Miracle-dz/UniFAR-FTUs huggingface dataset:
Bio-harmonized control experiments of a carangiform robotic fish underwater vehicle

This paper presents experimental implementation and comparison of three different control schemes of a bio-inspired robotic fish underwater vehicle. The dynamics model is obtained by unifying conventional rigid body dynamics and bio-fluid dynamics of a carangiform fish swimming given by Lighthill’s(LH) slender body theory. It proposes an inclusive mathematical design for better control and energy efficient path travel for the robotic fish. The system is modeled as an two-link robot manipulator (caudal tail) with a mobile base (head). This forward thrust drives the robotic fish head represented by a combined non-linear equation of motion in earth fixed frame. We develop and compare the dynamic motion closed loop control strategy of the bio-harmonized robotic fish based on three different non-linear control schemes using CTM (Computed Torque Method), FF (Feed-Forward) controllers both with dynamic PD compensation and finally a proposed combination of CTM with FF. An inverse dynamic control method based on non-linear state function model including hydrodynamics is proposed to improve tracking performance. CTM control generates a feedback loop for linearization and decoupling robot dynamic model with a shorter response time, while a dynamic PD compensation in the FF path is employed by FF scheme through the desired trajectories. FF model-based strategy results in an improved tracking and shorter route to travel between two points. Overall results indicate that performances of the proposed control schemes based on the inverse dynamic model are comparable and useful for robotic fish motion tracking in fluid environment. Graphical Abstract
A Combined Laser Microdissection and Mass Spectrometry Approach Reveals New Disease Relevant Proteins Accumulating in Aggregates of Filaminopathy Patients*

Filaminopathy is a subtype of myofibrillar myopathy caused by mutations in FLNC, the gene encoding filamin C, and histologically characterized by pathologic accumulation of several proteins within skeletal muscle fibers. With the aim to get new insights in aggregate composition, we collected aggregates and control tissue from skeletal muscle biopsies of six myofibrillar myopathy patients harboring three different FLNC mutations by laser microdissection and analyzed the samples by a label-free mass spectrometry approach. A total of 390 proteins were identified, and 31 of those showed significantly higher spectral indices in aggregates compared with patient controls with a ratio >1.8. These proteins included filamin C, other known myofibrillar myopathy associated proteins, and a striking number of filamin C binding partners. Across the patients the patterns were extremely homogeneous. Xin actin-binding repeat containing protein 2, heat shock protein 27, nebulin-related-anchoring protein, and Rab35 could be verified as new filaminopathy biomarker candidates. In addition, further experiments identified heat shock protein 27 and Xin actin-binding repeat containing protein 2 as novel filamin C interaction partners and we could show that Xin actin-binding repeat containing protein 2 and the known interaction partner Xin actin-binding repeat containing protein 1 simultaneously associate with filamin C. Ten proteins showed significant lower spectral indices in aggregate samples compared with patient controls (ratio <0.56) including M-band proteins myomesin-1 and myomesin-2. Proteomic findings were consistent with previous and novel immunolocalization data. Our findings suggest that aggregates in filaminopathy have a largely organized structure of proteins also interacting under physiological conditions. Different filamin C mutations seem to lead to almost identical aggregate compositions. The finding that filamin C was detected as highly abundant protein in aggregates in filaminopathy indicates that our proteomic approach may be suitable to identify new candidate genes among the many MFM patients with so far unknown mutation.
Recovering Individual's Commute Routes Based on Mobile Phone Data

Mining individuals’ commute routes has been a hot spot in recent researches. Besides the significant impact on human mobility analysis, it is quite important in lots of fields, such as traffic flow analysis, urban planning, and path recommendation. Common ways to obtain these pieces of information are mostly based on the questionnaires, which have many disadvantages such as high manpower cost, low accuracy, and low sampling rate. To overcome these problems, we propose a commute routes recovering model to recover individuals’ commute routes based on passively generated mobile phone data. The challenges of the model lie in the low sampling rate of signal records and low precision of location information from mobile phone data. To address these challenges, our model applies two main modules. The first is data preprocessing module, which extracts commute trajectories from raw dataset and formats the road network into a better modality. The second module combines two kinds of information together and generates the commute route with the highest possibility. To evaluate the effectiveness of our method, we evaluate the results in two ways, which are path score evaluation and evaluation based on visualization. Experimental results have shown better performance of our method than the compared method.
Differential rearing conditions alter operant responding for ethanol in outbred rats.

