Miracle-dz/UniFAR-FTUs huggingface dataset:
Drop the Likelihood Ratio

Summary Objective: To present a geometric ruler to determine predictive values of binary diagnostic test results from prevalence, sensitivity and specificity without calculation. Methods: On logarithmic scale the relationships between pre-/post-test odds and the likelihood ratio as well as sensitivity, specificity and the likelihood ratio appear as simple linear (additive) equations. Results: Each of these additive equations can be solved geometrically in form of a ruler with three scales. By amalgamation we devise a novel non-electronic tool which omits the intermediate step of likelihood ratio determination. Conclusions: We propose a simple geometric method to aid in interpretation of diagnostic test results for both practical and educational purposes.
Attitudes towards offensive advertising: Malaysian Muslims' views

Purpose – The purpose of this paper is to investigate the Malaysian Malays attitude towards offensive advertising and the reasons that make these advertisements offensive. This paper aims to explore the role of religiosity on attitudes towards controversial advertisements and the reasons why they are controversial.Design/methodology/approach – This paper consists of 279 randomly selected Malay participants. Data were analyzed using means, correlations, and ANOVA.Findings – Results indicate that those high on religiosity differ on the nature and manner of controversial advertisements from those of low religiosity. Malay Muslims when compared on their degree of religiosity differ in terms of their evaluation of offensive nature of advertisement. More important they differ more on the reason that make these advertisement offensive compared to the nature of the products.Research limitations/implications – Respondents are somewhat more skewed towards a younger population causing concern that the results might .
Differential privacy in control and network systems

As intelligent automation and large-scale distributed monitoring and control systems become more widespread, concerns are growing about the way these systems collect and make use of privacy-sensitive data obtained from individuals. This tutorial paper gives a systems and control perspective on the topic of privacy preserving data analysis, with a particular emphasis on the processing of dynamic data as well as data exchanged in networks. Specifically, we consider mechanisms enforcing differential privacy, a state-of-the-art definition of privacy initially introduced to analyze large, static datasets, and whose guarantees hold against adversaries with arbitrary side information. We discuss in particular how to perform tasks such as signal estimation, consensus and distributed optimization between multiple agents under differential privacy constraints.
Making lockless synchronization fast: performance implications of memory reclamation

Achieving high performance for concurrent applications on modern multiprocessors remains challenging. Many programmers avoid locking to improve performance, while others replace locks with non-blocking synchronization to protect against deadlock, priority inversion, and convoying. In both cases, dynamic data structures that avoid locking, require a memory reclamation scheme that reclaims nodes once they are no longer in use. The performance of existing memory reclamation schemes has not been thoroughly evaluated. We conduct the first fair and comprehensive comparison of three recent schemes -quiescent-state-based reclamation, epoch-based reclamation, and hazard-pointer-based reclamation - using a flexible microbenchmark. Our results show that there is no globally optimal scheme. When evaluating lockless synchronization, programmers and algorithm designers should thus carefully consider the data structure, the workload, and the execution environment, each of which can dramatically affect memory reclamation performance
Network traffic classification using AdaBoost Dynamic

Accurate traffic classification and identification is of paramount importance for proper network management and control in both edge and backbone networks. The use of Machine Learning (ML) algorithms has been gaining popularity due to its widespread availability and to its somewhat straightforward application to Internet traffic. This work focus on a specific case of using ML algorithms for network traffic classification. We introduce AdaBoost Dynamic with Logistic Function (AB-DL), an extension of AdaBoost. M1, that combines various classifiers to improve the final hypothesis. We carefully choose parameters from the flow records traces to improve the accuracy of the algorithms. Tests were executed with a publicly available data set from Ground Truth, and the other simulation was executed in a data set generated from University, that is not public. Results show that AB-DL achieve accuracy of 93% and 98.1%, respectively from each data set.
CONSISTENCY OF THE HYBRID REGULARIZATION WITH HIGHER COVARIANT DERIVATIVE AND INFINITELY MANY PAULI–VILLARS

We study the regularization and renormalization of the Yang–Mills theory in the framework of the manifestly invariant formalism, which consists of a higher covariant derivative with an infinitely many Pauli–Villars fields. Unphysical logarithmic divergence, which is the problematic point on the Slavnov method, does not appear in our scheme, and the well-known value of the renormalization group functions are derived. The cancellation mechanism of the quadratic divergence is also demonstrated by calculating the vacuum polarization tensor of the order of Λ0 and Λ-4. These results are the evidence that our method is valid for intrinsically divergent theories and is expected to be available for the theory which contains the quantity depending on the space–time dimensions, like supersymmetric gauge theories.
Tree-BASE: A database of phylogenetic information

