Miracle-dz/UniFAR-FTUs huggingface dataset:
Contact-dependent carcinoma aggregate dispersion by M2a macrophages via ICAM-1 and β2 integrin interactions

Tumor-associated macrophages (TAMs) can constitute up to 50% of the tumor mass and have strong implications in tumor progression and metastasis. Macrophages are plastic and can polarize to various subtypes that differ in terms of surface receptor expression as well as cytokine and chemokine production and effector function. Conventionally, macrophages are grouped into two major subtypes: the classically activated M1 macrophages and the alternatively activated M2 macrophages. M1 macrophages are pro-inflammatory, promote T helper (Th) 1 responses, and show tumoricidal activity, whereas M2 macrophages contribute to tissue repair and promote Th2 responses. Herein, we present a microfluidic system integrating tumor cell aggregates and subtypes of human monocyte-derived macrophages in a three-dimensional hydrogel scaffold, in close co-culture with an endothelial monolayer to create an in vitro tumor microenvironment. This platform was utilized to study the role of individual subtypes of macrophages (M0, M1, M2a, M2b and M2c) in human lung adenocarcinoma (A549) aggregate dispersion, as a representation of epithelial-mesenchymal transition (EMT). A significant difference was observed when M2a macrophages were in direct contact with or separated from A549 aggregates, suggesting a possible mechanism for proximity-induced, contact-dependent dissemination via ICAM-1 and integrin β2 interactions. Indeed, M2a macrophages tended to infiltrate and release cells from carcinoma cell aggregates. These findings may help in the development of immunotherapies based on enhancing the tumor-suppressive properties of TAMs.
Automatic Mapping of Task and Data Parallel Programs for Efficient Execution on Multicomputers

For a wide variety of applications, both task and data parallelism must be exploited to achieve the best possible performance on a multicomputer. Recent research has underlined the importance of exploiting task and data parallelism in a single compiler framework, and such a compiler can map a single source program in many different ways onto a parallel machine. There are several complex tradeoffs between task and data parallelism, depending on the characteristics of the program to be executed and the performance parameters of the target parallel machine. This makes it very difficult for a programmer to select a good mapping for a task and data parallel program. In this paper we isolate and examine specific characteristics of executing programs that determine the performance for different mappings on a parallel machine, and present an automatic system to obtain good mappings. The process consists of two steps: First, an instrumented input program is executed a fixed number of times with different mappings, to build an execution model of the program. Next, the model is analyzed to obtain a good final mapping of the program onto the processors of the parallel machine. The current implementation is static, feedback driven, although the approach can be extended to a dynamic system. We demonstrate the system with an example program that is a model for many applications in the domains of signal processing and image processing.
Development of a new type of micro fluidic system using EO pumps

This paper presents a novel micro fluidic system based on two EO (electoosmotic) pumps. This system consists of two EO pumps, one indirect pumping mechanism, and two switching valves. The indirect pumping mechanism includes two sealed chambers, one is the driving fluid chamber and the other is working fluid chamber. The EO pumps actuator make the diaphragm which separates two chambers reciprocate. So the liquid in the working fluid chamber can be pumped from inlet to outlet. Due to the large deflections of the actuator membrane, the device is completely self-filling and able to pump liquid. By using the indirect pumping mechanism, the problem of driving fluid circulation has been improved. The operation of the micropump was investigated experimentally. And a maximum flow rate of 194µl/min (using water) back-pressure 119kp was obtained by an input voltage of 20V and an exciting frequency of 1.6Hz. A close loop control system was designed to obtain stable flow rate. In this paper, the flow rate was controlled at 125µl/min and an experiment was accomplished to show the performance of the system. These experiments results demonstrate the fluidic system performance and ability to deliver the fluid and drags to LOC (laboratory-on-a-chip) for chemical analysis.
Efficacy and toxicity of the angiogenesis inhibitor SU5416 as a single agent in patients with advanced renal cell carcinoma, melanoma, and soft tissue sarcoma.