BACKGROUND Differential rearing environments affect a number of behaviors displayed by rats in adulthood. For example, rats reared in an impoverished condition (IC; reared alone in hanging metal cages), social condition (SC; reared in standard shoebox cages, 2 per cage), or enriched condition (EC; reared in a large metal cage with bedding, 14 novel objects, and 10 cohorts) display clear differences in the amount of drug they consume and/or self-administer through operant responding. Animals reared in an EC consume greater amounts of ethanol compared with rats reared in an IC when provided free access, but it is not known how differential rearing conditions affect operant responding for ethanol. METHODS Twenty-eight male Long-Evans rats were reared in 1 of 3 environments (IC, SC, or EC) during postnatal days 21 to 111. At the conclusion of the rearing period, all rats underwent sucrose/ethanol fading and then were tested for lever press responding for 10% ethanol as well as ethanol preference. RESULTS Rats reared in an IC responded for 10% ethanol at significantly higher rates than SC and EC rats. A greater percentage of IC rats were able to switch lever responding when the ethanol availability was changed to a second lever. Lastly, the IC group was the only one to display a clear preference for 10% ethanol when both this fluid and water were available. CONCLUSION Rats reared in an IC show greater proclivity to respond operantly for 10% ethanol compared with rats raised in either SC or EC (which did not differ from each other). These findings agree with a number of studies that have shown isolate reared animals to consume greater amounts of ethanol compared with their socially reared counterparts yet contrast some studies showing EC animals consume greater amounts of ethanol than IC rats. The current findings illustrate that rearing environment also plays an important role in an animal's proclivity to respond for ethanol.
The aminosteroid phospholipase C antagonist U-73122 potently inhibits human 5-lipoxygenase in vivo and in vitro

U-73122 (1-[6-[[17-beta-3-methoxyestra-1,3,5(10)-trien-17-yl]amino]hexyl]-1H-pyrrole-2,5-dione) is a widely employed antagonist of phosphoinositide-specific phospholipase (PL)C, and is frequently used to define a role of PLC in receptor-mediated elevation of [Ca 2+ ] i . In human polymorphonuclear leukocytes (PMNL), U-73122 inhibited increases in [Ca 2+ ] i induced by G protein-coupled receptor (GPCR) agonists (N-formyl-methionyl-leucyl-phenylalanine or platelet-activating factor; IC 50 (cid:124) 2 to 4 µM), but failed to suppress responses induced by ionomycin or thapsigargin. 5-Lipoxygenase (5-LO) is a Ca 2+ -regulated enzyme which can be activated in leukocytes by stimuli that elevate [Ca 2+ ] i . Attempts to investigate the involvement of PLC in cellular 5-LO activation revealed that U-73122 suppresses 5-LO product synthesis regardless of the stimulus and independently of Ca 2+ . Thus, U-73122 blocked 5-LO product synthesis induced by cell stress, involving 5-LO phosphorylation pathways in the absence of Ca 2+ with an IC 50 (cid:124) 2 µM. Direct inhibition of 5-LO by U-73122 was evident in PMNL homogenates (IC 50 (cid:124) 2.4 µM), and isolated human recombinant 5-LO enzyme was potently inhibited by U-73122 (IC 50 (cid:124) 30 nM). Thiols (glutathione) strongly blunted the effect of U-73122 on isolated 5-LO. On the other hand, depletion of cellular thiols by N-ethylmaleimide strongly increased the efficacy of U-73122 to inhibit 5-LO in intact cells or corresponding
Using extension theory to design a fast data processing model

