Miracle-dz/UniFAR-FTUs huggingface dataset:
Applications of Machine Learning in Cancer Prediction and Prognosis

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on “older” technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15–25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.
An Optimal Quantity Discounting Pricing Policy for Ameliorating Items

Recently, retailers who directly deal with poultry farmers increase in Japan. It therefore becomes necessary for the poultry farmers to deliver products to the retailers frequently in accordance with the retailers’ demand. The retailer purchases (raw) chicken meat from the poultry farmer. The stock of the poultry farmer increases due to growth, in contrast, the inventory level of the retailer is depleted due to the combined effect of its demand and deterioration. The poultry farmer attempts to increase her profit by controlling the retailer’s ordering schedule through a quantity discount strategy. We formulate the above problem as a Stackelberg game between the poultry farmer and the retailer to analyze the existence of the poultry farmer’s optimal quantity discount pricing policy which maximizes her total profit per unit of time. The same problem is also formulated as a cooperative game. Numerical examples are presented to illustrate the theoretical underpinnings of the proposed formulation.
Fusion of multiple features in Magnetic resonant image segmentation using genetic algorithm

In healthcare applications, there is tremendous growth in using the computer assistance for effective and fast diagnostic. There are various modalities such as Magnetic resonance imaging (MRI), computed tomography (CT), digital mammography, and others, to provide an insight of subject's body, noninvasively in order to facilitate diagnostic stakeholders to take decision in diagnosis. Being an important step of imaging systems in diagnostic, MRI imaging has been active area for researchers in computational intelligence and image processing. One of the most important problems in image processing and analysis is segmentation and same is true for biomedical imaging. The main objective of segmentation is separating the pixels associated with different types of tissues like white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). In this paper, we attempted to optimize the feature set constructed from more than three different types of features. It is well-known fact that, long feature vector representation can be boosting the performance. However, irrelevant feature elements from the long feature vector can become hurdle in convergence of classifier. The optimization feature vector is accomplished using genetic algorithm (GA) with an objective function of maximizing the sum of precision and recall. In addition to the elimination of the feature elements, some elements were also weighted to reduce their effect in the feature matching score. This overall process can also be considered as “fusion of features” for MRI segmentation.
Active documents : satisfiability of queries and view maintenance

We consider the evolution of active documents, and, more pre cisely, of Active XML documents with incoming streams of dat a. A main contribution of the paper is a study of “document satis fi bility” defined as follows. A formula issatisfiable for a document if it may hold in some future (depending on data brought by the incoming streams). We show how to evaluate document satisfiabi lity of tree-pattern queries using non-recursive datalog. We ch ara terize the complexity of this problem for important variants of the document model and the query language. We use this notion together with known datalog techniques (Di fferential and MagicSet) for maintaining views over active documents. We also exhibi t optimization techniques that consist in pushing filters to the in coming streams and garbage collecting data and streams that are use less with respect to the views of interest.
Constructing application-specific heterogeneous embedded architectures from custom HW/SW applications

Deep sub-micron processing technologies have enabled the implementation of new application-specific embedded architectures that integrate multiple software programmable processors (e.g. DSPs, microcontrollers) and dedicated hardware components together onto a single cost-efficient IC. These application-specific architectures are emerging as a key design solution to today's microelectronics design problems, which are being driven by emerging applications in the areas of wireless communication, broadband networking, and multimedia computing. However the construction of these customized heterogeneous multiprocessor architectures, while ensuring that the hardware and software parts communicate correctly, is a tremendously difficult and highly error proned task with little or no tool support. In this paper, we present a solution to this embedded architecture co-synthesis problem based on an orchestrated combination of architectural strategies, parameterized libraries, and software tool support.
Van der Waerden/Schrijver-Valiant like Conjectures and Stable (aka Hyperbolic) Homogeneous Polynomials: One Theorem for all

Let $p$ be a homogeneous polynomial of degree $n$ in $n$ variables, $p(z_1,.,z_n) = p(Z)$, $Z \in C^{n}$. We call such a polynomial $p$ {\bf H-Stable} if $p(z_1,.,z_n) \neq 0$ provided the real parts $Re(z_i) > 0, 1 \leq i \leq n$. This notion from {\it Control Theory} is closely related to the notion of {\it Hyperbolicity} used intensively in the {\it PDE} theory. The main theorem in this paper states that if $p(x_1,.,x_n)$ is a homogeneous {\bf H-Stable} polynomial of degree $n$ with nonnegative coefficients; $deg_{p}(i)$ is the maximum degree of the variable $x_i$, $C_i = \min(deg_{p}(i),i)$ and $$ Cap(p) = \inf_{x_i > 0, 1 \leq i \leq n} \frac{p(x_1,.,x_n)}{x_1 . x_n} $$ then the following inequality holds $$ \frac{\partial^n}{\partial x_1. \partial x_n} p(0,.,0) \geq Cap(p) \prod_{2 \leq i \leq n} (\frac{C_i -1}{C_i})^{C_{i}-1}. $$ This inequality is a vast (and unifying) generalization of the Van der Waerden conjecture on the permanents of doubly stochastic matrices as well as the Schrijver-Valiant conjecture on the number of perfect matchings in $k$-regular bipartite graphs. These two famous results correspond to the {\bf H-Stable} polynomials which are products of linear forms. Our proof is relatively simple and ``noncomputational''; it uses just very basic properties of complex numbers and the AM/GM inequality.
Optimal Design and ρ-Concavity

