Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic SAP102 expression in the hippocampal subregions of rats and APP/PS1 mice of various ages

The hippocampus is a structurally and functionally complex brain area that plays important and diverse roles in higher brain functions, such as learning and memory, and mounting evidence indicates that different hippocampal subregions play distinctive roles. The hippocampus is also one of the first regions in the brain to suffer damage in Alzheimer's disease (AD). Synaptic dysfunction in the hippocampus, rather than neuronal loss per se, is paralleled by behavioural and functional deficits in AD. The membrane‐associated guanylate kinase (MAGUK) family of proteins, including SAP102, PSD‐95, PSD‐93 and SAP97, have long been recognized as essential components of the postsynaptic density (PSD) at excitatory synapses. Hippocampal spines are the predominant synaptic transmission sites of excitatory glutamatergic synapses. During postnatal brain development, individual MAGUK members show distinct expression patterns. Although SAP102 has been confirmed as the dominant scaffold protein in neonatal synapses, its expression profiles in adult and ageing rodent hippocampi are discrepant. Furthermore, in AD brains, significantly reduced SAP102 protein levels have been found, suggesting that SAP102 may be related to AD progression; however, the precise mechanism underlying this result remains unclear. Herein, we observed distinct SAP102 expression profiles in the hippocampal CA1, CA3 and DG subregions of rats and APPswe/PS1dE9 (APP/PS1) mice at various ages using immunofluorescence. In Wistar rats, SAP102 was not only highly expressed in the hippocampal subregions of neonatal rats but also maintained relatively high expression levels in adult hippocampi and displayed no obvious decreases in the CA1 and DG subregions of aged rats. Surprisingly, we observed abnormally high SAP102 expression levels in the CA1 stratum moleculare and CA3 stratum polymorphum subregions of 2‐month‐old APP/PS1 mice, but low SAP102 levels in the DG and CA3 subregions of 7‐month‐old APP/PS1 mice, reflecting the subregion‐specific reactivity and vulnerability of AD mouse models in different disease stages. Our findings provide fundamental data to support the functional differences of SAP102 in different hippocampal subregions during postnatal periods and may serve as the basis for additional functional studies on SAP102 in normal physiological conditions and different stages of AD.
Tear Film Steroid Profiling in Dry Eye Disease by Liquid Chromatography Tandem Mass Spectrometry

Dry eye disease (DED) is a multifactorial disorder of the ocular surface unit resulting in eye discomfort, visual disturbance, and ocular surface damage; the risk of DED increases with age in both sexes, while its incidence is higher among females caused by an overall hormonal imbalance. The role of androgens has recently investigated and these hormones were considered to have a protective function on the ocular surface. In order to correlate DED to tear steroid levels, a robust, specific, and selective method for the simultaneous quantification of cortisol (CORT), corticosterone (CCONE), 11-deoxycortisol (11-DECOL), 4-androstene-3,17-dione (ADIONE), testosterone (TESTO), 17α-hydroxyprogesterone (17-OHP), and progesterone (PROG) was developed and applied for the analysis of tear samples. The method involves a simple extraction procedure of steroids from tears collected on Schirmer strips, followed by a high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis. In total, tear samples from 14 DED female patients and 13 healthy female controls were analysed and, CORT, ADIONE, and 17-OHP response levels resulted significantly decreased in dry eye patients respect to controls. The receiver operating characteristic (ROC) curve obtained by the combination of these three steroids (AUC = 0.964) demonstrated the good diagnostic power of the differential tear steroids in identifying DED. In conclusion, the present method made it possible, for the first time, to study steroid profiling directly in tear fluid.
RuleSelector

