Miracle-dz/UniFAR-FTUs huggingface dataset:
FOLFOX in patients with metastatic colorectal cancer and high alkaline phosphatase level: an exploratory cohort of the GERCOR OPTIMOX1 study.

BACKGROUND Alkaline phosphatase (ALP) is a strong prognostic factor in patients with metastatic colorectal cancer (MCRC). Patients with ALP more than three times the upper limit of normal (ULN) were excluded from our previous studies evaluating chemotherapy. An exploratory cohort of patients with ALP >3 ULN was included in the OPTIMOX1 study. PATIENTS AND METHODS Previously untreated patients with MCRC were randomized to FOLFOX4 until progression (arm A) or FOLFOX7 for six cycles, maintenance without oxaliplatin for 12 cycles and reintroduction of FOLFOX7 (arm B). Patients were stratified according to ALP level <or=3 ULN versus 3-5 ULN. RESULTS Among the 620 patients in OPTIMOX1 study, 63 had ALP 3-5 ULN; 33 in arm A and 30 in arm B. The response rate in these patients was 56% versus 59% in patients with ALP <or=3 ULN. Median progression-free survival and overall survival were, respectively, 6.4 and 11.5 months in patients with ALP 3-5 ULN and 9.0 and 21.1 months in patients with ALP <or=3 ULN. Thirty-three percent of the patients in the cohort experienced grade 3/4 toxicity. CONCLUSION Both FOLFOX regimens achieved high tumor response rates and offer good palliation in MCRC patients with a poor prognosis.
Chromatic Search Trees Revisited Institut F Ur Informatik | Report 91

Relaxed balancing of search trees was introduced with the aim of speeding up the updates and allowing a high degree of concurrency. In a relaxed version of a search tree the rebalancing operations are uncoupled from the updates and may be delayed. Using local transformations the rebalancing can be performed concurrently with updates and search operations. In this paper we revisit the rebalancing of chromatic trees, a relaxed version of red-black trees. During the rebalancing of a chromatic tree it can occur that the rebalancing operations change the search structure of the tree in order to settle rebalancing requests from the history although the tree is already a balanced red-black tree. We propose how to perform the rebalancing task in such a way that each performed structural change indeed correspond to a real imbalance situation in the tree. The number of rebalancing operations needed to restore the red-black tree balance condition is still O(i+d) pointer changes and O((i+d) log(n+ i)) colour changes, if i insertions and d deletions are applied to a chromatic tree of size n that initially ful lls the balance condition of red-black trees.
Meditation effects within the hippocampal complex revealed by voxel-based morphometry and cytoarchitectonic probabilistic mapping

Scientific studies addressing anatomical variations in meditators' brains have emerged rapidly over the last few years, where significant links are most frequently reported with respect to gray matter (GM). To advance prior work, this study examined GM characteristics in a large sample of 100 subjects (50 meditators, 50 controls), where meditators have been practicing close to 20 years, on average. A standard, whole-brain voxel-based morphometry approach was applied and revealed significant meditation effects in the vicinity of the hippocampus, showing more GM in meditators than in controls as well as positive correlations with the number of years practiced. However, the hippocampal complex is regionally segregated by architecture, connectivity, and functional relevance. Thus, to establish differential effects within the hippocampal formation (cornu ammonis, fascia dentata, entorhinal cortex, subiculum) as well as the hippocampal-amygdaloid transition area, we utilized refined cytoarchitectonic probabilistic maps of (peri-) hippocampal subsections. Significant meditation effects were observed within the subiculum specifically. Since the subiculum is known to play a key role in stress regulation and meditation is an established form of stress reduction, these GM findings may reflect neuronal preservation in long-term meditators—perhaps due to an attenuated release of stress hormones and decreased neurotoxicity.
Path and Observation Planning of Vision-based Mobile Robots with Multiple Sensing Strategies

In this paper, we propose a new path and viewpoint planning method for a mobile robot with multiple observation strategies. When a mobile robot works in the constructed environments such as indoor, it is very effective and reasonable to attach landmarks on the environment for the vision-based navigation. In that case, it is important for the robot to decide its motion automatically. Therefore, we propose a motion planning method that optimizes the efficiency of the task, the danger of colliding with obstacles, and the accuracy and the ease of the observation according to the situation and the performance of the robots.
The Influence of Alcohol Intoxication on Adolescent Sexual Intercourse and Contraception Use