Some of the most beautiful results in mechanism design depend crucially on Myersons (1981) regularity condition. E.g., the second-price auction with reserve price is revenue maximizing only if the type distribution is regular. This paper o¤ers two main results. First, an interpretation of regularity is developed in terms of being the next to fail. Second, using expanded concepts of concavity, a tight su¢ cient condition on the density function is formulated. New examples of parameterized distributions are shown to be regular. Applications include standard design problems, optimal reserve prices, the analysis of bidding data, and multidimensional types. Keywords and Phrases. Virtual valuation, Regularity, Generalized concavity, Prékopa-Borell Theorem, Mechanism design. JEL-Codes. D82 Asymmetric and Private Information; D44 Auctions; D86 Economics of Contract: Theory; C16 Speci c Distributions. 1. Introduction Some of the best-known results in the theory of mechanism design require that the underlying type distribution be regular. For example, the secondprice auction with reserve price is revenue maximizing only under the condition of regularity.1 It is therefore of some interest to clarify the meaning and scope of the assumption. Formally, regularity says that the virtual valuation, Jf (x) = x 1 F (x) f(x) , (1) is strictly increasing in the type x, where f and F , respectively, denote the density and distribution function of the type distribution.2 A simple way to ensure regularity is to impose that the hazard rate of the type distribution, f (x) = f(x) 1 F (x) , (2) is monotone increasing. This approach has been found useful mainly for two reasons. First, the hazard rate allows an immediate interpretation as a conditional likelihood of failure.3 Second, distributions with log-concave densities are known to possess a monotone hazard rate.4 However, the hazard rate condition will often be more restrictive than necessary. For example, the log-normal distribution does not possess a monotone 1Cf. Myerson [15]. When the type distribution is not regular, the optimal mechanism will typically entail conditional minimum bids, see Maskin and Riley [13]. 2Equivalently, the marginal revenue of a monopolist facing inverse demand p = F (1 q) is strictly declining in output. See Bulow and Roberts [5]. 3Indeed, if F (x) is the probability that a machine will fail before time x, then the hazard rate is the instantaneous probability of failure, given that the machine has not failed before time x. See, e.g., Barlow and Proschan [3]. 4See, e.g., An [1]. This result can be used to identify many parameterized examples of regular type distributions. Speci cally, as Bagnoli and Bergström [2] show, regularity holds for the uniform, normal, exponential, logistic, extreme value, Laplace, Maxwell, and Rayleigh distributions. With restrictions to parameters, this list extends to power, Weibull, Gamma, Chi-Squared, Chi, and beta distributions.
Trends in Patients Hospitalized With Heart Failure and Preserved Left Ventricular Ejection Fraction: Prevalence, Therapies, and Outcomes

Background— Heart failure with preserved ejection fraction (EF) is a common syndrome, but trends in treatments and outcomes are lacking. Methods and Results— We analyzed data from 275 hospitals in Get With the Guidelines–Heart Failure from January 2005 to October 2010. Patients were stratified by EF as reduced EF (EF <40% [HF–reduced EF]), borderline EF (40%⩽EF<50% [HF–borderline EF]), or preserved (EF ≥50% [HF–preserved EF]). Using multivariable models, we examined trends in therapies and outcomes. Among 110 621 patients, 50% (55 083) had HF–reduced EF, 14% (15 184) had HF–borderline EF, and 36% (40 354) had HF–preserved EF. From 2005 to 2010, the proportion of hospitalizations for HF–preserved EF increased from 33% to 39% (P<0.0001). In multivariable analyses, use of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers at discharge decreased in all EF groups, and &bgr;-blocker use increased. Patients with HF–preserved EF less frequently achieved blood pressure control (adjusted odds ratio, 0.44 versus HF–reduced EF; P<0.001) and were more likely discharged to skilled nursing (adjusted odds ratio, 1.16 versus HF–reduced EF; P<0.001). In-hospital mortality for HF–preserved EF decreased from 3.32% in 2005 to 2.35% in 2010 (adjusted odds ratio, 0.89 per year; P=0.01) but was stable for patients with HF–reduced EF (3.03%–2.83%; adjusted odds ratio, 0.93 per year; P=0.10). Conclusions— Hospitalization for HF–preserved EF is increasing relative to HF–reduced EF. Although in-hospital mortality for patients with HF–preserved EF declined over the study period, an important opportunity remains for identifying evidence-based therapies in patients with HF–preserved EF.
Euclidean Structure Recovery through Articulated

