results showed that the acute toxicity of landfill leachate had also been reduced significantly: toxicity units (TU) decreased from 84.75 to 12.00 for zebrafish larvae, from 82.64 to 10.55 for zebrafish embryos, and from 3.41 to 0.63 for Vibrio fischeri. The combined treatment process was proved to be an efficient treatment method to remove heavy metals, COD, NH4+-N, and acute bio-toxicity of landfill leachate.
Bridging the gap between planning and scheduling

Planning research in Artificial Intelligence (AI) has often focused on problems where there are cascading levels of action choice and complex interactions between actions. In contrast, scheduling research has focused on much larger problems where there is little action choice, but the resulting ordering problem is hard. In this paper, we give an overview of AI planning and scheduling techniques, focusing on their similarities, differences, and limitations. We also argue that many difficult practical problems lie somewhere between planning and scheduling, and that neither area has the right set of tools for solving these vexing problems.
A memetic algorithm for program verification

We present a memetic algorithm for program safety properties verification. This problem is expressed by means of Reach ability of some erroneous location L in the program. We use a new method for program modeling: A Separation Modeling Approach: ASMA, in which programs are represented by two components: Data Model DM, and Control Model CM. The erroneous location is represented by its "Location Access Chain", LAC: a string where each position represents the required value of CM elements guards to reach L. The memetic algorithm generates each time a new population attempting to provide an execution which is " conform" to the location access chain. An individual of the population is a set of intervals each one representing an input variable. At each generation, two local search operators are used to improve some chosen solutions.
The Social Lives of Microbes

Our understanding of the social lives of microbes has been revolutionized over the past 20 years. It used to be assumed that bacteria and other microorganisms lived relatively independent unicellular lives, without the cooperative behaviors that have provoked so much interest in mammals, birds, and insects. However, a rapidly expanding body of research has completely overturned this idea, showing that microbes indulge in a variety of social behaviors involving complex systems of cooperation, communication, and synchronization. Work in this area has already provided some elegant experimental tests of social evolutionary theory, demonstrating the importance of factors such as relatedness, kin discrimination, competition between relatives, and enforcement of cooperation. Our aim here is to review these social behaviors, emphasizing the unique opportunities they offer for testing existing evolutionary theory as well as highlighting the novel theoretical problems that they pose.
Mantis: Automatic Performance Prediction for Smartphone Applications

We present Mantis, a framework for predicting the performance of Android applications on given inputs automatically, accurately, and efficiently. A key insight underlying Mantis is that program execution runs often contain features that correlate with performance and are automatically computable efficiently. Mantis synergistically combines techniques from program analysis and machine learning. It constructs concise performance models by choosing from many program execution features only a handful that are most correlated with the program's execution time yet can be evaluated efficiently from the program's input. We apply program slicing to accurately estimate the evaluation cost of a feature and automatically generate executable code snippets for efficiently evaluating features. Our evaluation shows that Mantis predicts the execution time of six Android apps with estimation error in the range of 2.2-11.9% by executing predictor code costing at most 1.3% of their execution time on Galaxy Nexus.