Miracle-dz/UniFAR-FTUs huggingface dataset:
Hydrostatic pressure sensing using a polymer optical fibre Bragg gratings

The sensitivity of a fibre Bragg grating (FBG) sensor fabricated in polymer optical fibre (POF) to hydrostatic pressure was investigated for the first time. In this initial investigative work a reflected Bragg response of a FBG fabricated in multimode microstructured POF (MMmPOF) was monitored, whilst the hydrostatic pressure was increased up to 10MPa. Positive sensitivities were observed, meaning a positive wavelength shift to increasing pressure, as opposed to negative sensitivities monitored when using a FBG sensor fabricated in silica optical fibre. The FBG sensors fabricated in the MMmPOF gave fractional changes in wavelength and hence sensitivities of at least 64.05×10-6/MPa, which is some 25 times larger than the -2.50×10-6/MPa sensitivity of a FBG sensor fabricated in silica optical fibre that was measured in this work. Furthermore this work highlighted a decrease in sensitivity of the FBG sensor fabricated in the MMmPOF by some 50% by sealing the holes of the mPOF at the tip of the fibre with an adhesive. This offers the potential to tailor the response of the sensor to hydrostatic pressure.
Nanosecond Pulse Generation at 2.7 μm From a Passively Q-Switched Er:Y2O 3 Ceramic Laser

Efficient passively Q-switched Er:Y<sub>2</sub>O<sub>3</sub> ceramic lasers operating at 2.7 <italic>μ </italic>m were demonstrated. Using a semiconductor saturable absorber mirror (SESAM) of 2.4% modulation depth, we achieved 63 ns pulses that are close to the limit set by the cavity length. For 9.5 W of the absorbed pump power, an average output power of 0.88 W was generated with a pulse energy of 17.4 <italic>μ</italic> J and a pulse duration of 63 ns, resulting a pulse peak power of 0.27 kW. By using an SESAM with a lager modulation depth, shorter pulses of 29 ns were generated. To our knowledge, this is the first report of sub-100 ns pulses from the continuously pumped ∼3-<italic>μ</italic>m passively Q-switched lasers. The prospects for further pulse shortening are considered, and these results may give a further insight into 3-<italic> μ</italic>m passively Q-switched laser systems.
Preparation and properties of poly(L-lactic acid) scaffolds by thermally induced phase separation from a ternary polymer–solvent system

Poly(L-lactic acid) (PLLA) foams for tissue engineering were prepared via thermally induced phase separation of a ternary system PLLA/dioxane/tetrahydrofuran (THF) followed by double solvent exchange (water and ethyl alcohol) and drying. An extension to solidification from solution of a previously developed method for solidification from the melt was adopted. The technique is based on a continuous cooling transformation (CCT) approach, consisting in recording the thermal history experienced by rapidly cooled samples and then analyzing the resulting sample morphology. Different foams were produced by changing the relative amount of dioxane and THF in the starting solution while the amount of polymer was kept constant. Results show that the final morphology and crystallinity (measured by DSC) depend on solvent power, which in its turn was determined by the ratio dioxane/THF, and a minimum of pore size, optimum final crystallinity and crystallization rate were achieved for a system containing 70 % of dioxane. Under this condition, a higher bulk density (evaluated by Hg intrusion porosimetry) and a larger specific surface area (measured by BET N2 sorption technique) was achieved. Copyright © 2004 Society of Chemical Industry
The small heat shock protein B8 (HSPB8) modulates proliferation and migration of breast cancer cells

