Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic clustering of time series data

We propose a new method for clustering multivariate time-series data based on Dynamic Linear Models. Whereas usual time-series clustering methods obtain static membership parameters, our proposal allows each time-series to dynamically change their cluster memberships over time. In this context, a mixture model is assumed for the time series and a flexible Dirichlet evolution for mixture weights allows for smooth membership changes over time. Posterior estimates and predictions can be obtained through Gibbs sampling, but a more efficient method for obtaining point estimates is presented, based on Stochastic Expectation-Maximization and Gradient Descent. Finally, two applications illustrate the usefulness of our proposed model to model both univariate and multivariate time-series: World Bank indicators for the renewable energy consumption of EU nations and the famous Gapminder dataset containing life-expectancy and GDP per capita for various countries.
The Cytokine Profile and Prostate Specific Antigen Levels in Prostate Cancer Patients at Kenyatta National Hospital

Prostate cancer (PCa) is Kenya‘s most frequently diagnosed cancer of men with an incidence rate of 32 per 100,000 and mortality rate of 12 per 100,000. It is also the leading cancer in terms of incidence and mortality in men from Africa and the Caribbean and the numbers may double by 2030. Prostate Specific Antigen (PSA) is the main diagnostic biomarker used for screening patients currently. Biopsy histology is the only confirmatory test, but it is invasive and tedious to perform. There is an urgent need to develop other accurate biomarkers that can be used for screening and diagnosis. Cytokines have potential but have not been extensively studied as biomarkers. The objectives of this study were to evaluate the cytokine profile, determine the PSA levels in PCa patients and the risk factors that lead to the development of PCa. The study profiled six cytokines (interleukin-2 (IL-2), interleukin-4 (IL-4), interleukin-6 (IL-6), interleukin-10 (IL-10), interferon gamma (IFN-Gamma) and tumor necrosis factor alpha (TNF-Alpha) and the total PSA levels in the serum of 45 PCa patients, 7 benign prostate enlargement (BPE) patients and 7 healthy males as controls. Cytokines were measured using a highly sensitive cytometric bead array technique. PSA levels were determined using enzyme linked immunosorbent assay (ELISA) technique. A questionnaire was used to determine the demographic and risk factors that lead to the development of PCa. Statistical analysis was performed using statistical package for social sciences (SPSS) version 21. Analysis of variance (ANOVA) was used to compare the means of the cytokines and PSA levels in the different Gleason scores of the PCa patients. Pearson correlation was used to correlate the six individual cytokines and PSA levels. Statistical significance was set at the level of p<0.05 for both the ANOVA and the Pearson correlation test. The results showed that serum levels of all cytokines and PSA were significantly (p<0.05) higher in the PCa and the BPE patients. The PCa patients with a Gleason score of 8-10 had the highest levels of all the cytokines followed by those with a Gleason score of 5-7, then those with a Gleason score of 24. TNF-Alpha and IL-6 were the cytokines with the highest levels while IL-4 and IL-10 had the lowest levels. The cytokine levels among the BPE patients were less than those of the PCa patients. The PSA levels were also significantly higher (p=0.002) in the BPE and PCa patients and they were significantly correlated (p=0.01) with the six cytokines in the two study groups. Kenyan men who are above 50 years are at risk of suffering from PCa. These results indicated that cytokine profiles in PCa patients are distinct by the stage of the disease. TNF-Alpha, IL-6, IFN-Gamma, IL-2 and IL-4 may be potential early diagnostic biomarkers for prostate cancer. The current data forms a basis for further investigations.
The Role of Capital and Liquidity in Bank Lending: Are Banks Safer?