We use the method of situational decomposition in an attempt to identify the causal effect of alcohol intoxication on adolescent sexual intercourse and contraception use. This approach assumes that the relationship between frequency of alcohol intoxication and behavior while sober is entirely spurious. With this in mind, the total association between drinking and behavior can be decomposed into spurious and “non-spurious” (i.e., causal) components. The larger the magnitude of the total association relative to the spurious association, the larger the influence of alcohol on behavior. This method was employed to analyze data from the first wave of National Longitudinal Study of Adolescent to Adult Health (Add Health) in-home interview (N = 20,743). The results suggest that almost all of the relationship between alcohol and sexual intercourse is spurious. On the contrary, alcohol intoxication was found to reduce the use of contraceptives during sexual intercourse, especially among boys.
On a question of Gowers

We show that any subset of density 100 log 1/4 ∗ n of an n by n square in Z contains an isoceles right-angle triangle with a fixed orientation whose sizes are parallel to the axes, for all sufficiently large n. AMS Subject Classificiation Numbers: 05, 11.
Social Architecture and the Emergence of Power Laws in Online Social Games

This paper explores the concept of the “social architecture” of games, and tests the theory that it is possible to analyse game mechanics based on the effect they have on the social behaviour of the players. Using tools from Social Network Analysis, these studies confirm that social activity in games reliably follows a power distribution: a few players are responsible for a disproportionate amount of social interactions. Based on this, the scaling exponent is highlighted as a simple measure of sociability that is constant for a game design. This allows for the direct comparison of social activity in very different games. In addition, it can act as a powerful analytical tool for highlighting anomalies in game designs that detrimentally affect players’ ability to interact socially. Although the social architectures of games are complicated systems, SNA allows for quantitative analysis of social behaviours of players in meaningful ways, which are to the benefit of game designers.
Comprehensive evaluation on housing market supply & demand based on principal component analysis: the case of Xi'an, China

At present, China's housing prices and structures have been severe distorted, which have been done serious harm on the development of national economy and people's lives, the government has implemented the most strictest macro-control. This paper applies the correlation and principal component analysis on the supply & demand of housing market. Aims to points out clear direction for the implementation of macro-control policies in the future.
Clustering and Mapping Violence News Events

It is difficult to follow the entirity of the global of news sources , and the events happening everyday. If an analyst in her area has to follow and map all these according to the timeline they happen, the task quickly becomes overwhelming. We present an online tool which attempts to ease the analyst’s task of finding all news articles about an event, and sorting and mapping them on a timeline. We implemented an incremental clustering algorithm working on real-time incoming news, experimenting with different feature sets, including named entities and sentence overlap methods. We evaluated these approaches using Document Understand Conference (DUC) datasets
the Second EECE 512 Mini-Conference on Computer Security

Version 2.5 of the Python programming language contains no mechanism for restricting access to resources by Python code. This is a slight hindrance to the language as it is used in many situations, such as a domain-speciﬁc language in other applications, where some mechanism to control what resources Python code can access would be helpful. Python did once have a security mechanism for restricting resource access, but it was disabled in version 2.3. The disabling of the security mechanism was driven by a lack of security expertise on the part of the Python development team. This means that any introduced security mechanism should, if possible, not require language support so as to prevent the need to turn off any new security mechanism in the future. This paper presents a security mechanism whose impact upon the Python language is minimal. By removing four function or methods from Python’s built-in namespace and utilizing Python’s modularity in terms of its connection with its underlying inter-preter, the proposed security mechanism has minimal impact upon the language. The mechanism allows for controlling access to resources within a single Python interpreter. This allows Python to have some form of a security mechanism between Python code and the system it is running on.
Narrow Proofs May Be Maximally Long ( Extended

We prove that there are 3-CNF formulas over n variables that can be refuted in resolution in width w but require resolution proofs of size n. This shows that the simple counting argument that any formula refutable in width w must have a proof in size n is essentially tight. Moreover, our lower bounds can be generalized to polynomial calculus resolution (PCR) and Sherali-Adams, implying that the corresponding size upper bounds in terms of degree and rank are tight as well. Our results do not extend all the way to Lasserre, however—the formulas we study have Lasserre proofs of constant rank and size polynomial in both n and w. Keywords-proof complexity; resolution; polynomial calculus; PCR; Sherali-Adams; Lasserre; size; length; width; degree; rank
Online dictionary learning for kernel LMS. Analysis and forward-backward splitting algorithm