Breast cancer (BC) is one of the major causes of cancer death in women and is closely related to hormonal dysregulation. Estrogen receptor (ER)-positive BCs are generally treated with anti hormone therapy using antiestrogens or aromatase inhibitors. However, BC cells may become resistant to endocrine therapy, a process facilitated by autophagy, which may either promote or suppress tumor expansion. The autophagy facilitator HSPB8 has been found overexpressed in some BC. Here we found that HSPB8 is highly expressed and differentially modulated by natural or synthetic selective ER modulators (SERMs), in the triple-positive hormone-sensitive BC (MCF-7) cells, but not in triple-negative MDA-MB-231 BC cells. Specific SERMs induced MCF-7 cells proliferation in a HSPB8 dependent manner whereas, did not modify MDA-MB-231 cell growth. ER expression was unaffected in HSPB8-depleted MCF-7 cells. HSPB8 over-expression did not alter the distribution of MCF-7 cells in the various phases of the cell cycle. Conversely and intriguingly, HSPB8 downregulation resulted in an increased number of cells resting in the G0/G1 phase, thus possibly reducing the ability of the cells to pass through the restriction point. In addition, HSPB8 downregulation reduced the migratory ability of MCF-7 cells. None of these modifications were observed, when another small HSP (HSPB1), also expressed in MCF-7 cells, was downregulated. In conclusion, our data suggest that HSPB8 is involved in the mechanisms that regulate cell cycle and cell migration in MCF-7 cells.
Extending signal temporal logic specifications for distributed model predictive control

In recent years, model predictive control with signal temporal logic (STL) propositions serving as the constraints has become an emerging research area. In this paper, we extend STL to specify the behaviors of both controlled systems and controllers in the distributed model predictive control (DMPC) framework. The proposed design aims to specify desired properties and satisfy correctness requirements. To obtain optimal controllers and expected properties, we encode an auto-programming to combine the system dynamics and the STL constraints into a mixed-integer linear/quadratic programming (MILP/MIQP) optimization problem. What's more, the experimental results for controllers of multi-tank liquid-level control systems are presented to verify the correctness of this procedure.
Advanced, Analytic, Automated (AAA) Measurement of Engagement During Learning

It is generally acknowledged that engagement plays a critical role in learning. Unfortunately, the study of engagement has been stymied by a lack of valid and efficient measures. We introduce the advanced, analytic, and automated (AAA) approach to measure engagement at fine-grained temporal resolutions. The AAA measurement approach is grounded in embodied theories of cognition and affect, which advocate a close coupling between thought and action. It uses machine-learned computational models to automatically infer mental states associated with engagement (e.g., interest, flow) from machine-readable behavioral and physiological signals (e.g., facial expressions, eye tracking, click-stream data) and from aspects of the environmental context. We present 15 case studies that illustrate the potential of the AAA approach for measuring ensgagement in digital learning environments. We discuss strengths and weaknesses of the AAA approach, concluding that it has significant promise to catalyze engagement research.
Learning Max-Margin GeoSocial Multimedia Network Representations for Point-of-Interest Suggestion

With the rapid development of mobile devices, point-of-interest (POI) suggestion has become a popular online web service, which provides attractive and interesting locations to users. In order to provide interesting POIs, many existing POI recommendation works learn the latent representations of users and POIs from users' past visiting POIs, which suffers from the sparsity problem of POI data. In this paper, we consider the problem of POI suggestion from the viewpoint of learning geosocial multimedia network representations. We propose a novel max-margin metric geosocial multimedia network representation learning framework by exploiting users' check-in behavior and their social relations. We then develop a random-walk based learning method with max-margin metric network embedding. We evaluate the performance of our method on a large-scale geosocial multimedia network dataset and show that our method achieves the best performance than other state-of-the-art solutions.
Frequent conceptual links and link-based clustering: A comparative analysis of two clustering techniques

Numerous social network mining methods have been proposed until now for addressing social mining tasks and specially searching for communities or frequent social patterns. However, the degree of complementarity of these methods has been very little studied. In this paper, we focus on two knowledge extraction processes in social networks: a link-based clustering that may extract social communities and a recent approach that searches for frequent conceptual link involving both clustering and search for frequent social patterns. We explore how the models extracted by each method may match and which potential useful knowledge they may provide. Our objective is to evaluate the potential relationships between communities and frequent conceptual links. For this purpose, we propose a set of measures for evaluating the degree to which these patterns extracted from the same dataset are matching. Our approach is applied on two datasets and demonstrates the importance of considering simultaneously various kinds of knowledge and their complementarity.
Social Media in Health — What are the Safety Concerns for Health Consumers?

