Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of mammographic masses using generalized dynamic fuzzy neural networks

In this paper, computer-aided classification of mammographic masses using generalized dynamic fuzzy neural networks (GDFNN) is presented. The texture parameters, derived from first-order gradient distribution and gray-level co-occurrence matrices (GCMs), were computed from the regions of interest (ROIs). A total of 77 images containing 38 benign cases and 39 malignant cases from the Digital Database for Screening Mammography (DDSM) were analyzed. A fast approach of automatically generating fuzzy rules from training samples was implemented to classify tumors. The novelty of this work is that it alleviates the problem of the conventional computer-aided diagnosis (CAD) system that requires a designer to examine all the input-output relationships of a training database in order to obtain the most appropriate structure for the classifier. In this approach, not only the connection weights can be adjusted, but also the structure can be self-adaptive during the learning process. With the classifier automatically generated by the GDFNN learning algorithm, the area under the receiver-operating characteristic (ROC) curve, Az, reached 0.9289, which corresponded to a true-positive fraction of 94.9% at a false positive fraction of 73.7%. The corresponding accuracy was 84.4%, the positive predictive value was 78.7\% and the negative predictive value was 93.3%.
Satisfying link perturbation and k-out anonymous in social network privacy protection

With the development of information technology, social networking has gradually become the main way of communication between people, and sensitive information exposed to the public network led to a variety of privacy issues. In social networks, important nodes have more influence on the virus spread, information dissemination compare to other nodes, therefore, they need more perturbation. In this paper, under the condition of satisfying privacy protection, given the threshold probability of replacing the correct node with a false node; further, we devise algorithms to achieve the graph also satisfied k-out of anonymity, the experimental results demonstrate that our algorithm can preserve the privacy and utility of social networks effectively on real word datasets.
An efficient feature selection method for network video traffic classification

A feature selection method RFPSO based on RelieiF and Particle Swarm Optimization (PSO) is proposed to mitigate the problem that the feature dimension of network traffic classification is too high. In this method, the ReliefF algorithm is used to filter out some irrelevant features and achieve the goal of rapid dimension reduction. Then, PSO is used as the search algorithm, and some better features are used as the partial initial population of particle swarm. The inconsistency rate is used as the evaluation function to select the optimal subset in the remaining feature subsets. The experimental results show that the classification accuracy of the RFPSO algorithm is higher than that of existing algorithms, and the computational complexity of the algorithm is lower than that of other two feature selection algorithms based on classification learning algorithm.
Cross-Lingual Generation and Evaluation of a Wide-Coverage Lexical Semantic Resource

Neural word embedding models trained on sizable corpora have proved to be a very efﬁcient means of representing meaning. However, the abstract vectors representing words and phrases in these models are not interpretable for humans by themselves. In this paper we present the Thing Recognizer, a method that assigns explicit symbolic semantic features from a ﬁnite list of terms to words present in an embedding model, making the model interpretable for humans and covering the semantic space by a controlled vocabulary of semantic features. We do this in a cross-lingual manner, applying semantic tags taken form lexical resources in one language (English) to the embedding space of another (Hungarian).
Assessing Emotional Reactivity: Psychometric Properties of the Perth Emotional Reactivity Scale and the Development of a Short Form

ABSTRACT The Perth Emotional Reactivity Scale (PERS) is a 30-item self-report measure of trait levels of emotional reactivity. In this article, we examine the psychometric properties of the PERS subscale and composite scores in an adult community sample (N = 428), and develop an 18-item short form of the measure (PERS–S). The PERS and PERS–S are designed to assess the typical ease of activation, intensity, and duration of one's emotional responses, and do so for positive and negative emotions separately. Our confirmatory factor analyses supported that the PERS and PERS–S both had the same theoretically congruent factor structure, and that all subscale and composite scores displayed high internal consistency reliability. Correlations with scores from established measures of psychopathology and emotion regulation also supported the validity of PERS and PERS–S scores. Our data therefore suggest that the PERS–S subscale and composite scores retain the psychometric strengths of their longer PERS counterparts. We conclude that both forms of the measure have good utility. Clinical and research applications are discussed.
[Curative observation on allergic rhinitis treated by intranasal corticosteroids combined with nasal irrigation].