Modern smartphones and ubiquitous computing systems collect a wealth of context data from users. Conditional action rules, as popularized by the IFTTT (If-This-Then-That) platform, are a popular way for users to automate frequently repeated tasks or receive smart reminders, due to the intelligibility and control that rules provide to users. A key drawback of IFTTT systems is that they place the burden of manually specifying action rules on the user. While multiple rule mining algorithms have been proposed in existing work to automatically discover action rules, they generate hundreds of action rules, and the problem of how to present a small subset of rules to smartphone users and allow them to interactively select action rules remains unsolved. In this work, we take the first step towards solving this problem by designing and implementing RuleSelector, the first interactive rule selection tool to allow smartphone users to browse, modify, and select action rules from a small set of summarized rules presented to the user. We propose novel rule selection metrics to address the needs of smartphone users, and analyze the performance of RuleSelector using data from 200 users. We also perform a qualitative user study in order to evaluate how users use the RuleSelector tool and perceive the selected rules, and present the insights gained and design recommendations for future rule selection systems. Our users rated the selected rules from useful to very useful, and an important finding of our study is that users prefer an interactive rule selection system such as RuleSelector that automatically suggests rules, but allows users to select and modify the suggested rules. Finally, we examine the promise of RuleSelector in other ubiquitous computing systems such as smart homes and smart TVs by applying our tool to public context datasets from these domains.
A decentralized solution for IoT data trusted exchange based-on blockchain

Internet of Things (IoT) plays an important role in the development of various fields. The increasing scale and scope of applications make a great demand of IoT data exchange in recent years. Meanwhile, a number of IoT data exchange platforms which dedicated to connecting various and distributed data sources are emerging. In such a platform, service providers can search and exchange the data sets that they need. However, the centralized infrastructure cannot provide enough trust as the third-party intermediaries for data exchange. As a result, most platforms unable to satisfy the complex requirements due to few institutions and individuals are willing to share their IoT data sets in such an untrustworthy environment. This paper proposes a decentralized solution based on the blockchain for IoT data trusted exchange. Specifically, In this paper, the basic principles of blockchain and corresponding key technologies are expounded through in-depth analysis of three main reliable requirements in IoT data exchange. Besides, this paper provides an architecture of above solution and detailed design of its main trust component. Finally, it realizes a prototype by using Ethereum blockchain and smart contracts and presents its auditable, transparent, decentralized features visually.
Effects of the antimicrobial contaminant triclocarban, and co‐exposure with the androgen 17β‐trenbolone, on reproductive function and ovarian transcriptome of the fathead minnow (Pimephales promelas)

Triclocarban (TCC) is an antimicrobial agent routinely detected in surface waters that has been hypothesized to interact with the vertebrate endocrine system. The present study examined the effects of TCC alone and in combination with the model endocrine disruptor 17β‐trenbolone (TRB) on fish reproductive function. Adult Pimephales promelas were continuously exposed to either 1 µg TCC/L or 5 µg TCC/L, to 0.5 µg TRB/L, or to a mixture (MIX) of 5 µg TCC/L and 0.5 µg TRB/L for 22 d, and a variety of reproductive and endocrine‐related endpoints were examined. Cumulative fecundity was significantly reduced in fathead minnows exposed to TRB, MIX, or 5 µg TCC/L. Exposure to 1 µg TCC/L had no effect on reproduction. In general, both TRB and MIX treatments caused similar physiological effects, evoking significant reductions in female plasma vitellogenin, estradiol, and testosterone, and significant increases in male plasma estradiol. Based on analysis of the ovarian transcriptome, there were potential pathway impacts that were common to both TRB‐ and TCC‐containing treatment groups. In most cases, however, those pathways were more plausibly linked to differences in reproductive status than to androgen‐specific functions. Overall, TCC was reproductively toxic to fish at concentrations at or near those that have been measured in surface water. There was little evidence that TCC elicits reproductive toxicity through a specific mode of endocrine or reproductive action, nor that it could augment the androgenic effects of TRB. Nonetheless, the relatively small margin of safety between some measured environmental concentrations and effect concentrations suggests that concern is warranted. Environ Toxicol Chem 2017;36:231–242. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.
“It’s a gut feeling” – Escherichia coli biofilm formation in the gastrointestinal tract environment