Recent literature has discussed the unintended consequences of clinical information technologies (IT) on patient safety, yet there has been little discussion about the safety concerns in the area of consumer health IT. This paper presents a range of safety concerns for consumers in social media, with a case study on YouTube. We conducted a scan of abstracts on ‘quality criteria’ related to YouTube. Five areas regarding the safety of YouTube for consumers were identified: (a) harmful health material targeted at consumers (such as inappropriate marketing of tobacco or direct-to-consumer drug advertising); (b) public display of unhealthy behaviour (such as people displaying self-injury behaviours or hurting others); (c) tainted public health messages (i.e. the rise of negative voices against public health messages); (d) psychological impact from accessing inappropriate, offensive or biased social media content; and (e) using social media to distort policy and research funding agendas. The examples presented should contribute to a better understanding about how to promote a safe consumption and production of social media for consumers, and an evidence-based approach to designing social media interventions for health. The potential harm associated with the use of unsafe social media content on the Internet is a major concern. More empirical and theoretical studies are needed to examine how social media influences consumer health decisions, behaviours and outcomes, and devise ways to deter the dissemination of harmful influences in social media.
Fuzzy Clustering of Crowdsourced Test Reports for Apps

DevOps is a new approach to drive a seamless Application (App) cycle from development to delivery. As a critical part to promote the successful implementation of DevOps, testing can significantly improve team productivity and reliably deliver user experience. However, it is difficult to use traditional testing to cover diverse mobile phones, network environments, operating systems, and so on. Hence, many large companies crowdsource their App testing tasks to workers from open platforms. In crowdsourced testing, test reports submitted by workers may be highly redundant, and their quality may vary sharply. Meanwhile, multi-bug test reports may be submitted, and their root causes are hard to diagnose. Hence, it is a time-consuming and tedious task for developers to manually inspect these test reports. To help developers address the above challenges, we issue the new problem of Fuzzy Clustering Test Reports (FULTER). Aiming to resolve FULTER, a series of barriers need to be overcome. In this study, we propose a new framework named Test Report Fuzzy Clustering Framework (TERFUR) by aggregating redundant and multi-bug test reports into clusters to reduce the number of inspected test reports. First, we construct a filter to remove invalid test reports to break through the invalid barrier. Then, a preprocessor is built to enhance the descriptions of short test reports to break through the uneven barrier. Last, a two-phase merging algorithm is proposed to partition redundant and multi-bug test reports into clusters that can break through the multi-bug barrier. Experimental results over 1,728 test reports from five industrial Apps show that TERFUR can cluster test reports by up to 78.15% in terms of AverageP, 78.41% in terms of AverageR, and 75.82% in terms of AverageF1 and outperform comparative methods by up to 31.69%, 33.06%, and 24.55%, respectively. In addition, the effectiveness of TERFUR is validated in prioritizing test reports for manual inspection.
Robust power control for underlay cognitive radio networks under probabilistic quality of service and interference constraints

In cognitive radio networks, conventional power control algorithms (PCAs) based on instantaneous perfect channel gain may lead to performance degradation in practical systems, since channel uncertainties are inevitable because of quantisation errors and estimation errors. As a result, robustness of the algorithms becomes an important issue. However, traditional robust PCAs with probabilistic models require to perfectly know the distribution information of the estimation error (e.g. Gaussian distribution) which is difficult to obtain. Moreover, the distribution function of the actual error may not be Gaussian distribution. In this study, instead of using deterministic distribution model, a robust PCA based on a distribution-free method is designed to minimise total transmit power of secondary users subject to probabilistic interference and signal to interference plus noise ratio constraints. Based on the minimax probability machine, the original problem is reformulated as a second order cone programming problem solved by interior-point method. An adaptive estimation scheme is proposed to estimate the actual mean and covariance matrix of uncertain parameters. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm by comparing with the robust algorithms under worst-case constraints and probabilistic constraints, respectively.
In Vivo magnetic resonance imaging of xenografted tumors using FTH1 reporter gene expression controlled by a tet-on switch