Objective: To observe the effect of normal saline with intranasal corticosteroids in the treatment of allergic rhinitis(AR). Method:Two hundred and seventy-three outpatients with severe persistent allergic rhinitis were participated in this study.All patients were randomly divided into three groups, and were treated for 12 weeks using three different therapies, respectively. Symptom assessment of each patient were performed before treatment, 4 weeks, 8 weeks, and 12 weeks after treatment, respectively. The content of symptom assessment includes visual analogue scale, rhinoconjunctivitis quality of life questionnaire, symptoms scores and endoscopy examination scores.Result:Efficacy of intranasal corticosteroids combined with normal saline nasal irrigation in the treatment of AR is better than that of intranasal corticosteroids only, and is almost equivalent to intranasal corticosteroids combined with antihistamines.Conclusion:Long-term application of intranasal corticosteroids in combination with normal saline irrigation can effectively control and mitigate symptoms of severe persistent AR patients, and improve the patient's quality of life. This combination therapy is a better choice for the patient who is not satisfied with the single use of intranasal corticosteroids.
Neutrophil-lymphocyte ratio and creatinine reduction ratio predict good early graft function among adult cadaveric donor renal transplant recipients. Single institution series.

Background Delayed graft function (DGF) is a common complication following kidney transplantation and is associated with ischemia-reperfusion injury (IRI). Lymphocytes contribute to the pathogenesis of IRI and ischemia-reperfusion related delayed graft function Materials and Methods 135 Caucasian patients received a kidney graft from deceased heart-beating organ donors. We divided patients into 2 groups- patients with the eGFR>=30 on the 21st day post-transplantation (n=36) and patients with the eGFR<30 on the 21st day post-transplantation (n=99) to assess kidney graft function. We measured the serum creatinine levels on 1st and 2nd post-transplant day and preoperative levels of monocytes, lymphocytes, platelets and neutrophils and their ratios. Results We have found statistically significant differences between the eGFR<30 and the eGFR>=30 groups in the average lnLymphocytes (0,36 +/-0,6 vs -0,016 +/-0,74 respectively p=0,004) lnNLR ( 1,27 +/-0,92 vs. 1,73+/-1,08 p=0,016) lnLMR (1,01 +/-0,57 vs. 0,73 +/-0,64 p=0,02), lnPLR (4,97 +/-0,55 vs. 5,26 +/- 0,67 p=0,023) and CCR2% (-20,20 +/- 21,55 vs. -4,29 +/- 29,62 p=0,004 . On univariate analysis, factors of lnLymphocytes >=0,22 (OR=0,331 95%CI 0,151-0,728 p=0,006), lnLMR>=1,4 (OR=0,255 95%CI 0,072-0,903 p=0,034) were associated with worse graft function while lnNLR>=1,05 (OR=2,653 95%CI 1,158-6,078 p=0,021), lnPLR>=5,15 (OR=2,536 95%CI 1,155-5,566 p=0,02) and CRR2 (OR=3,286 95% CI 1,359-7,944 p=0,008) indicated better graft function Conclusion Higher absolute lymphocyte count (lnLymphocytes) and lnLMR as well as lower lnNLR and lnPLR were associated with lower eGFR on the 21st day after kidney transplantation. On multivariate analysis CRR2 in combination with either lnLymphocytes, lnNLR or lnPLR improved the accuracy of detecting patients with poor graft function.
Pelagic larval duration, growth rate, and population genetic structure of the tidepool snake moray Uropterygius micropterus around the southern Ryukyu Islands, Taiwan, and the central Philippines