Abstract Escherichia coli can commonly be found, either as a commensal, probiotic or a pathogen, in the human gastrointestinal (GI) tract. Biofilm formation and its regulation is surprisingly variable, although distinct regulatory pattern of red, dry and rough (rdar) biofilm formation arise in certain pathovars and even clones. In the GI tract, environmental conditions, signals from the host and from commensal bacteria contribute to shape E. coli biofilm formation within the multi-faceted multicellular communities in a complex and integrated fashion. Although some major regulatory networks, adhesion factors and extracellular matrix components constituting E. coli biofilms have been recognized, these processes have mainly been characterized in vitro and in the context of interaction of E. coli strains with intestinal epithelial cells. However, direct observation of E. coli cells in situ, and the vast number of genes encoding surface appendages on the core or accessory genome of E. coli suggests the complexity of the biofilm process to be far from being fully understood. In this review, we summarize biofilm formation mechanisms of commensal, probiotic and pathogenic E. coli in the context of the gastrointestinal tract. Graphical Abstract
Optical neuronal guiding on the hypothalamic GnRH cell line GT1

Acknowledgements First of all, I want to thank my supervisor Prof. Mark Raizen for giving me the unique opportunity to work in his research group. It was a great experience and I learned a lot in this year. I appreciate the way he works together with his students, his unrestricted support and all his helpful discussions. I also want to thank Samantha Moore and Florian Schreck, who introduced me to the project and worked together with me for the past year. Samantha, you taught me a lot in the beginning, all I know about cell culture I learned from you, and I am grateful you always helped me and supported me. I had a lot of fun in the lab. Thanks also to Artem and Chuangwei for the nice atmosphere in the office, it was nice having you around. And of course there are all the other members of the Raizen group in the cold-atoms lab, who always helped me looking for optics parts and Florian. Last but not least, I want to thank my parents and the rest of my family in Germany for their support during that year, which also contributed a lot to my having a pleasant stay here in Austin. This work descibes experiments on optical neuronal guiding in vitro performed on the hypothalamic gonadotropin-releasing hormone (GnRH) cell line GT1. Briefly, a focused laser beam is set on the growing tip of the axon to induce further growth, making use of the dipole force the laser exerts on polarizable particles within the cell or in the cell membrane. After a brief introduction to the idea of optical neuronal guiding and its first results, an outline of the cell line GT1 will be presented, followed by a comparison with the cell line NG108. The main part of this thesis presents the experimental setup, the experiments themselves and their results. The two final chapters discuss these results and give a theoretical approach.
RANS SIMULATION OF COMBINED FLOW AND HEAT TRANSFER THROUGH OPE-CELL ALUMINUM FOAM HEAT SINK

Frequently, advanced electronics, optics, nuclear equipment and high frequency microwaves systems require cooling of some devices at a heat flux of about 5-30 MW/m. To meet this demand the porous medium of the heat exchangers has to be compressed thus the spherical particles are distorted and agglomerated. The aim of this research is to study by simulation the effect of open cell aluminum foam on the heat transfer and pressure drop in cooling devices at the high heat fluxes. Heat transfer and pressure drop in an open foam heat exchanger, made of aluminum of different porosity (ε) and porous density (PPI), cooled by water were investigated numerically using CFD code Fluent and the results are presented. Maximum fluid flow velocity used was 1.2m/s. The permeability (K) and form coefficient (cF) varied from 2.52×10 m and 1276 m to 3.44×10 m and 4731 m, respectively. It was determined that the flow rate range influenced these calculated parameters. Heat flux (q) up to 1.38 MW/m was removed by using porous sample with porosity 60% (ε=0.608) and average pore diameter (dp) 2.3mm. Under this simulating condition, the difference between the temperature of the wall and the bulk water did not exceed 630C. An estimate of heat sink efficiency using compressed aluminum foam for cooling high-power electronic devices was done. The results obtained in this study are relevant to engineering applications employing metal foams ranging from convection heat sinks to filters and flow straightening devices.
STOMACH SPECIFIC GASTRORETENTIVE FLOATING TABLET OF ANTI-HYPERLIPIDEMIC DRUG: FORMULATION DEVELOPMENT AND IN-VITRO CHARACTERIZATION