With the advent of the Internet and WWW in the late 1990s, intelligent systems have found another application area. In the Internet-based system, how to search for the desired information in a short time is very important for the agent, search engine and data mining systems. Thus, we try to design an intelligent system with the characteristics of low complexity, quick convergence and low output error for both academia and industry. We use grey relational analysis to select more important input variables to establish a simplified fuzzy model. Then, we exploit the concepts of extension theory to adjust the fuzzy model during the parameter identification to expedite the tuning process. Finally, the proposed extension-based fuzzy model is applied to implementing an intelligent information retrieval system for the search engine to stress the model's applicability.
downloaded from King’s Research Portal

Benzo[ a ]pyrene (BaP) is a widespread environmental carcinogen activated by cytochrome P450 (P450) enzymes. In Hepatic P450 Reductase Null (HRN) and Reductase Conditional Null (RCN) mice, P450 oxidoreductase (Por) is deleted specifically in hepatocytes, resulting in the loss of essentially all hepatic P450 function. Treatment of HRN mice with a single i.p. or oral dose of BaP (12.5 or 125 mg/kg body weight) resulted in higher DNA adduct levels in liver (up to 10-fold) than in wild-type (WT) mice, indicating that hepatic P450s appear to be more important for BaP detoxification in vivo . Similar results were obtained in RCN mice. We tested whether differences between hepatocytes and non-hepatocytes in P450 activity may underlie the increased liver BaP-DNA binding in HRN mice. Cellular localisation by immunohistochemistry of BaP-DNA adducts showed that HRN mice have ample capacity for formation of BaP-DNA adducts in liver, indicating that the metabolic process does not result in the generation of a reactive species different from that formed in WT mice. However, increased protein expression of cytochrome b 5 in hepatic microsomes of HRN relative to WT mice suggests that cytochrome b 5 may modulate the P450-mediated bioactivation of BaP in HRN mice, partially substituting the function of Por.
Plasmid Incidence in Bacteria from Deep Subsurface Sediments

Bacteria were isolated from deep terrestrial subsurface sediments underlying the coastal plain of South Carolina. A total of 163 isolates from deep sediments, surface soil, and return drill muds were examined for plasmid DNA content and resistance to the antibiotics penicillin, ampicillin, carbenicillin, streptomycin, kanamycin, and tetracycline. MICs of Cu2+, Cr3+, and Hg2+ for each isolate were also determined. The overall frequency of plasmid occurrence in the subsurface bacteria was 33%. Resistance was most frequent to penicillin (70% of all isolates), ampicillin (49%), and carbenicillin (32%) and was concluded to be related to the concentrations of the individual antibiotics in the disks used for assaying resistance and to the production of low levels of β-lactamase. The frequencies of resistance to penicillin and ampicillin were significantly greater for isolates bearing plasmids than for plasmidless isolates; however, resistance was not transferable to penicillin-sensitive Escherichia coli. Hybridization of subsurface bacterial plasmids and chromosomal DNA with a whole-TOL-plasmid (pWWO) probe revealed some homology of subsurface bacterial plasmid and chromosomal DNAs, indicating a potential for those bacteria to harbor catabolic genes on plasmids or chromosomes. The incidences of antibiotic resistance and MICs of metals for subsurface bacteria were significantly different from those for drill mud bacteria, ruling out the possibility that bacteria from sediments were derived from drill muds.
Quality of Life in Asthmatic Outpatients