The relationships between pelagic larval duration (PLD) and geographic distribution patterns or population genetic structures of fishes remain obscure and highly variable among species. To further understand the early life history of the tidepool snake moray Uropterygius micropterus and the potential relationship between PLD and population genetic structure of this species, otolith microstructure and population genetics based on concatenated mtDNA sequence (cytochrome b and cytochrome oxidase subunit I, 1,336 bp) were analyzed for 195 specimens collected from eight locations around the southern Ryukyu Islands, Taiwan, and the central Philippines. Eels with longer PLD and lower otolith growth rates were observed at relatively higher latitudes with lower water temperatures (54.6 ± 7.7 days and 1.28 ± 0.16 µm day−1 on Ishigaki Island, Japan, vs. 43.9 ± 4.9 days and 1.60 ± 0.19 µm day−1 on Badian, the Philippines), suggesting that leptocephali grew faster and had shortened pelagic periods in warmer waters. Meanwhile, the eels along the southwest coast of Taiwan had relatively longer PLD (57.9 ± 10.5 days), which might be associated with the more complex ocean current systems compared to their counterparts collected along the east coast of Taiwan (52.6 ± 8.0 days). However, the southwestern and eastern Taiwan groups had similar otolith growth rates (1.33 ± 0.19 µm day−1 vs. 1.36 ± 0.16 µm day−1). Despite the intergroup variation in PLD, genetic analysis revealed fluent gene flow among the tidepool snake morays in the study regions, implying that intraspecies PLD variation had a weak effect on genetic structure. The leptocephalus stage might have ensured the widespread gene flow among the study areas and leptocephalus growth was likely influenced by regional water temperature.
Long-Chain n-3 Fatty Acids Attenuate Oncogenic KRas-Driven Proliferation by Altering Plasma Membrane Nanoscale Proteolipid Composition.

Ras signaling originates from transient nanoscale compartmentalized regions of the plasma membrane composed of specific proteins and lipids. The highly specific lipid composition of these nanodomains, termed nanoclusters, facilitates effector recruitment and therefore influences signal transduction. This suggests that Ras nanocluster proteolipid composition could represent a novel target for future chemoprevention interventions. There is evidence that consumption of fish oil containing long-chain n-3 polyunsaturated fatty acids (n-3 PUFA) such as eicosapentaenoic acid (EPA, 20:5Δ5,8,11,14,17) and docosahexaenoic acid (DHA, 22:6Δ4,7,10,13,16,19) may reduce colon cancer risk in humans, yet the mechanism underlying this effect is unknown. Here, we demonstrate that dietary n-3 PUFA reduce the lateral segregation of cholesterol-dependent and -independent nanoclusters, suppressing phosphatidic acid-dependent oncogenic KRas effector interactions, via their physical incorporation into plasma membrane phospholipids. This results in attenuation of oncogenic Ras-driven colonic hyperproliferation in both Drosophila and murine models. These findings demonstrate the unique properties of dietary n-3 PUFA in the shaping of Ras nanoscale proteolipid complexes and support the emerging role of plasma membrane-targeted therapies.Significance: The influence of dietary long chain n-3 polyunsaturated fatty acids on plasma membrane protein nanoscale organization and KRas signaling supports development of plasma membrane-targeted therapies in colon cancer.Graphical Abstract: http://cancerres.aacrjournals. org/content/canres/78/14/3899/F1.large. jpg Cancer Res; 78(14); 3899-912. ©2018 AACR.
An Analysis of the Financial Impact of Changing Athletic Conference Affiliation within the NCAA

The purpose of this causal comparative study was to provide Division I athletic programs with athletic and institutional fundraising insight when considering a change in athletic conference affiliation. The study provided descriptive data regarding athletic conference affiliation pre and post-conference change. The research evaluated if there was a significant increase in athletic and educational fundraising when changing athletic conferences. The quantitative study compared educational and athletic foundations’ IRS 990 forms for 15 NCAA Division 1 institutions that changed athletic conferences between 2012 and 2013. Data was analyzed using an ANOVA and t-tests from the institutions’ academic and athletic foundations. The results of pre-conference affiliation and post-conference change were evaluated and they indicated that there is not a significant increase in fundraising for either the athletic or educational fundraising foundations, thus failing to reject the null hypotheses. Suggestions for further research are noted.
Connection formulas for thermal density functional theory

We show that the adiabatic connection formula of ground-state density functional theory relates the correlation energy to a coupling-constant integral over a purely potential contribution, and is widely used to understand and improve approximations. The corresponding formula for thermal density functional theory is cast as an integral over temperatures instead, ranging upward from the system's physical temperature. We also show how to relate different correlation components to each other, either in terms of temperature or coupling-constant integrations. Lastly, we illustrate our results on the uniform electron gas.
High and low-level hierarchical classification as an efficient analysis of remotely sensed hyperpectral data