INTRODUCTION Vascular endothelial growth factor (VEGF) is a key regulator in angiogenesis. Preclinical and clinical data support the role of VEGF and angiogenesis in renal cell carcinoma (RCC), melanoma (M), and soft tissue sarcoma (STS). The tyrosine kinase inhibitor SU5416 is a potent inhibitor of the VEGF receptors 1 and 2. EXPERIMENTAL DESIGN We investigated 145 mg/m(2) SU5416 twice weekly in patients with advanced or metastatic RCC, M, and STS. The primary objectives were efficacy and safety. Disease assessments were performed after 4 and 8 weeks of treatment and every 2 months thereafter. Documented stable disease (SD) lasting for > or =3 months was considered an antitumor response. RESULTS A group of 29 patients was entered in the RCC trial, 20 patients in the M trial, and 31 patients in the STS trial. Response was observed in 6 (1 minor response and 5 SDs) of 24 evaluable patients (25%) in the RCC group, 6 (1 minor response and 5 SDs) of 26 patients (23%) in the STS group, and none of the patients in the M group. Progression-free survival ranged from 7 to 252 days (median 59 days) in the RCC group, from 7 to 260 days (median 60 days) in the STS group, and from 14 to 139 days (median 41 days) in the M group. Toxicities observed were those reported previously for SU5416. CONCLUSION SU5416 single agent is well tolerated. The antitumor response was low in patients with RCC and STS, whereas no responses were seen in patients with M.
Click'n'Cut: Crowdsourced Interactive Segmentation with Object Candidates

This paper introduces Click'n'Cut, a novel web tool for interactive object segmentation designed for crowdsourcing tasks. Click'n'Cut combines bounding boxes and clicks generated by workers to obtain accurate object segmentations. These segmentations are created by combining precomputed object candidates in a light computational fashion that allows an immediate response from the interface. Click'n'Cut has been tested with a crowdsourcing campaign to annotate images from publicly available datasets. Results are competitive with state-of-the-art approaches, especially in terms of time needed to converge to a high quality segmentation.
A Survey on Collaborative Filtering in Accordance with the Agricultural Application

In modern E-Commerce it is not easy for the customers to find the best goods of their interest as there are millions of products available online. Recommender systems, one of these systems, are one of information filtering systems forecasting the items that may be additional interest for user within a big set of items on the basis of user’s interests. This system uses the Collaborative filtering, which offers some recommendations to users on the basis of matches in behavioral and functional patterns of users and also shows similar fondness and behavioral patterns with those users. We are going to develop an agriculture based application by using the Collaborative Filtering, Semantic Analysis and Big Data concepts. This system will be useful to farmers for selling their products and getting information regarding the required material in farming.
Bubbles: a data management approach to create an advanced industrial interoperability layer for critical systems development applying reuse techniques

The development of critical systems is becoming more and more complex. The overall tendency is that development costs raise. In order to cut cost of development, companies are forced to build systems from proven components and larger new systems from smaller older ones. Respective reuse activities involve good number of people, tools and processes along different stages of the development lifecycle which involve large numbers of tools. Some development is directly planned for reuse. Planned reuse implies excellent knowledge management and firm governance of reusable items. According to the current state of the art, there are still practical problems in the two fields, mainly because the governance and knowledge management is fragmented over the tools of the toolchain. In our experience, the practical effect of this fragmentation is that involved ancestor and derivation relationships are often undocumented or not exploitable. Additionally, useful reuse is almost always dealing with heterogeneous content which must be transferred from older to newer development environments. In this process, interoperability proves either as biggest obstacle or greatest help. In this paper, authors connect the topics interoperability and knowledge management and propose to seek for ubiquitous reuse via advanced interoperability features. A single concept from a larger Technical Interoperability Concept (TIC) with the name bubble is presented. Bubbles are expected to overcome existing barriers to cost-efficient reuse in systems and software development lifecycles. That is why, the present paper introduces and defines bubbles by showing how they simplify application of repairs and changes and hence contribute to expansion of reuse at reduced cost.
High Confidence Off-Policy Evaluation with Models

In many reinforcement learning applications executing a poor policy may be costly or even dangerous. Thus, it is desirable to determine confidence interval lower bounds on the performance of any given policy without executing said policy. Current methods for high confidence off-policy evaluation require a substantial amount of data to achieve a tight lower bound, while existing model-based methods only address the problem in discrete state spaces. We propose two bootstrapping approaches combined with learned MDP transition models in order to efficiently estimate lower confidence bounds on policy performance with limited data in both continuous and discrete state spaces. Since direct use of a model may introduce bias, we derive a theoretical upper bound on model bias when we estimate the model transitions with i.i. d. sampled trajectories. This bound can be used to guide selection between the two methods. Finally, we empirically validate the data-efficiency of our proposed methods across three domains and analyze the settings where one method is preferable to the other.
Serotonin- and Dopamine-Related Gene Expression in db/db Mice Islets and in MIN6 β-Cells Treated with Palmitate and Oleate