Asthma patients incur a great cost in terms of loss of quality of life. The purpose of this study is to evaluate the relative contribution and relationship of several patient- and disease-related factors, measured by several variables, to the quality of life in adults with asthma. Two hundred and ten asthmatic outpatients over 18 years old, registered in a Family Health Unit, were randomly selected to complete the Asthma Quality of Life (AQLQ) and Short Form Generic questionnaires (SF-36), respectively. Single and multiple linear regression models were developed to explain the variability of the summary scores of AQLQ and Physical and Mental Health SF-36. As potential predictors, the following independent variables were used: gender, age, number of comorbidities, asthma severity following the Global Initiative for Asthma (GINA) criteria, asthma control (measured by ACQ questionnaire), %FEV1 (forced expiratory volume in the first second) and, for the first time, Graffar Score to assess socioeconomical features. The Graffar Score is an index that divides the population in 5 socioeconomic layers. We report the best Adjusted R Square of these models published in the literature, ranging from 0.40 to 0.76. Women showed poorer quality of life than men. The best predictor of AQLQ was ACQ, followed by Asthma Severity, Gender and %FEV1. The best predictors of Physical and Mental Health SF-36 were, by decreasing importance, ACQ, number of comorbidities, Gender and Graffar Score. We note that the variable number of comorbidities was included in both SF-36 models, but not in AQLQ model. Asthma Severity and %FEV1 did not enter into SF-36 models. We conclude that besides clinical and functional measures, the evaluation process of the overall health status must incorporate quality-of-life measures.
Motivational feedback in crowdsourcing: a case study in speech transcription

A widely used strategy in human and machine performance enhancement is achieved through feedback. In this paper we investigate the effect of live motivational feedback on motivating crowds and improving the performance of the crowdsourcing computational model. The provided feedback allows workers to react in real-time and review past actions (e.g. word deletions); thus, to improve their performance on the current and future (sub) tasks. The feedback signal can be controlled via clean (e.g. expert) supervision or noisy supervision in order to trade-off between cost and target performance of the crowd-sourced task. The feedback signal is designed to enable crowd workers to improve their performance at the (sub) task level. The type and performance of feedback signal is evaluated in the context of a speech transcription task. Amazon Mechanical Turk (AMT) platform is used to transcribe speech utterances from different corpora. We show that in both clean (expert) and noisy (worker/turker) real-time feedback conditions the crowd workers are able to provide significantly more accurate transcriptions in a shorter time.
Transcriptional Activation of Human CYP17 in H295R Adrenocortical Cells Depends on Complex Formation among p54nrb/NonO, Protein-Associated Splicing Factor, and SF-1, a Complex That Also Participates in Repression of Transcription.

The first 57 bp upstream of the transcription initiation site of the human CYP17 (hCYP17) gene are essential for both basal and cAMP-dependent transcription. EMSA carried out by incubating H295R adrenocortical cell nuclear extracts with radiolabeled −57/−38 probe from the hCYP17 promoter showed the formation of three DNA-protein complexes. The fastest complex contained steroidogenic factor (SF-1) and p54nrb/NonO, the intermediate complex contained p54nrb/NonO and polypyrimidine tract-binding protein-associated splicing factor (PSF), and the slowest complex contained an SF-1/PSF/p54nrb/NonO complex. (Bu)2cAMP treatment resulted in a cAMP-inducible increase in the binding intensity of only the upper complex and also activated hCYP17 gene transcription. SF-1 coimmunoprecipitated with p54nrb/NonO, indicating direct interaction between these proteins. Functional assays revealed that PSF represses basal transcription. Further, the repression of hCYP17 promoter-reporter construct luciferase activity resulted fro.
GRIMS: a scalable management and storage system for massive remote sensing images

Remote sensing images are important in ecological, geographical and military applications. With the rapid growing volume of remote sensing images, how to manage and store the massive remote sensing images is becoming a must-be-solved problem. We build a scalable storage and management system for massive remote sensing images aiming to store global remote sensing images -- Global Remote Sensing Images Management and Storage system (GRIMS). In GRIMS, we propose a tile pyramid model -- Plate Carree Projection Grid Quad-Tree (PCPGQT) to spatially partition the high resolution images and build a double tower (DT) index for the big image data file. Meanwhile, we analyze the fragment problem in image mosaic. Through fragment collection, huge disk spaces could be saved. By using the open source software HADOOP, we realize a distributed storage system to store massive image data file. Experiments show that our tile pyramid model is suitable to support our system purpose, and the distributed storage system is highly efficient.
Tissue shrinkage and unbiased stereological estimation of particle number and size *