A heat exchanger for exchanging heat between fluids comprising a conduit for flow of a first fluid therethrough comprising a manifold with a single port in one area and a pair of ports in another area and a plurality of spaced fluid tubes attached to the pair of ports with the combination of the plurality of tubes having outer peripheral surfaces describing a cylinder and the inner confronting peripheral surfaces spaced apart to provide an open area therebetween for flow of a second fluid therethrough and means for directing the second fluid over and around both the inner and outer peripheral surfaces and through the open area between the tubes for achieving maximum surface area heat transfer with minimum cross sectional area of the conduits.
Influence of Body Weight and Gender on the Pharmacokinetics, Pharmacodynamics, and Antihypertensive Efficacy of Aliskiren

Gender and body weight influence the pharmacokinetics and pharmacodynamics of many drugs. This pooled analysis of 17 clinical studies evaluated the effect of gender, body mass index (BMI), body weight, and lean body weight (LBW) on the pharmacokinetics of the direct renin inhibitor aliskiren in healthy volunteers (n = 392). A separate pooled analysis of 5 clinical studies in patients with hypertension (n = 2327) assessed the influence of gender and BMI on the effects of aliskiren on plasma renin activity and blood pressure. Area under the aliskiren plasma concentration‐time curve (AUCτ) was 22% lower and the peak aliskiren plasma concentration (Cmax) was 24% lower in men than women (P < .05). BMI was not significantly correlated with AUCτ (r = 0.005; P = .917); AUCτ was negatively correlated with body weight (r = −0.235; P < .0001) and LBW (r = −0.295; P < .0001). Results were similar for Cmax. Adjusting individual aliskiren AUCτ and Cmax values for overall mean body weight or LBW abolished gender differences. Based on r2 values, LBW variation accounted for 8.9% of aliskiren AUCτ variation. In patients with hypertension, gender and BMI did not significantly influence the effects of aliskiren on plasma renin activity or blood pressure. It was concluded that lower systemic exposure to aliskiren in men versus women relates to differences in body weight; neither gender nor body weight has clinically relevant effects on the pharmacokinetics or pharmacodynamics of aliskiren.
Bone marrow cavity segmentation using graph-cuts with wavelet-based texture feature

Emerging bioimaging technologies enable us to capture various dynamic cellular activities [Formula: see text]. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on. To reduce manual inputs to segment BMC, we classified the texture pattern using wavelet transformation and support vector machine. We also integrated the result of texture pattern classification into the graph-cuts-based image segmentation method because texture analysis does not consider spatial continuity. Our method is applicable to a particular frame in an image sequence in which the condition of fluorescent material is variable. In the experiment, we evaluated our method with nine types of mother wavelets and several sets of scale parameters. The proposed method with graph-cuts and texture pattern classification performs well without manual inputs by a user.
Video-Mediated Communication to Support Distant Family Connectedness

It can be difficult to maintain family connections with geographically distant members. However, advances in computer–human interaction (CHI) systems, including video-mediated communication (VMC) are emerging. While VMC does not completely substitute for physical face-to-face communication, it appears to provide a sense of virtual copresence through the addition of visual and contextual cues to verbal communication between family members. The purpose of this study was to explore current patterns of VMC use, experiences, and family functioning among self-identified VMC users separated geographically from their families. A total of 341 participants (ages 18 to above 70) completed an online survey and Family APGAR. Ninty-six percent of the participants reported that VMC was the most common communication method used and 60% used VMC at least once/week. The most common reason cited for using VMC over other methods of communication was the addition of visual cues. A significant difference between the Family APGAR scores and the number of positive comments about VMC experience was also found. This exploratory study provides insight into the acceptance of VMC and its usefulness in maintaining connections with distant family members.
Non-random associations of graphemes to colours in synaesthetic and non-synaesthetic populations