High circulating nonesterified fatty acids (NEFAs) concentration, often reported in diabetes, leads to impaired glucose-stimulated insulin secretion (GSIS) through not yet well-defined mechanisms. Serotonin and dopamine might contribute to NEFA-dependent β-cell dysfunction, since extracellular signal of these monoamines decreases GSIS. Moreover, palmitate-treated β-cells may enhance the expression of the serotonin receptor Htr2c, affecting insulin secretion. Additionally, the expression of monoamine-oxidase type B (Maob) seems to be lower in islets from humans and mice with diabetes compared to nondiabetic islets, which may lead to increased monoamine concentrations. We assessed the expression of serotonin- and dopamine-related genes in islets from db/db and wild-type (WT) mice. In addition, the effect of palmitate and oleate on the expression of such genes, 5HT content, and GSIS in MIN6 β-cell was determined. Lower Maob expression was found in islets from db/db versus WT mice and in MIN6 β-cells in response to palmitate and oleate treatment compared to vehicle. Reduced 5HT content and impaired GSIS in response to palmitate (−25%; p < 0.0001) and oleate (−43%; p < 0.0001) were detected in MIN6 β-cells. In conclusion, known defects of GSIS in islets from db/db mice and MIN6 β-cells treated with NEFAs are accompanied by reduced Maob expression and reduced 5HT content.
Watching the Shop from the Front Seat: Determinants of Venture Capitalists' Representation on the Board

Oversight and involvement are essential for a venture capital firm to influence the destiny of the portfolio company. This paper focuses primarily on the venture capital firm's decision to take a formal responsibility through joining the board. Our study uses a large sample of private British companies that received institutional investment between 1999 and 2002. We examine the determinants of board composition and board size. Contrary to common belief, only 30% of the companies have any institutional investor (a "VC") on board. The decision to take a formal board seat is based on the ability to make a contribution: Specifically, on the stage of the portfolio firm, the industry fit between the investment and the venture capital firm, and the overall experience of the latter. Two aspects of British venture capital firms inhibit their role in governance. First, firms that are organised as a public corporation (and not as a partnership) refrain from undertaking a formal board responsibility. Second, some of the more established institutions are organised around branches. We find that the VC firms with branches are less involved with board membership. Finally, we report (but are helpless to rationalize) a sizeable number of cases in which a VC firm is represented on the board yet did not invest in the firm.
Dealer: Dynamic Request Splitting for Performance-Sensitive Applications in Multi-Cloud Environments

Enterprises are increasingly deploying their applications in the cloud given the cost-saving advantages, and the potential to geo-distribute applications to ensure resilience and better service experience. However, a key unknown is whether it it is feasible to meet the stringent response time requirements of enterprise applications using the cloud. We make several contributions. First, we show through empirical measurement studies that (i) there is significant short-term variability in application workload and response times of individual components; however (ii) the response times of the same component in different data-centers are often uncorrelated. This leads us to argue that there are potential latency savings if work related to a poorly performing component is dynamically reassigned to a replica in a remote data-center. We leverage this insight to build a system that we term Dealer which for each component, dynamically splits transactions among its replicas in different data-centers. In doing so, Dealer seeks to minimize user response times, and takes component performance, as well as intra-datacenter and inter-data-center communication latencies into account. We have implemented Dealer in a way that it can be added to any multi-tier application. Evaluations of our approach on two multi-tier applications on actual Azure cloud deployments indicates the importance and feasibility of our mechanisms. For instance, the 90%ile of application response times could be reduced by as much as 6 times under natural cloud dynamics.
ICA photographic encoding gear: image bases towards IPEG

Independent component analysis (ICA) is applied to image coding. There, new design methods for ICA bases are presented. The new feature of this learning algorithm includes the weak guidance, or decreasing supervisory information. The weak guidance reduces the permutation indeterminacy which is unavoidable in usual ICA algorithms. In view of the image compression, this effect corresponds to the generation of image bases honoring the space frequency's neighborhood and 2-D ordering. Following the presentation of this learning algorithm, experiments are performed to obtain serviceable ICA bases. Finally, image compression and restoration are demonstrated to show the eligibility for "image. IPEG. " Other applications such as image retrieval are also commented upon.
Image normalization by mutual information

Image normalization refers to eliminating image variations (such as noise, illumination, or occlusion) that are related to conditions of image acquisition and are irrelevant to object identity. Image normalization can be used as a preprocessing stage to assist computer or human object perception. In this paper, a class-based image normalization method is proposed. Objects in this method are represented in the PCA basis, and mutual information is used to identify irrelevant principal components. These components are then discarded to obtain a normalized image which is not affected by the specic conditions of image acquisition. The method is demonstrated to produce visually pleasing results and to improve signicantly the accuracy of known recognition algorithms. The use of mutual information is a signicant advantage over the standard method of discarding components according to the eigenvalues, since eigenvalues correspond to variance and have no direct relation to the relevance of components to representation. An additional advantage of the proposed algorithm is that many types of image variations are handled in a unied framework.
Assertiveness and narcissism.