This paper derives a direct constraint satissed by points on the axis of articulation of a compound object. A minimum of three views of the articulated object in motion are required to recover the projective position of the articulation axis. No camera calibration is required. The method given here is a signiicant improvement on a previous method, doing away entirely with the need to use the fundamental matrix in building an intermediate constraint 19]. This paper also extends the Euclidean structure from uncalibrated stereo result of Faugeras 3] to use the second link in an articulated system eeectively as a virtual second camera. Euclidean structure may then be recovered by observing an articulated object in motion with a single uncalibrated camera.
High dose intensity doxorubicin in aggressive non-Hodgkin's lymphoma: a literature-based meta-analysis.

BACKGROUND Aggressive non-Hodgkin's lymphoma (NHL) represents approximately 60% of lymphomas in the West and even more in the developing world. cyclophosphamide, doxorubicin, vincristine and prednisone (CHOP) is recognized as the standard chemotherapy regimen and the addition of rituximab to B-cell subtypes has been shown to significantly improve treatment outcomes. Nevertheless, still a significant fraction of patients is not offered rituximab due to economic reasons. Thus, CHOP is still offered to these patients as well as those with T-cell subtypes. Data from the early 1990s have indicated that the dose intensity (DI) of doxorubicin is a key factor in predicting survival. METHODS A Medline and Cochrane library search was carried out using the search terms 'CHOP', 'lymphoma' and 'randomized trials'. Eligible trials had CHOP as a control arm and any regimen administering doxorubicin at a higher DI (16.6 mg/m(2)/week) as the investigational arm. Pooling of data was carried out using the mixed effect model. RESULTS Eight trials were eligible. Patients receiving DI doxorubicin-based regimens had a significantly better overall survival [summary hazard ratio (SHR) 0.82; 95% confidence interval (CI) 0.71-0.96], event-free survival (SHR 0.86; 95% CI 0.75-0.99) and higher complete response rate (summary odds ratio 0.91; 95% CI 0.67-0.97). CONCLUSION High DI doxorubicin based should be considered in patients with aggressive NHL.
Counting Set Systems by Weight

Applying the enumeration of sparse set partitions, we show that the number of set systems H such that the emptyset is not in H, the total cardinality of edges in H is n, and the vertex set of H is {1, 2, . , m}, equals (1/log(2)+o(1))^nb_n where b_n is the n-th Bell number. The same asymptotics holds if H may be a multiset. If vertex degrees in H are restricted to be at most k, the asymptotics is (1/alpha_k+o(1))^nb_n where alpha_k is the unique root of x^k/k! +. +x^1/1! -1 in (0,1].
Comparing Stance in Chinese EFL learners ’ English and Chinese argumentative essays of a shared topic

Writers’ stance can be communicated by various linguistic means in both English and Chinese. Previous research (Camiciottoli 2004; Neff 2004; Xu 2007; Liang 2008) shows that L2 learners of English, even for advanced learners, are not capable of taking their stance appropriately in English. This study takes a contrastive approach to examine the stance markers in 122 pieces of Chinese learners’ English and Chinese argumentative essays of a shared topic “Is the Internet a blessing or a curse? ” Each learner was asked to write an English essay first and then the other one in Chinese. An annotation scheme of stance marking categories (epistemic, deontic, attitudinal and textual) was devised to manually annotate the 122 parallel texts. The results show that the overall occurrences of stance markers in the 61 English texts are considerably correlated (r = .592) with those in the 61 corresponding Chinese texts. Namely, in terms of stance marking, Chinese learners’ English essays share the tendency of their Chinese essays. A closer look at individual stance categories specifies that epistemic, attitudinal and textual markers are correlated with their Chinese counterparts at r = . 306, r = . 578, r = . 444 respectively, with attitudinal the highest. This coincides with Xu (2007) in that Chinese learners of English tend to be unduly involved with personal judgments and attitudes in academic writing. The follow-up concordance analysis of the texts reveals that Chinese learners of English tend to use similar semantic stance types in two languages on the one hand, and employ lexical and phrasal items, which are literal translations to each other, on the other. The apparent alignment in semantic types and lexical realizations of stance sheds some light of cross-linguistic influence of Chinese on learners’ English writing.
Design decision trees