This study shows that biases exist in the associations of letters with colours across individuals both with and without grapheme-colour synaesthesia. A group of grapheme-colour synaesthetes were significantly more consistent over time in their choice of colours than a group of controls. Despite this difference, there were remarkable inter-subject agreements, both within and across participant groups (e.g., a tends to be red, b tends to be blue, c tends to be yellow). This suggests that grapheme-colour synaesthesia, whilst only exhibited by certain individuals, stems in part from mechanisms that are common to us all. In addition to shared processes, each population has its own distinct profile. Synaesthetes tend to associate higher frequency graphemes with higher frequency colour terms. For control participants, choices are influenced by order of elicitation, and by exemplar typicality from the semantic class of colours.
An Open Source Approach for a Military Situational Awareness System

This paper discusses the shortfalls of current military command & control systems with respect to providing situational awareness and to potentially improving and adapting such systems. It describes the architecture and required features of a military situational awareness system. It shows that by using common web map standards, it is possible to combine the strengths of an open source enterprise content management system with additional open source software tools creating a new kind of C2 system. It demonstrates as one possible use case how this military situational awareness system supports reach back networks for military decision support to operations.
The definition of Trichophyton rubrum syndrome

Summary. Although chronic widespread dermatophyte infection is reported widely in the literature, neither a uniform nomenclature, nor even a clear definition of this syndrome have been established so far. Thus, we suggest Trichophyton rubrum syndrome (TRS) for denomination and define the following obligatory clinical and mycological criteria for TRS. (A) Skin lesions at the following four sites: (1) feet, often involving soles; (2) hands, often involving palms; (3) nails; and (4) at least one lesion in another location than (1) (2) or (3), except for groins. (B) Positive microscopic analyses of potassium hydroxide preparations of skin scrapings in all four locations. (C) Identification of Trichophyton rubrum by cell culture at three of the four locations at least. For diagnosis of TRS the criteria (A) and (B) and (C) have to be fulfilled. This standardization is a prerequisite for further investigations of underlying mechanisms of this disease. The typical clinical pattern of TRS is illustrated by the presentation of two paradigmatic cases.
Timewarp rigid body simulation

The traditional high-level algorithms for rigid body simulation work well for moderate numbers of bodies but scale poorly to systems of hundreds or more moving, interacting bodies. The problem is unnecessary synchronization implicit in these methods. Jefferson's timewarp algorithm [22] is a technique for alleviating this problem in parallel discrete event simulation. Rigid body dynamics, though a continuous process, exhibits many aspects of a discrete one. With modification, the timewarp algorithm can be used in a uniprocessor rigid body simulator to give substantial performance improvements for simulations with large numbers of bodies. This paper describes the limitations of the traditional high-level simulation algorithms, introduces Jefferson's algorithm, and extends and optimizes it for the rigid body case. It addresses issues particular to rigid body simulation, such as collision detection and contact group management, and describes how to incorporate these into the timewarp framework. Quantitative experimental results indicate that the timewarp algorithm offers significant performance improvements over traditional high-level rigid body simulation algorithms, when applied to systems with hundreds of bodies. It also helps pave the way to parallel implementations, as the paper discusses.
A New General Framework for Shot Boundary Detection Based on SVM

Video shot boundary detection is an important step in many video applications. Since the rapid development of video editing technology, especially, the extensive use of subwindow in news video, the original method of video segmentation cannot efficiently detect the video shot boundary caused by special video technique. In this paper, previous temporal multi-resolution analysis (TMRA) work was extended by first using SVM (supported vector machines) classify the video frames within a sliding window into normal frames, gradual transition frames and CUT frames, then clustering the classified frames into different shot categories. The experimental result on ground truth, which has about 26 hours (13,344 shots) news video clips, shows that the new framework has relatively good accuracy for the detection of shot boundaries. It basically resolves the difficulties of shot boundaries detection caused by sub-window technique in video. The framework also greatly improves accuracy of gradual transitions of shot
Acoustic assessment of the seasonal occurrence and behaviour of Antarctic blue whales Balaenoptera musculus intermedia in the southeastern Atlantic and Southern Oceans