This paper is a review of the stereological problems related to the unbiased estimation of particle number and size when tissue deformation is present. The deformation may occur during the histological processing of the tissue. It is especially noted that the widely used optical disector may be biased by dimensional changes in the z‐axis, i.e. the direction perpendicular to the section plane. This is often the case when frozen sections or vibratome sections are used for the stereological measurements. The present paper introduces new estimators to be used in optical fractionator and optical disector designs; the first is, as usual, the simplest and most robust. Finally, it is stated that when tissue deformation only occurs in the z‐direction, unbiased estimation of particle size with several estimators is possible.
Tongue colour and coating prediction in traditional Chinese medicine based on visible hyperspectral imaging

Tongue diagnosis is an important concept in Traditional Chinese Medicine (TCM). The tongue colour and coating can aid understanding of the body's physiological mechanisms, as well as the pathology of diseases. Existing research has focused on using digital images and tongue colour classification, without considering the other visible bands of information in the tongue. In this study, a visible hyperspectral image system, with an approximate spectral range of 400–1000 nm, was used to predict the tongue colour values and the coating position in TCM, and a stacked autoencoder (SAE) predict model based on spectral–spatial feature was performed to digital the tongue colour space and the coating. The experimental results show the effectiveness of the spectral–spatial feature with SAE model in predicting the CIELAB values of L, a, and coating position, thus the authors provide a new technique for the objective and digitising development of TCM.
Sequential Mining Classification

Sequential pattern mining is a data mining technique that aims to extract and analyze frequent subsequences from sequences of events or items with time constraint. Sequence data mining was introduced in 1995 with the well-known Apriori algorithm. The algorithm studied the transactions through time, in order to extract frequent patterns from the sequences of products related to a customer. Later, this technique became useful in many applications: DNA researches, medical diagnosis and prevention, telecommunications, etc. GSP, SPAM, SPADE, PrefixSPan and other advanced algorithms followed. View the evolution of data mining techniques based on sequential data, this paper discusses the multiple extensions of Sequential Pattern mining algorithms. We classified the algorithms into Sequential Pattern mining, Sequential rule mining and Sequence prediction with their extensions. The classification is presented in a tree at the end of the paper.
Optimal Hadoop over ICN Placement Algorithm for Networking and Distributed Computing

Information-Centric Networking (ICN) is very promising for Hadoop-based distributed computing systems, where the data-centric approach is advantageous in reducing the data retrieval latency as well as the network traffic for Hadoop services. Moreover, the inherent in-network caching and computing features in ICN relaxes the end-to-end connectivity between consumers and producers (this helps networking, computation, and power efficiency as Hadoop nodes will use ICN services). Yet, building such a complex system needs new definitions and mappings on the architecture side. It needs also a flattening of the components and an optimization relative to data flow and computation performance. These issues are presented in this paper. Optimal optimization algorithms are then proposed, implemented and evaluated to improve the overall network performance. Experiments demonstrate that ICN support of Hadoop is a feasible architecture and show to improve the performance of Hadoop systems and reduce the end-to-end consumer delay.
Distant supervised relation extraction via long short term memory networks with sentence embedding

Distant supervision is a widely applied approach in field of relation extraction, which could automatically generate large amounts of labeled training corpus with minimal manual effort. However, the labeled training corpus may have many false positive instances, which would hurt the performance of relation extraction. Moreover, in traditional distant supervised approaches, extraction models adopt human-design features with complicated natural language processing (NLP) preprocessing. It may cause poor performance either. To address these two shortcomings, in this work, we propose a novel Long Short Term Memory (LSTM) network integrated with multi-instance learning. Our approach is supposed to learn and extract features automatically from the data itself and treats distant supervision as a multi-instance learning problem to settle the problem of false positive instances. Experimental results demonstrate that our proposed approach is effective and achieve better performance than traditional methods.
To integrate or not to integrate?

Jewell addresses an important issue in questioning the benefits and risks of closer integration between the primary and acute care sectors.1 In a desperate search to explain poor health system performance, many commentators have seized upon the lack of vertical integration in the UK as A Problem Needing a Solution. At face value, they are …