The aim of the present study to develop the various processing parameters and formulations aspects for developing a pharmaceutical equivalent, stable, cost improved and quality improved formulation of floating tablet of Simvastatin comparable with innovator and optimize certain process parameters to get maximum yield of the product during large scale manufacturing. Being a Class II drug, Simvastatin shows slow dissolution rate, limited oral absorption and high variability in pharmacological effects. Gastro retentive floating tablet of Simvastatin was prepared by direct compression technique using HPMC K15M as the rate controlling polymer. The hydrophilic cellulose derivative, HPMC K15M was evaluated for its gel forming and release controlling properties. Sodium bicarbonate and citric acid were incorporated as gas generating agents. The effects of soluble components (sodium bicarbonate and citric acid) and gel forming agents on drug release profile and floating properties were investigated. The tablets from all formulations were evaluated for thickness, diameter, weight variation, hardness, and friability. In vitro drug release, kinetic data and related stability studies after optimization of promising formulation of selected drug are being done to exhibit diffusion dominant drug release and its stability may be attributed to that the present problem certainly will be helpful and surely will open an avenue for new trend of control drug delivery system. The release mechanisms were explored and explained with zero order, first order, Higuchi, Hixon Crowell and Korsmeyer equations. The release rate, extent and mechanisms were found to be WO
Combine-and-conquer: improving the diversity in similarity search through influence sampling

Result diversification methods are intended to retrieve elements similar to a given object whereas also enforcing a certain degree of diversity among them, aimed at improving the answer relevance. Most of the methods are based on optimization, but bearing NP-hard solutions. Diversity is injected into an otherwise all-too-similar result set in two phases: in the first, the search space is reduced to speed up finding the optimal solution, whereas in the second a trade-off between diversity and similarity over the reduced space is obtained. It is assumed that the first phase is achieved by applying a traditional nearest neighbor algorithm, but no previous investigation evaluated the impact of the first over the second phase. In this paper, we devised alternative techniques to execute the first phase and evaluated how obtaining a better quality set of elements in the first phase can improve the diversity. Besides the traditional nearest neighbor-based pre-selection, we also considered naive random selection, cluster-based and influence-based ones. Thereafter, extensive experiments evaluated a number of state-of-the-art diversity algorithms employed in the second phase, regarding both processing time and answer quality. The obtained results have shown that although the much more elaborated (and much more time consuming) methods indeed provide best answers, other alternatives are able to provide a better commitment regarding quality and performance. Moreover, the pre-selection techniques can reduce the total running time by up to two orders of magnitude.
The 2018 DAVIS Challenge on Video Object Segmentation

We present the 2018 DAVIS Challenge on Video Object Segmentation, a public competition specifically designed for the task of video object segmentation. It builds upon the DAVIS 2017 dataset, which was presented in the previous edition of the DAVIS Challenge, and added 100 videos with multiple objects per sequence to the original DAVIS 2016 dataset. Motivated by the analysis of the results of the 2017 edition, the main track of the competition will be the same than in the previous edition (segmentation given the full mask of the objects in the first frame -- semi-supervised scenario). This edition, however, also adds an interactive segmentation teaser track, where the participants will interact with a web service simulating the input of a human that provides scribbles to iteratively improve the result.
Energy efficiency maximization in ultra dense heterogeneous cellular network, considering both downlink and uplink