In this paper we address the problem of the remote sensing data analysis on high-dimensional space like hyperspectral data. Its complexity is caused by many factors, such as the large spectral or spatial variability and the curse of dimensionality. Much work has been carried out in the literature to overcome this particular ill-posed issue. Applied to hyperspectral data in hyper-dimensional features spaces, the first particularity of our method is the special structure of its cluster tree. Their leaves are associated with sources represented according to mutually independent axes to represent specifically some land covers. The second particularity is that at each level of the cluster tree we combine a divisive clustering approach applied at a high-level and an agglomerative clustering operating at a low-level. We propose to compare the performances of our approach with those of hierarchical method based on Ward approach.
Online Learning Algorithms Can Converge Comparably Fast as Batch Learning

Online learning algorithms in a reproducing kernel Hilbert space associated with convex loss functions are studied. We show that in terms of the expected excess generalization error, they can converge comparably fast as corresponding kernel-based batch learning algorithms. Under mild conditions on loss functions and approximation errors, fast learning rates and finite sample upper bounds are established using polynomially decreasing step-size sequences. For some commonly used loss functions for classification, such as the logistic and the <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-norm hinge loss functions with <inline-formula> <tex-math notation="LaTeX">$p\in [{1,2}]$ </tex-math></inline-formula>, the learning rates are the same as those for Tikhonov regularization and can be of order <inline-formula> <tex-math notation="LaTeX">$O(T^{- {(1 / 2)}} \log T)$ </tex-math></inline-formula>, which are nearly optimal up to a logarithmic factor. Our novelty lies in a sharp estimate for the expected values of norms of the learning sequence (or an inductive argument to uniformly bound the expected risks of the learning sequence in expectation) and a refined error decomposition for online learning algorithms.
Variability of transferrin in field mouse from urban and suburban populations

On the basis of 3-year studies transferrin polymorphism in Apodemus agrarius in chosen differently isolated urban (Warsaw), suburban and field (Turew) populations it was stated as follows: (a) a lack of differences in variability of transferrin related to sex, sexual activity and season (summer-early autumn), (b) differences in frequencies of transferrin alleles between populations during two years of studies when the gradient of genetic variability in populations was opposite to gradient of isolation and urbanization of habitat studied, (c) significantly different frequencies of transferrin alleles from year to year in isolated population from the city centre.
A novel mutual information based ant colony classifier

By constructing a list of IF-THEN rules, the traditional ant colony optimization (ACO) has been successfully applied on data classification with not only a promising accuracy but also a user comprehensibility. However, as the collected data to be classified usually contain large volumes and redundant features, it is challenging to further improve the classification accuracy and meanwhile reduce the computational time for ACO. This paper proposes a novel hybrid mutual information based ant colony algorithm (mr2 AM+) for classification. First, a maximum relevance minimum redundancy feature selection method is used to select the most informative and discriminative attributes in a dataset. Then, we use the enhanced ACO classifier (i.e., AM+) to perform the classification. Experimental results show that the proposed mr2AM+ outperforms other seven state-of-art related classification algorithms in terms of accuracy and the size of model.
Circulating human papillomavirus DNA as a surveillance tool in head and neck squamous cell carcinoma: A systematic review and meta‐analysis

The incidence of human papillomavirus‐induced (HPV+) head and neck squamous cell carcinoma (HNSCC), that is, especially oropharyngeal cancers (OPSCC), is increasing, and a significant proportion of patients encounter disease progression. A simple and sensitive test to identify patients with progression is an unmet need.
Bitterness in Almonds1[C][OA]