The aim of this paper is to examine whether and to what extent bank capital requirements and liquidity standards influence the level of bank stability. Our approach is that both capital and liquidity affect lending growth, which in turn affects bank stability. We construct a panel dataset on a sample of 2,054 commercial banks from 117 developed and developing countries during the 2000–16 period. By applying a two‐stage least squares (2SLS) empirical methodology, our findings show that capital and liquidity have a negative direct impact on the level of bank stability. However, this influence is counteracted by an indirect positive effect through the increased level of credit. Our results are not homogeneous across legal and institutional environments. In particular, we provide evidence on more relevant relationships in countries with higher level of protection of creditor rights and lower restrictions on non‐traditional banking activities. Our empirical findings are robust to different specifications of the empirical model and to potential endogeneity problems.
Experimental research on Bifidobacterium-cultivated supernatant fluid regulating blood fat index of aging rats underlined by D-gal

Objective To explore the anti-aging system of Bifidobacterium-cultivated supernatant fluid on the basis of observing its influence on the blood fat index and studying memorizing behavior of aging rats underlined by D-gal,so as to provide theoretical support for the further study of the anti-aging ingredients in the Bifidobacterium-cultivate supernatant fluid.Methods We established a subacute aging model group of rats by giving dorsum ocervical subcutanous injection of physiological saline and D-gal to them.Meanwhile,we offered intraperitoneal injection of Bifidobacterium-cultivated supernatant fluid to the rats in experment group.After the cultivating of the rats for 42 days,we weighed them and then killed them by cutting the neck.Then we detected the content of TC,TG and HDL-C in blood serum and testing the memorizing behavior of the rats by Step-down.Results Compared to the model rats,TC and TG level in blood serum of experiment rats getted lower significantly(P0.05),while HDL-C/TC getted higher.And the step-down-test showed an obvious advance of the experiment rats in memorizing behavior than that of the model rats.Conclusion The Bifidobacterium-cultivated supernatant fluid functions in decreasing the content of TG,TC in blood serum and delaying of D-gal aging organs and the decrease of memorizing ability.
Voice quality and coda /r/ in Glasgow English in the early 20th century

Abstract We present acoustic and auditory analyses of changes to coda /r/ and voice quality in Glasgow English in the early twentieth century. Our initial acoustic analysis suggests that /r/ was weakening across the board based on an increase in F3. However, an auditory analysis of the same data finds no significant changes. An acoustic analysis of the same speakers’ vowels reveals that the shift in F3 is not unique to /r/. It reflects a change in voice quality, which we link to velarization using Vocal Profile Analysis. We then reanalyze the acoustic /r/ data, controlling for voice quality, and find only moderate changes that are restricted to females. These findings provide new evidence for diachronic changes in voice quality, contribute to our understanding of the development of /r/ in Glasgow English, and highlight the importance of investigating speech sounds in their broader context using multiple methodologies.
Inhalt

1.1. Einkommensentwicklung. 30 1.2. Art der Beschäftigung. 31 1.3. Arbeitszeit . 32 1.4. Frauenbeschäftigung . 32 1.5. Entwicklung von Arbeitsunfällen. 32
Gene expression changes in oral tissues following black raspberry exposure: Interim Affymetrix array analysis of a Phase 1 clinical trial.