The paper proposes a formalism to be used as a systematic approach to incrementally document, refine, organise and reuse the architectural knowledge for software design. The formalism is a hierarchical organisation of design patterns into a design decision tree (DDT) that is a partial ordering of design decisions put in the context of the problem requirements and the constraints imposed by earlier decisions. Our model supports the representation of the essential problems that recur in the domain, knowledge of alternative solutions to these problems and the implications of the solutions. This model integrates architectural knowledge of software design into a software development process.
Blockade of Endocannabinoid-Degrading Enzymes Attenuates Neuropathic Pain

Direct-acting cannabinoid receptor agonists are well known to reduce hyperalgesic responses and allodynia after nerve injury, although their psychoactive side effects have damped enthusiasm for their therapeutic development. Alternatively, inhibiting fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MAGL), the principal enzymes responsible for the degradation of the respective endogenous cannabinoids, anandamide (AEA) and 2-arachydonylglycerol (2-AG), reduce nociception in a variety of nociceptive assays, with no or minimal behavioral effects. In the present study we tested whether inhibition of these enzymes attenuates mechanical allodynia, and acetone-induced cold allodynia in mice subjected to chronic constriction injury of the sciatic nerve. Acute administration of the irreversible FAAH inhibitor, cyclohexylcarbamic acid 3′-carbamoylbiphenyl-3-yl ester (URB597), or the reversible FAAH inhibitor, 1-oxo-1-[5-(2-pyridyl)-2-yl]-7-phenylheptane (OL-135), decreased allodynia in both tests. This attenuation was completely blocked by pretreatment with either CB1 or CB2 receptor antagonists, but not by the TRPV1 receptor antagonist, capsazepine, or the opioid receptor antagonist, naltrexone. The novel MAGL inhibitor, 4-nitrophenyl 4-(dibenzo[d][1,3]dioxol-5-yl(hydroxy)methyl)piperidine-1-carboxylate (JZL184) also attenuated mechanical and cold allodynia via a CB1, but not a CB2, receptor mechanism of action. Whereas URB597 did not elicit antiallodynic effects in FAAH(-/-) mice, the effects of JZL184 were FAAH-independent. Finally, URB597 increased brain and spinal cord AEA levels, whereas JZL184 increased 2-AG levels in these tissues, but no differences in either endo-cannabinoid were found between nerve-injured and control mice. These data indicate that inhibition of FAAH and MAGL reduces neuropathic pain through distinct receptor mechanisms of action and present viable targets for the development of analgesic therapeutics.
Fault-aware scheduling for Bag-of-Tasks applications on Desktop Grids

Desktop grids have proved to be a suitable platform for the execution of bag-of-tasks applications but, being characterized by a high resource volatility, require the availability of scheduling techniques able to effectively deal with resource failures and/or unplanned periods of unavailability. In this paper we present a set of fault-aware scheduling policies that, rather than just tolerating faults as done by traditional fault-tolerant schedulers, exploit the information concerning resource availability to improve application performance. The performance of these strategies have been compared via simulation with those attained by traditional fault-tolerant schedulers. Our results, obtained by considering a set of realistic scenarios modeled after real desktop grids, show that our approach results in better application performance and resource utilization
Multi-oriented moving text detection

Detection of moving text of different orientations in video is challenging because of low resolution and complex background of video. In this paper, we propose a method based on motion vectors to identify the moving blocks which have linear and constant velocity. For each block, we compute moments and use k-means clustering algorithm to extract text candidate. We introduce a new criterion based on gradient direction of pixels in text candidates to remove false text candidates which we outputs potential text candidates. Then the method performs region growing to group the potential text candidates which outputs text lines. The method is tested on both static and moving text video to evaluate the performance in terms of recall, precision, F-measure, misdetection rate and time. The results are compared with the well-known existing methods to show effectiveness of the proposed method.
A comparative study of topic models for topic clustering of Chinese web news

Topic model is an increasing useful tool to analyze the semantic level meanings and capture the topical features. However, there is few research about the comparative study of the topic models. In this paper, we describe our comparative study of three topic models in the extrinsic application of topic clustering. The topic model distance is defined on the converged parameters of topic models, which is used in the topic clustering. Then, the topic models are compared using the clustering result of the corresponding topic distance matrix. A series of comparative experiments are carried on a corpus containing 5033 web news from 30 topics using the cosine distance as the base-line. Web page collections with different number of topics and documents are used in experiments. The experiment results show that topic clustering using topic distance achieves a better precision and recall in the data set containing related topics. The topic clustering using topic distance benefits from the topic features captured by topic models. The complex topic model does provide further help than the simple topic model in topic clustering.