Adaptive filtering algorithms operating in reproducing kernel Hilbert spaces have demonstrated superiority over their linear counterpart for nonlinear system identification. Unfortunately, an undesirable characteristic of these methods is that the order of the filters grows linearly with the number of input data. This dramatically increases the computational burden and memory requirement. A variety of strategies based on dictionary learning have been proposed to overcome this severe drawback. Few, if any, of these works analyze the problem of updating the dictionary in a time-varying environment. In this paper, we present an analytical study of the convergence behavior of the Gaussian least-mean-square algorithm in the case where the statistics of the dictionary elements only partially match the statistics of the input data. This allows us to emphasize the need for updating the dictionary in an online way, by discarding the obsolete elements and adding appropriate ones. We introduce a kernel least-mean-square algorithm with L1-norm regularization to automatically perform this task. The stability in the mean of this method is analyzed, and its performance is tested with experiments.
A Tutorial on Information Retrieval Modelling

Many applications that handle information on the internet would be completely inadequate without the support of information retrieval technology. How would we find information on the world wide web if there were no web search engines? How would we manage our email without spam filtering? Much of the development of information retrieval technology, such as web search engines and spam filters, requires a combination of experimentation and theory. Experimentation and rigorous empirical testing are needed to keep up with increasing volumes of web pages and emails. Furthermore, experimentation and constant adaptation of technology is needed in practice to counteract the effects of people that deliberately try to manipulate the technology, such as email spammers. However, if experimentation is not guided by theory, engineering becomes trial and error. New problems and challenges for information retrieval come up constantly. They cannot possibly be solved by trial and error alone. So, what is the theory of information retrieval? There is not one convincing answer to this question. There are many theories, here called formal models, and each model is helpful for the development of some information retrieval tools, but not so helpful for the development others. In order to understand information retrieval, it is essential to learn about these retrieval models. In this chapter, some of the most important retrieval models are gathered and explained in a tutorial style. But first, we will describe what exactly it is that these models model.
Modeling in Big Data Environments

Human-Centered Big Data Research (HCBDR) is an area of work that focuses on the methodologies and research areas focused on understanding how humans interact with "big data". In the context of this paper, we refer to "big data" in a holistic sense, including most (if not all) the dimensions defining the term, such as complexity, variety, velocity, veracity, etc. Simply put, big data requires us as researchers of to question and reconsider existing approaches, with the opportunity to illuminate new kinds of insights that were traditionally out of reach to humans.
Neisseria meningitidis infection of human endothelial cells interferes with leukocyte transmigration by preventing the formation of endothelial docking structures

Neisseria meningitidis elicits the formation of membrane protrusions on vascular endothelial cells, enabling its internalization and transcytosis. We provide evidence that this process interferes with the transendothelial migration of leukocytes. Bacteria adhering to endothelial cells actively recruit ezrin, moesin, and ezrin binding adhesion molecules. These molecules no longer accumulate at sites of leukocyte–endothelial contact, preventing the formation of the endothelial docking structures required for proper leukocyte diapedesis. Overexpression of exogenous ezrin or moesin is sufficient to rescue the formation of docking structures on and leukocyte migration through infected endothelial monolayers. Inversely, expression of the dominant-negative NH2-terminal domain of ezrin markedly inhibits the formation of docking structures and leukocyte diapedesis through noninfected monolayers. Ezrin and moesin thus appear as pivotal endothelial proteins required for leukocyte diapedesis that are titrated away by N. meningitidis. These results highlight a novel strategy developed by a bacterial pathogen to hamper the host inflammatory response by interfering with leukocyte–endothelial cell interaction.
An ontology-driven approach for semantic information retrieval on the Web

The concept of relevance is a hot topic in the information retrieval process. In recent years the extreme growth of digital documents brought to light the need for novel approaches and more efficient techniques to improve the accuracy of IR systems to take into account real users' information needs. In this article we propose a novel metric to measure the semantic relatedness between words. Our approach is based on ontologies represented using a general knowledge base for dynamically building a semantic network. This network is based on linguistic properties and it is combined with our metric to create a measure of semantic relatedness. In this way we obtain an efficient strategy to rank digital documents from the Internet according to the user's interest domain. The proposed methods, metrics, and techniques are implemented in a system for information retrieval on the Web. Experiments are performed on a test set built using a directory service having information about analyzed documents. The obtained results compared to other similar systems show an effective improvement.
Supporting disease insight through data analysis: refinements of the monarca self-assessment system

There is a growing interest in personal health technologies that sample behavioral data from a patient and visualize this data back to the patient for increased health awareness. However, a core challenge for patients is often to understand the connection between specific behaviors and health, i.e. to go beyond health awareness to disease insight. This paper presents MONARCA 2.0, which records subjective and objective data from patients suffering from bipolar disorder, processes this, and informs both the patient and clinicians on the importance of the different data items according to the patient's mood. The goal is to provide patients with a increased insight into the parameters influencing the nature of their disease. The paper describes the user-centered design and the technical implementation of the system, as well as findings from an initial field deployment.
C-HeavyAP: a centralized approach for optimal AP backhaul resource aggregation