A129 INTRODUCTION: Chemoprevention is "the prevention, inhibition, or reversal of carcinogenesis by administration of one or more chemical entities, either as individual drugs or as naturally occurring constituents of the diet. " (GD Stoner, MA Morse, GJ Kelloff. EHP 105 Suppl 4:945,1997). The aim of this Phase 1 Clinical Trial was to evaluate molecular changes in oral cavity tissues after oral exposure to lyophilized black raspberries (LBR). Biopsy-confirmed oral squamous cell carcinoma (OSCC) patients were administered three LBR troches four times each day (4.3g cumulative dose) between pre-surgical enrollment and their normally scheduled surgery. Tissue biopsies were obtained from tumor (T1) and distant normal tissues (N1) at enrollment and during surgical resection (T2,N2), an exposure range of 7-34 days. An interim cohort of 10 patients was characterized by Affymetrix HG-U133 Plus 2.0 Arrays ("Affymetrix Arrays";1,300,000 unique oligonucleotide features, >47,000 transcripts, ~39,000 genes). METHODS: Four Affymetrix Arrays (N1,T1,N2,T2) were analyzed for each patient. Baseline pre-surgical tumor (T1) and distant normal (N1) tissues were collected at enrollment. After LBR troche administration, post-surgical tumor (T2) and distant normal (N2) tissues were obtained. Affymetrix Arrays were processed by The Ohio State University Comprehensive Cancer Center Microarray Shared Resource (OSUCCC MASR). Affymetrix CEL files were processed by DNA-Chip Analyzer (dChip) Software and analyses performed using custom statistical routines. Patient covariates included treatment duration, lesion site, tumor staging, and age. RESULTS: As expected, significant differences were readily detected between normal and tumor tissues, both before (T1/N1) and after (T2/N2) LBR exposure. Significant differences were also detected between normal tissues (N2/N1) and tumors (T2/T1) before and after LBR exposure. Importantly, significant differences were revealed when duration of LBR exposure was examined as a covariate among the 10 patient cohort. The data from this interim Phase 1 analysis provide substantial insight into possible biomarkers of oral cancer, and specifically of LBR-responsive genes in the normal and tumor tissues of OSCC patients. Furthermore, additional validation of these possible biomarkers may reveal detailed mechanistic, functional, prognostic, or diagnostic roles for these statistically significant modulated transcripts. SUPPORT: NIH/NCI R21DE016361, ACS RSGT-06-126-01-CNE
Impact of data center placement on the power consumption of flexible-grid optical networks

Abstract. The increasing trend of global IP traffic is mainly driven by high-definition video services and cloud computing and storage. Moreover, to maintain a high quality of service in content delivery networking, data are geographically replicated in data centers distributed within network topologies. Thus, data centers are an emerging scenario for research and development aimed at energy-efficient transmission and networking solutions. Previous research work has focused on intradata center energy efficiency while interdata center energy issues have not been extensively analyzed yet. We propose heuristics and meta-heuristics for optimal placement of data centers with minimum power consumption over a network topology relying on flex-grid spectral use. In order to minimize the network’s power consumption, we have performed a detailed comparison of heuristic and meta-heuristic designs for different network scenarios based on real topologies. Moreover, our results show that meta-heuristic provides an optimum data center placement in a reasonable amount of time for a small- to medium-sized network.
Design of fixed-time synchronization algorithm with applications

Fixed-time synchronization problem for a class of leader–follower multi-agent systems with second-order nonlinearity is studied in this article. A new fixed-time synchronization control algorithm is developed by effectively combining homogeneous system theory, Lyapunov stability theory, and fixed-time/finite-time control technology. The leader–follower multi-agent system is considered to achieve fixed-time synchronization control. Finally, numerical simulations including coordination control multiple pendulum robot systems and electric power networks are carried out to verify the control performance of the control strategy.
A high-performance millirobot for swarm-behaviour studies: Swarm-topology estimation

In this article, we present a novel high-performance millirobot ( m illi- rob ot- To ronto), designed to allow for the testing of complex swarm-behaviours, including human–swarm interaction. m illi- rob ot- To ronto, built only with off-the-shelf components, has locomotion, processing and sensing capabilities that significantly improve upon existing designs, while maintaining one of the smallest footprints among current millirobots. As complementary software to this hardware development, herein, we also present a new global swarm-topology estimation algorithm. The method is novel in that it uniquely fuses incomplete location data collected by the individual robots in a distributed manner to optimally estimate the topology of the overall swarm using a centralized computer. It is a generalized technique usable by any swarm comprising robots capable of collecting location estimates of neighbouring robots. Numerous experiments, evaluating the performance of m illi- rob ot- To ronto and the proposed optimal swarm-topology estimation algorithm, are also included.
Output error of converse piezoelectric fiber voltage sensor caused by optical fiber factors