As a promising magnetic resonance imaging (MRI) reporter, ferritin has been used to track cells in vivo; however, its continuous overexpression can be cytotoxic, which restricts its application. In this study, we aimed to develop a switch to turn this genetic reporter “on” or “off” while monitoring cell grafts via MRI. To accomplish this, we genetically modified the ferritin heavy chain (FTH1) with a Tet-On switch and assessed the expression of FTH1 in transduced neuroblastoma cells (SK-N-SH) in vitro and in xenografted tumors in vivo. We found that FTH1 expression induced by doxycycline (Dox) in SK-N-SH-FTH1 cells depended on treatment dose and duration. We successfully detected T2-weighted MRI contrast in cell grafts after switching “on” the reporter gene using Dox, and this contrast disappeared when we switched it “off”. The genetic reporter FTH1 can thus be switched “on” or “off” throughout longitudinal monitoring of cell grafts, limiting expression to when MRI contrast is needed. The controllable imaging system we have developed minimizes risks from constitutive reporter gene overexpression and facilitates tumor cell monitoring in vitro and in vivo.
Thick laminated circular plates on elastic foundation subjected to a concentrated load

In this study, the state equation for axisymmetric bending of laminated transversely isotropic circular plates on elastic foundation is established on the basis of three-dimensional elasticity. By using the expansions of Bessel functions, an analytical solution of the problem is presented. As a result, all the fundamental equations of three-dimensional elasticity can be satisfied exactly and all the independent elastic constants can be fully taken into account. Furthermore, the continuity conditions at the interfaces of plies can also be satisfied.
Spontaneous cluster activity in the inferior olivary nucleus in brainstem slices from postnatal mice

• The cerebellum is organized in modules, where groups of neurons in the inferior olivary nucleus (IO) are connected to elongated bands of Purkinje neurons in the cerebellar cortex; it is still largely unknown what the specific function of these modules is, and how they are formed. • Here we show that IO neurons spontaneously generate clusters of co‐active neurons in in vitro brain slice preparations from newborn mice, in an age window ranging from birth to two weeks old. • Intracellular recordings revealed that electrical coupling between neighbouring IO neurons may contribute to the synchronization. • The dorsomedial cell column, which is a subregion in the IO involved in the control of balance and posture, showed a high frequency of regular repeating clusters compared to the rest of the IO, suggesting that this system may be on a fast developmental track. • These results increase our understanding of how the circuitry of the cerebellar system develops in the early postnatal period, where animals acquire the ability to produce finely controlled motor acts.
Energy efficient uplink transmission for UE-to network relay in heterogeneous networks

UE-to-Network relay leverages the proximity communication between user equipments (UEs) and allows certain UEs to provide relay assistance for others, which can greatly improve system energy efficiency. In this paper, we consider the scenario where UEs suffering from bad channel condition and low battery level can communicate with the base station directly or via the help of other UEs in heterogeneous networks. The optimal power allocation and connectivity among UEs are studied, which aims at minimizing the system transmission energy while guaranteeing the minimum data rate requirement of each UE. An optimization framework is presented to formulate the system transmission energy minimization problem, which can be converted into a weighted one-to-one matching problem. And a practical joint transmission mode with relay selection and power allocation (JMRP) algorithm is developed to solve it. Simulation results show that the proposed algorithm outperforms the existing works in terms of system transmission energy and throughput.
Generalized MMSD feature extraction using QR decomposition

Multiple Maximum scatter difference (MMSD) discriminant criterion is an effective feature extraction method that computes the discriminant vectors from both the range of the between-class scatter matrix and the null space of the within-class scatter matrix. However, singular value decomposition (SVD) of two times is involved in MMSD, making this method impractical for high dimensional data. In this paper, we propose a novel method for feature extraction and classification based on MMSD criterion, called generalized MMSD (GMMSD), which employs QR decomposition rather than SVD. Unlike MMSD, GMMSD does not require the computation of the whole scatter matrix. Instead, it computes the discriminant vectors from both the range of whitenizated input data matrix and the null space of the within-class scatter matrix. We evaluate the effectiveness of the GMMSD method in terms of classification accuracy in the reduced dimensional space. Our experiments on two facial expression databases demonstrate that the GMMSD method provides favorable performance in terms of both recognition accuracy and computational efficiency.
Chemotherapy induces tumor immune evasion by upregulation of programmed cell death ligand 1 expression in bone marrow stromal cells