Wireless communications markets present rapidly changing technology, evolving customer demands, and the emergence of new products and services. Within spectral limitations, wireless standards end up competing for optimal network performance and better client satisfaction, especially for residential scenarios and hotspots. In actual wireless networks, the main issue of resource management concerns the one-to-one link constraint. In fact, each station is connected to one Access Point (AP) at once, where several are reachable. Therefore, wireless clients should be able to use every available resource within range. In this context, stands the idea of AP backhaul bandwidth aggregation. This paper introduces an enhanced solution, Centralized- HeavyAP, for backhaul resource aggregation. Our solution focuses on symmetric AP-to-AP level and proposes several upgrades for optimal allocation of available backhaul resource. Within an adequate optimization method, namely the Newton method, we succeeded to establish weighted throughput and load balance among APs in the same network.
Deterrents to women taking computer science courses

The United States faces a shortage of computer scientists. Despite the current economic downturn, the most recent estimate indicates a labor force shortage of IT professionals. The shortage of IT professionals, and especially of computer scientists, provides impetus for increasing the representation of women in computer science (CS). We examine why so few students, and particularly few women, choose to enter the beginning phase of the CS pipeline by choosing to try out CS courses. Women are seriously under-represented at this early juncture of the CS pipeline. If we are serious about making CS a more inclusive field, we need to make an impact at this early juncture. This is not to belittle the laudable efforts to reduce attrition among women CS majors. However, for maximum effect, interventions to increase the flow of women into the CS pipeline also need to occur before women declare their major.
A short introduction to information theory and Bayesian Model Averaging

1.2. Optimal code length for a known source. In the case when PXn (the distribution of X n = (X1, . . . , Xn)) is known and c is arbitrary, minimizing the code length is achieved by sorting A in order of decreasing probabilities. More precisely, let us write A = {bi, i = 1, . , d}, where d = |A| is the size of the alphabet and where the blocks of n letters are indexed by order of decreasing probabilities:
A dynamic spectrum decision algorithm for underwater cognitive acoustic networks

Cognitive acoustic (CA) is emerging as a promising technique for spectrum-efficient Underwater Acoustic Networks (UANs). Due to the unique features of UANs, especially the long propagation delay, the busy terminal problem and large interference range, traditional spectrum decision methods used for radio networks need an overhaul to work efficiently in underwater environment. In this paper, we propose a dynamic spectrum decision algorithm called Receiver-viewed Dynamic Borrowing (RvDB) algorithm for Underwater Cognitive Acoustic Networks (UCANs) to improve the efficiency of spectrum utilization. RvDB algorithm is with the following features. Firstly, the spectrum resource is decided by receiver. Secondly, the receivers can borrow the idle spectrum resource from neighbouring nodes dynamically. Finally, the spectrum sensing is completed by control packets on control channel which is separated from data channels. Simulation results show that RvDB algorithm can greatly improve the performance on spectrum efficiency.
Parametric design and optimization of multi-rotor aerial vehicles

This work addresses the optimal selection of propulsion components for a multi-rotor aerial vehicle (MRAV), for a given payload, payload capacity, number of rotors and flight duration. A steady state model is developed for motors, propellers, electronic speed controllers (ESC), and batteries, using a simplified analysis. Based on technical specifications of batteries, motors and ESCs, component functional parameters are expressed as a function of an equivalent length. Propeller models are developed using experimental data. An optimization program is developed, which calculates the optimal design vector, employing as objective function the energy consumption or the vehicle diameter. Using this program, the influence of the payload and of the number of rotors on the design vector and the MRAV size is studied. The results obtained by the program were compared successfully to existing commercial MRAVs.
Natural Volatility, Welfare and Taxation

Cyclical components are analytically computed in a theoretical model of stochastic endogenous fluctuations and growth. Volatility is shown to depend on the speed of convergence of the cyclical component, the expected length of a cycle and on the altitude of the slump. Taxes affect these channels and can therefore explain cross-country differences and breaks over time in volatility. With exogenous sources of fluctuations, a special case of our model, decentralized factor allocation is efficient. With endogenous fluctuations and growth, decentralized factor allocation is inefficient and (time-invariant) taxes can (de-) stabilize the economy. No unambiguous link exists between volatility and welfare.