In fiber voltage sensor, imperfect fiber splicing angle and length difference between the sensing fiber and the compensating fiber usually influence the system output performance. This article established the mathematical model of the system output error using the Jones matrix and analyzed the relationship between the system output error and the above two error factors, respectively. The results show that the angle error of 90° splice has a significant influence on the system output, and the tolerance of angle error varies with different test voltages. When the test voltage is higher than 6 kV, if the expected system error is less than 0.02%, the splicing angle error should be less than 0.15°. Additionally, the length difference also has a significant influence on the system output accuracy. The length difference between sensing fiber and compensating fiber should be less than 1 µm when the test voltage is 110 kV so that the system can meet the accuracy requirements of IEC 0.2s. This research provides a reference for the development of fiber voltage sensor based on the converse piezoelectric effect and also provides a basis for the design of intelligent power detection robot system.
Three-dimensional walking of a simulated muscle-driven quadruped robot with neuromorphic two-level central pattern generators

We aim to design a neuromorphic controller for the locomotion of a quadruped robot with muscle-driven leg mechanisms. To this end, we use a simulated cat model; each leg of the model is equipped with three joints driven by six muscle models incorporating two-joint muscles. For each leg, we use a two-level central pattern generator consisting of a rhythm generation part to produce basic rhythms and a pattern formation part to synergistically activate a different set of muscles in each of the four sequential phases (swing, touchdown, stance, and liftoff). Conventionally, it was difficult for a quadruped model with such realistic neural systems and muscle-driven leg mechanisms to walk even on flat terrain, but because of our improved neural and mechanical components, our quadruped model succeeds in reproducing motoneuron activations and leg trajectories similar to those in cats and achieves stable three-dimensional locomotion at a variety of speeds. Moreover, the quadruped is capable of walking upslope and over irregular terrains and adapting to perturbations, even without adjusting the parameters.
Untangling the Ties Between Social Cognition and Body Motion: Gender Impact

We proved the viability of the general hypothesis that biological motion (BM) processing serves as a hallmark of social cognition. We assumed that BM processing and inferring emotions through BM (body language reading) are firmly linked and examined whether this tie is gender-specific. Healthy females and males completed two tasks with the same set of point-light BM displays portraying angry and neutral locomotion of female and male actors. For one task, perceivers had to indicate actor gender, while for the other, they had to infer the emotional content of locomotion. Thus, with identical visual input, we directed task demands either to BM processing or inferring of emotion. This design allows straight comparison between sensitivity to BM and recognition of emotions conveyed by the same BM. In addition, perceivers were administered a set of photographs from the Reading the Mind in the Eyes Test (RMET), with which they identified either emotional state or actor gender. Although there were no gender differences in performance on BM tasks, a tight link occurred between recognition accuracy of emotions and gender through BM in males. In females only, body language reading (both accuracy and response time) was associated with performance on the RMET. The outcome underscores gender-specific modes in visual social cognition and triggers investigation of body language reading in a wide range of neuropsychiatric disorders.
Multi-Level Clustering of Dynamic Directional Brain Network Patterns and Their Behavioral Relevance