Analysis of data traffic in the cellular network indicates that its growing trend will continue. Therefore, it needs to increase the cellular network's capacity. Heterogeneous cellular network is a promising solution for improving energy and spectrum efficiency. On the other hand, due to the limited energy of the batteries, the signals sent by the User Equipment (UE) are not strong and will be attenuated by the destructive factors (such as path loss). Therefore, considering some parameters related to power consumption of UE can improve the quality of uplink signals with an acceptable power usage. In this paper, a novel scheme is proposed for heterogeneous cellular network, which utilizes cell switch on/off and continuous cell zooming techniques. The scheme aims at maximizing energy efficiency, defined in both downlink and uplink. In the proposed scheme, an optimization problem is defined whose utility function aims to maximize energy efficiency. PSO method is used to solve the problem. The results show that when the number of users increases, the proposed scheme achieves lower energy consumption and higher energy and spectral efficiency compared to the previous studies.
Propagation characteristics of the Underground-to-Aboveground Communication link about 2.4GHz and 433MHz radio wave: An empirical study in the pine forest of Guizhou Province

Wireless Underground Sensor Network (WUSN) is an emerging research area. They are used in many fields from intelligent irrigation to safety and assisted navigation [1]. Wireless underground sensor networks (WUSN) also enable a wide variety of novel applications [2], [3], including soil condition monitoring, earthquake and landslide prediction, underground infrastructure monitoring, sports-field turf management, landscape management, border patrol and security, and etc. Although Traditional wireless communication techniques using electromagnetic (EM) waves encounter three major problems in underground environments: the high path loss, the dynamic channel condition and the large antenna size [4]. However, given the great value of wireless underground sensor networks, further research is necessary, and which also stimulates the interest of many scholars at home and abroad. Channel model is essentially important to WUSN study. There are many relevant studies on Channel Model of WUSN such as in [5][6][7]. By comparison, and according to the condition of pine forest in Guizhou province, we choose a relatively appropriate path loss model in [7]. We will discuss the selected model later. In this paper, two CC2530 RF communication modules and two NRF905 RF communication modules are used to carry out Underground-to-Aboveground communication experiment, respectively, through the experimental study we can find the communication characteristics of Underground-to-Aboveground communication link of wireless underground sensor network of pine forest in Guizhou province. In this paper, the influence of the depth of the underground node on the communication effect is mainly studied. The height of the receiver is divided into three gradients of 70,100,130cm, and the depth of the underground module is divided into five gradients of 5, 10, 15 and 20cm.
Pairwise learning using multi-lingual bottleneck features for low-resource query-by-example spoken term detection

We propose to use a feature representation obtained by pairwise learning in a low-resource language for query-by-example spoken term detection (QbE-STD). We assume that word pairs identified by humans are available in the low-resource target language. The word pairs are parameterized by a multi-lingual bottleneck feature (BNF) extractor that is trained using transcribed data in high-resource languages. The multi-lingual BNFs of the word pairs are used as an initial feature representation to train an autoencoder (AE). We extract features from an internal hidden layer of the pairwise trained AE to perform acoustic pattern matching for QbE-STD. Our experiments on the TIMIT and Switchboard corpora show that the pairwise learning brings 7.61% and 8.75% relative improvements in mean average precision (MAP) respectively over the initial feature representation.
Adaptive structured subspace clustering algorithm

Sparse subspace clustering (SSC) algorithm, founds a new pattern for the subspace clustering, and has led to the satisfactory results in many applications. SSC is implemented in two phases: learning a sparse affinity matrix and performing spectral clustering on the affinity matrix. However, SSC can not commendably cluster together the correlated data within cluster, as well as explicitly capture the natural relationship between the affinity matrix and the segmentation of the data. Motivated by some of the CASS and S3C algorithms, a combinatorial algorithm is presented in this paper. Using trace Lasso instead of l1 norm as regularization constraint, it can adaptively segment subspace and lead to more dense intra-cluster and more sparse inter-cluster. Using a joint optimization framework, it can organically connect two phases of SSC. The optimization model is solved by combining efficient alternating minimization and alternating direction method of multipliers. Experiments on Synthetic data, Handwritten Digits dataset, Extended Yale B and ORL facial databases demonstrate the effectiveness of ASSC approach.