Scores on the Rathus Assertiveness Schedule (RAS) were positively related to measures of healthy narcissism and inversely related to empathic distress, anxiety, and depression. Partial correlational procedures controlled for the tendency of healthy and unhealthy forms of narcissism to be linked together and revealed the RAS to be inversely associated with maladaptive narcissism. This same basic pattern was observed following a more specific examination of RAS items previously identified as predictive of individuals who create an impression of not being "nice. " These results do not support arguments that a psychotherapeutic emphasis on assertiveness promotes an antisocial egocentrism and instead are consistent with a suggested connection between individualism and interdependence.
Prediction of cirrhosis from liver ultrasound B-mode images based on Laws' masks analysis

In this present work, a technique for differentiation of normal and cirrhotic liver segmented regions of interest (SROIs) based on Laws' masks analysis is reported. Thirty four B-mode ultrasound images taken from 22 normal volunteers and 12 patients suffering from liver cirrhosis were collected from Department of Radiodiagnosis and Imaging, PGIMER, Chandigarh, India. The filtered texture images are obtained by convolving the SROIs with twenty five, 2D (5×5) special filters based on laws' masks. Metrics that can quantify the texture can be obtained by computing the statistics from these filtered texture images. Similar features are combined to remove the directional information as texture directionality is not important here. This results into 15 rotational invariant filtered texture images for each SROI. For each of the filtered images, five statistics namely, mean, standard deviation, skewness, kurtosis and energy are computed. Thus, a total of 75 Laws' texture features (15 filtered texture images × 5 statistical features) are computed for 82 normal SROIs and 39 cirrhotic SROIs taken from 34 B-Mode ultrasound liver images. Correlation based feature selection (CFS) method is used to find the optimal subset of Laws' texture features which can provide best discrimination between normal and cirrhotic SROIs. It has been observed that CFS method results in an optimal subset of 8 Laws' texture features {LLmean, LLsd, LEsd, SSskewness, RRenergy, LEenergy, LSenergy and LWenegy}. The classification performance of neural network (NN) classifier is compared with support vector machine (SVM) classifier. By using all 75 Laws' texture features the classification accuracy of 90.08% and 90.90% is obtained with NN and SVM classifier respectively. By using 8 Laws' features selected by CFS method the classification accuracy of 91.73% and 92.56% is obtained with NN and SVM classifier respectively. From the comparison it is can be concluded that only 8 Laws' texture features namely {LLmean, LLsd, LEsd, SSskewness, RRenergy, LEenergy, LSenergy and LWenegy} can be used to build an efficient computer aided diagnostic (CAD) system for predicting of liver cirrhosis.
Assessment of Trihalomethane Formation in Chlorinated Raw Waters with Differential UV Spectroscopy Approach

In this study, the changes in UV absorbance of water samples were characterized using defined differential UV spectroscopy (DUV), a novel spectroscopic technique. Chlorination experiments were conducted with water samples from Terkos Lake (TL) and Büyükçekmece Lake (BL) (Istanbul, Turkey). The maximum loss of UV absorbance for chlorinated TL and BL raw water samples was observed at a wavelength of 272 nm. Interestingly, differential absorbance at 272 nm (ΔUV272) was shown to be a good indicator of UV absorbing chromophores and the formation of trihalomethanes (THMs) resulting from chlorination. Furthermore, differential spectra of chlorinated TL waters were similar for given chlorination conditions, peaking at 272 nm. The correlations between THMs and ΔUV272 were quantified by linear equations with R 2 values >0.96. The concentration of THMs formed when natural organic matter is chlorinated increases with increasing time and pH levels. Among all THMs, CHCl3 was the dominant species forming as a result of the chlorination of TL and BL raw water samples. The highest chloroform (CHCl3), dichlorobromomethane (CHCl2Br), and dibromochloromethane (CHBr2Cl) concentration were released per unit loss of absorbance at 272 nm at pH 9 with a maximum reaction time of 168 hours and Cl2/dissolved organic carbon ratio of 3.2.
Research on media cognition practical projects curriculum

With the development of digital signal processing, the field of media cognition has more attention which is the necessary method to achieve human-computer interaction technology. The electronic media is a new human civilization carrier which will give birth to new culture and arts. Media cognition projects practice is set up to accomplish the target of cultivating talented person. This paper shows some new practical projects curriculum on media cognition. Students complete a series of small independent media cognition practical projects curriculum to fully stimulate students' interest in the related research areas. High-level talents will be trained by these practical projects. Analysis shows that the media cognition practical projects curriculum improved the ability to acquire the relevant knowledge and in-depth investigation of project programming.