Dynamic functional connectivity (DFC) obtained from resting state functional magnetic resonance imaging (fMRI) data has been shown to provide novel insights into brain function which may be obscured by static functional connectivity (SFC). Further, DFC, and by implication how different brain regions may engage or disengage with each other over time, has been shown to be behaviorally relevant and more predictive than SFC of behavioral performance and/or diagnostic status. DFC is not a directional entity and may capture neural synchronization. However, directional interactions between different brain regions is another putative mechanism by which neural populations communicate. Accordingly, static effective connectivity (SEC) has been explored as a means of characterizing such directional interactions. But investigation of its dynamic counterpart, i.e., dynamic effective connectivity (DEC), is still in its infancy. Of particular note are methodological insufficiencies in identifying DEC configurations that are reproducible across time and subjects as well as a lack of understanding of the behavioral relevance of DEC obtained from resting state fMRI. In order to address these issues, we employed a dynamic multivariate autoregressive (MVAR) model to estimate DEC. The method was first validated using simulations and then applied to resting state fMRI data obtained in-house (N = 21), wherein we performed dynamic clustering of DEC matrices across multiple levels [using adaptive evolutionary clustering (AEC)] – spatial location, time, and subjects. We observed a small number of directional brain network configurations alternating between each other over time in a quasi-stable manner akin to brain microstates. The dominant and consistent DEC network patterns involved several regions including inferior and mid temporal cortex, motor and parietal cortex, occipital cortex, as well as part of frontal cortex. The functional relevance of these DEC states were determined using meta-analyses and pertained mainly to memory and emotion, but also involved execution and language. Finally, a larger cohort of resting-state fMRI and behavioral data from the Human Connectome Project (HCP) (N = 232, Q1–Q3 release) was used to demonstrate that metrics derived from DEC can explain larger variance in 70 behaviors across different domains (alertness, cognition, emotion, and personality traits) compared to SEC in healthy individuals.
Ketamine Alleviates Postoperative Depression-Like Symptoms in Susceptible Mice: The Role of BDNF-TrkB Signaling

Patients are more likely to suffer from central nervous system (CNS) complications after anesthesia and surgery. However, postoperative depression (POD) has not yet received sufficient attentions, and its pathogenesis and therapeutic strategies remain poorly understood. We here aimed to investigate whether brain derived neurotrophic factor (BDNF)-tropomyosin-related kinase B (TrkB) signaling plays an important role in POD. BDNF-TrkB signaling was altered in brain and peripheral tissues, including medial prefrontal cortex (mPFC), hippocampus, liver, and muscle, among control, POD susceptible, and resilient groups. Additionally, we demonstrated that 7,8-dihydroxyflavone (7,8-DHF), a TrkB agonist, could exert its pharmacologic property to alleviate POD-like symptoms. More importantly, ketamine, a non-competitive N-methyl-D-aspartic acid (NMDA) receptor antagonist, also has significant antidepressant effects in POD model, associating with the improving effects on levels of BDNF-TrkB signaling in brain and peripheral tissues. Interestingly, the beneficial effects of ketamine on POD-like symptoms are fully attenuated by a TrkB antagonist. These findings suggest that abnormal expressions of BDNF-TrkB signaling in brain and peripheral tissues are implicated in the pathogenesis of POD, and that therapeutic agents targeting BDNF-TrkB, particularly ketamine, could favor the beneficial effects for POD.
The Genetics and Epigenetics of 22q11.2 Deletion Syndrome

Chromosome 22q11.2 deletion syndrome (22q11.2del) is a complex, multi-organ disorder noted for its varying severity and penetrance among those affected. The clinical problems comprise congenital malformations; cardiac problems including outflow tract defects, hypoplasia of the thymus, hypoparathyroidism, and/or dysmorphic facial features. Additional clinical issues that can appear over time are autoimmunity, renal insufficiency, developmental delay, malignancy and neurological manifestations such as schizophrenia. The majority of individuals with 22q11.2del have a 3 Mb deletion of DNA on chromosome 22, leading to a haploinsufficiency of ~106 genes, which comprise coding RNAs, noncoding RNAs, and pseudogenes. The consequent haploinsufficiency of many of the coding genes are well described, including the key roles of T-box Transcription Factor 1 (TBX1) and DiGeorge Critical Region 8 (DGCR8) in the clinical phenotypes. However, the haploinsufficiency of these genes alone cannot account for the tremendous variation in the severity and penetrance of the clinical complications among those affected. Recent RNA and DNA sequencing approaches are uncovering novel genetic and epigenetic differences among 22q11.2del patients that can influence disease severity. In this review, the role of coding and non-coding genes, including microRNAs (miRNA) and long noncoding RNAs (lncRNAs), will be discussed in relation to their bearing on 22q11.2del with an emphasis on TBX1.