Programmed cell death ligand 1 (PD‐L1) is a negative regulator of the immune response that enables tumor cells to escape T‐cell immunity. Although PD‐L1 expression in cancer cells has been extensively studied, the expression of PD‐L1 in stromal cells and its clinical significance remain largely unknown. Here, we show that bone marrow stromal cells express a low level of PD‐L1 and that this molecule is significantly upregulated by key drugs used in the treatment of lymphoma at clinically relevant concentrations. Mechanistically, chemotherapeutic drugs induce PD‐L1 expression in stromal cells through upregulation of granulocyte macrophage colony‐stimulating factor and activation of the extracellular signal‐regulated kinase (ERK) 1/2 signaling pathway. Suppression of ERK by a chemical inhibitor or genetic silencing of ERK2 expression prevents drug‐induced PD‐L1 expression. PD‐L1 expression is upregulated in the bone marrow stromal cells of mice treated with doxorubicin and in drug‐treated bone marrow specimens from lymphoma patients. Drug‐induced PD‐L1 expression in stromal cells can cause significant impairment of T‐cell functions. Overall, our study reveals a previously unrecognized mechanism by which chemotherapy induces tumor immune evasion by upregulation of PD‐L1 in bone marrow stromal cells, and provides new evidence for the combination of chemotherapy and anti‐PD‐L1/PD‐1 as an effective strategy for treatment of lymphoma and other cancers.
Robust visual tracking via occlusion detection based on staple algorithm

In this paper, we propose a novel algorithm to handle occlusions for robust visual object tracking. For a robust and adaptive tracking algorithm, it is critical to distinguish occlusions from target appearance variations. Occlusions are introduced in the 3-D scene to 2-D plane projection process and usually correspond to interactions between the target and the background. In our algorithm, we exploit temporal and spatial context information to identify the occurrence of occlusions. We implement the proposed occlusion detection scheme based on Staple algorithm [2], which is an efficient and accurate tracking algorithm. Besides the tracker to estimate the state of the target, we also investigate the background patches around the target with trackers to monitor their interaction with the target. If occlusions are detected, the current target model stops updating. Comprehensive experiments on benchmark OTB-2013 show that our strategy can detect occlusions correctly and therefore enable the proposed tracking algorithm robust to occlusions.
DNA stable‐isotope probing identifies uncultivated members of Pseudonocardia associated with biodegradation of pyrene in agricultural soil

ABSTRACT Identifying functional microorganisms involved in the degradation of high‐molecular‐mass polycyclic aromatic hydrocarbons (HMM‐PAHs) in agricultural soil environments could assist in developing bioremediation strategies for soil PAH contamination. Active populations of HMM‐PAH degraders in agricultural soils are currently poorly understood. In this study, we identified aerobic pyrene‐degrading bacteria in agricultural and industrial soils by [13C]pyrene incubations followed by DNA stable‐isotope probing and high‐throughput sequencing. More than 80% of pyrene was degraded during an incubation time of 35 days in both soils, with slower mineralization rates observed in agricultural soil compared with industrial soil. Members of the Pseudonocardia genus, not previously implicated in pyrene degradation, were the dominant pyrene‐degrading population in agricultural soil; their relative abundance increased by three orders of magnitude. In industrial soil, Arthrobacter sp. appeared as the major pyrene degraders, while Pseudonocardia was not detectable. Mycobacterium, a group of well‐known pyrene degraders, was found to be active in pyrene degradation in both soils. These results highlight the role of uncultivated members of Pseudonocardia in natural PAH biodegradation processes and expand our understanding of the metabolic potential of uncultivated microorganisms for bioremediation applications in agricultural soils.