Bitterness in almond (Prunus dulcis) is determined by the content of the cyanogenic diglucoside amygdalin. The ability to synthesize and degrade prunasin and amygdalin in the almond kernel was studied throughout the growth season using four different genotypes for bitterness. Liquid chromatography-mass spectrometry analyses showed a specific developmentally dependent accumulation of prunasin in the tegument of the bitter genotype. The prunasin level decreased concomitant with the initiation of amygdalin accumulation in the cotyledons of the bitter genotype. By administration of radiolabeled phenylalanine, the tegument was identified as a specific site of synthesis of prunasin in all four genotypes. A major difference between sweet and bitter genotypes was observed upon staining of thin sections of teguments and cotyledons for β-glucosidase activity using Fast Blue BB salt. In the sweet genotype, the inner epidermis in the tegument facing the nucellus was rich in cytoplasmic and vacuolar localized β-glucosidase activity, whereas in the bitter cultivar, the β-glucosidase activity in this cell layer was low. These combined data show that in the bitter genotype, prunasin synthesized in the tegument is transported into the cotyledon via the transfer cells and converted into amygdalin in the developing almond seed, whereas in the sweet genotype, amygdalin formation is prevented because the prunasin is degraded upon passage of the β-glucosidase-rich cell layer in the inner epidermis of the tegument. The prunasin turnover may offer a buffer supply of ammonia, aspartic acid, and asparagine enabling the plants to balance the supply of nitrogen to the developing cotyledons.
JOINT MOMENTS OF UNILATERAL TRANSFEMORAL AMPUTEES USING RUNNING-SPECIFIC PROSTHESIS DURING SPRINTING

The aim of this study was to investigate the bilateral difference of the joint moments between an intact leg (INT) and a prosthetic leg (PST) in unilateral transfemoral amputees (TFAs) wearing running-specific prosthesis during sprinting. Eight sprinters with unilateral TFAs performed maximal sprinting on a 40-m runway with 7 force platforms located in between. Hip and knee joint extension and flexion moments during stance phase in INT were significantly greater than those of PST. However, ankle plantarflexion moment in PST was significantly greater than that of INT. Since kinetic asymmetry between legs is thought to be related with running-related injury, sprinter with unilateral TFAs may have a higher risk of musculoskeletal injury at hip and knee joints.
Covert Wireless Communications with Active Eavesdropper on AWGN Channels

Covert wireless communication can prevent an adversary from knowing the existence of user's transmission, thus provide stronger security protection. In AWGN channels, a square root law was obtained and the result shows that Alice can reliably and covertly transmit $\mathcal{O}(\sqrt{n})$ bits to Bob in n channel uses in the presence of a passive eavesdropper (Willie). However, existing work presupposes that Willie is static and only samples the channels at a fixed place. If Willie can dynamically adjust the testing distance between him and Alice according to his sampling values, his detection probability of error can be reduced significantly via a trend test. We found that, if Alice has no prior knowledge about Willie, she cannot hide her transmission behavior in the presence of an active Willie, and the square root law does not hold in this situation. We then proposed a novel countermeasure to deal with the active Willie. Through randomized transmission scheduling, Willie cannot detect Alice's transmission attempts if Alice can set her transmission probability below a threshold. Additionally, we systematically evaluated the security properties of covert communications in a dense wireless network, and proposed a density-based routing scheme to deal with multi-hop covert communication in a wireless network. As the network grows denser, Willie's uncertainty increases, and finally resulting in a "shadow" network to Willie.
A philosophical foundation for diagnostic blocks, with criteria for their validation.

BACKGROUND In the absence of a suitable reference standard, diagnostic local anesthetic blocks cannot be validated in the manner conventionally used for diagnostic tests. Consequently, diagnostic blocks are vulnerable to criticism for lacking validity, or being "not proven. " STUDY DESIGN Philosophical essay. METHODS Inspired by the "viewpoints" proposed by Bradford Hill for testing cause and effect in epidemiology, a set of axiomatic criteria was developed with which the validity of diagnostic blocks could be assessed. RESULTS Eight criteria were established: plausibility, experiment, target-specificity, effect, duration, consistency, control, and replication. Applying weighted scores to these criteria produces a metric by which the validity of a particular diagnostic block can be quantified. CONCLUSION The eight criteria provide an axiomatic, philosophical basis for diagnostic blocks in general, and serve to show what empirical evidence needs to be gathered in order to validate a particular block. The associated metric allows the scientific evidence for different blocks to be quantified and compared.