The International Whaling Commission (IWC) carried out blue whale research components within its annual austral summer Southern Ocean Whale and Ecosystem Research (SOWER) cruises between 1996 and 2010. Over 700 sonobuoys were deployed to record blue whale vocalizations during 11 Antarctic and three low latitude blue whale cruises off Australia, Madagascar and Chile. The recorded acoustic files from these deployments were collated and reviewed to develop a database of both the digital acoustic files and the associated deployment station metadata of 7,486 acoustic files from 484 stations. Acoustic files were analysed using the automated detection template and visual verification methods. We found a significant difference between the total number of acoustic recording hours (2,481) reported for these cruises (in the associated cruise reports) and the currently available number of acoustic recording hours (1,541). Antarctic blue whale vocalizations (9,315 and 24,902 Dand Z-calls) were detected on 4,183 of the 7,486 acoustic files. December had the lowest call rates whilst January and February yielded high call rates. Although the majority (63%) of the sonobuoys were deployed between 18h00 and 06h00 the following day, most calls (62%) were detected during observation periods between 06h00 and 18h00. The recently described southeastern Pacific 2 song of the Chilean pygmy blue whale was also found from Chilean blue whale cruise acoustic data. The difference between the available and reported data are of
Mining data streams with periodically changing distributions

Dynamic data streams are those whose underlying distribution changes over time. They occur in a number of application domains, and mining them is important for these applications. Coupled with the unboundedness and high arrival rates of data streams, the dynamism of the underlying distribution makes data mining challenging. In this paper, we focus on a large class of dynamic streams that exhibit periodicity in distribution changes. We propose a framework, called DMM, for mining this class of streams that includes a new change detection technique and a novel match-and-reuse approach. Once a distribution change is detected, we compare the new distribution with a set of historically observed distribution patterns and use the mining results from the past if a match is detected. Since, for two highly similar distributions, their mining results should also present high similarity, by matching and reusing existing mining results, the overall stream mining efficiency is improved while the accuracy is maintained. Our experimental results confirm this conjecture.
Increasing Crop Diversity Mitigates Weather Variations and Improves Yield Stability

Cropping sequence diversification provides a systems approach to reduce yield variations and improve resilience to multiple environmental stresses. Yield advantages of more diverse crop rotations and their synergistic effects with reduced tillage are well documented, but few studies have quantified the impact of these management practices on yields and their stability when soil moisture is limiting or in excess. Using yield and weather data obtained from a 31-year long term rotation and tillage trial in Ontario, we tested whether crop rotation diversity is associated with greater yield stability when abnormal weather conditions occur. We used parametric and non-parametric approaches to quantify the impact of rotation diversity (monocrop, 2-crops, 3-crops without or with one or two legume cover crops) and tillage (conventional or reduced tillage) on yield probabilities and the benefits of crop diversity under different soil moisture and temperature scenarios. Although the magnitude of rotation benefits varied with crops, weather patterns and tillage, yield stability significantly increased when corn and soybean were integrated into more diverse rotations. Introducing small grains into short corn-soybean rotation was enough to provide substantial benefits on long-term soybean yields and their stability while the effects on corn were mostly associated with the temporal niche provided by small grains for underseeded red clover or alfalfa. Crop diversification strategies increased the probability of harnessing favorable growing conditions while decreasing the risk of crop failure. In hot and dry years, diversification of corn-soybean rotations and reduced tillage increased yield by 7% and 22% for corn and soybean respectively. Given the additional advantages associated with cropping system diversification, such a strategy provides a more comprehensive approach to lowering yield variability and improving the resilience of cropping systems to multiple environmental stresses. This could help to sustain future yield levels in challenging production environments.
Estimating the permanent

We refer the reader to Jerrum's book [1] for the analysis of a Markov chain for generating a random matching of an arbitrary graph. Here we'll look at how to extend the argument to sample perfect matchings in dense graphs and arbitrary bipartite graphs. Both of these results are due to Jerrum and Sinclair [2]. Dense graphs We'll need some definitions and notations first: Definition 7.1 A graph G = (V, E) is said to be dense if for every v ∈ V , degree(v) > n/2, where n = |V |. Definition 7.2 Let G be a graph and let M G be the set of all perfect matchings of G. Similarly, for two distinct vertices u, v, let N G (u, v) be the set of all perfect matchings of the graph G \ {u, v}. We refer to matchings in N G (u, v) as near-perfect matchings, or matchings with holes u and v. Whenever G is clearly understood from the context, we shall use simply M and N (u, v). Jerrum's book presents the analysis of a Markov chain for sampling matchings (not necessarily perfect). The Markov chain for sampling perfect matchings in dense graphs is only a slight modification of the original chain. The state space Ω is the set of perfect and near-perfect matchings, i.e., Ω = M ∪ ∪ u,v∈V N (u, v). The near-perfect matchings are needed to navigate between perfect matchings.