Miracle-dz/UniFAR-FTUs huggingface dataset:
Ex vivo optical metabolic measurements from cultured tissue reflect in vivo tissue status

Abstract. Optical measurements of metabolism are ideally acquired in vivo; however, intravital measurements are often impractical. Accurate ex vivo assessments would greatly broaden the applicability of optical measurements of metabolism. We investigate the use of live tissue culture experiments to serve as a surrogate for in vivo metabolic measurements. To validate this approach, NADH and FAD fluorescence intensity and lifetime images were acquired with a two-photon microscope from hamster cheek pouch epithelia in vivo, from biopsies maintained in live tissue culture up to 48 h, and from flash-frozen and thawed biopsies. We found that the optical redox ratio (fluorescence intensity of NADH/FAD) of the cultured biopsy was statistically identical to the in vivo measurement until 24 h, while the redox ratio of the frozen-thawed samples decreased by 15% (p<0.01). The NADH mean fluorescence lifetime (τm) remained unchanged (p>0.05) during the first 8 h of tissue culture, while the NADH τm of frozen-thawed samples increased by 13% (p<0.001). Cellular morphology did not significantly change between in vivo, cultured, and frozen-thawed tissues (p>0.05). All results were consistent across multiple depth layers in this stratified squamous epithelial tissue. Histological markers for proliferation and apoptosis also confirm the viability of tissues maintained in culture. This study suggests that short-term ex vivo tissue culture may be more appropriate than frozen-thawed tissue for optical metabolic and morphologic measurements that approximate in vivo status.
EEG-signals based cognitive workload detection of vehicle driver using deep learning

Vehicle driver's ability to maintain optimal performance and attention is essential to ensure the safety of the traffic. Electroencephalography (EEG) signals have been proven to be effective in evaluating human's cognitive state under specific tasks. In this paper, we propose the use of deep learning on EEG signals to detect the driver's cognitive workload under high and low workload tasks. Data used in this research are collected throughout multiple driving sessions conducted on a high fidelity driving simulator. Preliminary experimental results conducted on only 4 channels of EEG show that the proposed system is capable of accurately detecting the cognitive workload of the driver with an enormous potential for improvement.
Client and practitioner perspectives on the screening mammography experience

Mammography can be painful and unpleasant, but effective interventions to improve the experience remain scarce. As a first step towards more effective interventions, we aimed to achieve a thorough, contemporary understanding of thoughts, feelings and behaviours which affect and arise from mammography experiences. Research and professional experience suggest that the interaction between client and practitioner may be paramount in determining the quality of a client's experience. Therefore, this study aimed to capture the perspectives of clients and mammography staff from UK breast screening programmes. Thematic analysis of semi‐structured qualitative in‐depth interviews with 22 clients and 18 staff revealed that clients had positive attitudes to breast screening and mostly low knowledge about potential harms. Staff data indicated that some women attend for breast screening under pressure from others. Pain and coping with it were prominent themes, with wide variations in pain experiences. Clients recognised differences in mammographers’ abilities to put them at ease. Staff difficulties included empowering clients within the confines of a taxing technique, and maintaining compassionate care when under strain. Future intervention development should focus on the information and support needs of women prior to the appointment and on effectively training and supporting mammographers to deal with challenging encounters.
A novel task recommendation model for mobile crowdsourcing systems

With the developments of sensors in mobile devices, mobile crowdsourcing systems are attracting more and more attention. However, how to recommend user-preferred and trustful tasks for users is an important issue to improve efficiency of mobile crowdsourcing systems. This paper proposes a novel task recommendation model for mobile crowdsourcing systems. Considering both user similarity and task similarity, the recommendation probabilities of tasks are derived. Based on dwell-time, the latent recommendation probability of tasks can be predicted. In addition, the trust of tasks is obtained based on their reputations and participation frequencies. Finally, we perform comprehensive experiments towards the Amazon metadata and YOOCHOOSE datasets to verify the effectiveness of the proposed recommendation model.
Chemogenomic Active Learning's Domain of Applicability on Small, Sparse qHTS Matrices: A Study Using Cytochrome P450 and Nuclear Hormone Receptor Families

Computational models for predicting the activity of small molecules against targets are now routinely developed and used in academia and industry, partially due to public bioactivity databases. While models based on bigger datasets are the trend, recent studies such as chemogenomic active learning have shown that only a fraction of data is needed for effective models in many cases. In this article, the chemogenomic active learning method is discussed and used to newly analyze public databases containing nuclear hormone receptor and cytochrome P450 enzyme family bioactivity. In addition to existing results on kinases and G‐protein coupled receptors, results here demonstrate the active learning methodology's effectiveness on extracting informative ligand–target pairs in sparse data scenarios. Experiments to assess the domain of the applicability demonstrate the influence of ligand profiles of similar targets within the family.
In vitro proliferation and osteogenic differentiation of human dental pulp stem cells in injectable thermo-sensitive chitosan/β-glycerophosphate/hydroxyapatite hydrogel

Injectable thermo-sensitive hydrogels have a potential application in bone tissue engineering for their sensitivities and minimal invasive properties. Human dental pulp stem cells have been considered a promising tool for tissue reconstruction. The objective of this study was to investigate the proliferation and osteogenic differentiation of dental pulp stem cells in injectable thermo-sensitive chitosan/β-glycerophosphate/hydroxyapatite hydrogel in vitro. The chitosan /β-glycerophosphate hydrogel and chitosan/β-glycerophosphate/hydroxyapatite hydrogel were prepared using the sol-gel method. The injectability of chitosan /β-glycerophosphate hydrogel and chitosan/β-glycerophosphate/hydroxyapatite hydrogel was measured using a commercial disposable syringe. Scanning electron microscopy was used to observe the inner structure of hydrogels. Then dental pulp stem cells were seeded in chitosan /β-glycerophosphate hydrogel and chitosan/β-glycerophosphate/hydroxyapatite hydrogel, respectively. The growth of dental pulp stem cells was periodically observed under an inverted microscope. The proliferation of dental pulp stem cells was detected by using an Alamar Blue kit, while cell apoptosis was determined by using a Live/Dead Viability/Cytotoxicity kit. The osteogenic differentiations of dental pulp stem cells in chitosan /β-glycerophosphate hydrogel and chitosan/β-glycerophosphate/hydroxyapatite hydrogel were evaluated by alkaline phosphatase activity assay and mRNA expression of osteogenesis gene for 21 days in osteogenic medium. The results indicated that there was no significant difference between chitosan /β-glycerophosphate hydrogel and chitosan/β-glycerophosphate/hydroxyapatite hydrogel in injectability. Cells within the chitosan/β-glycerophosphate/hydroxyapatite hydrogel displayed a typical adherent cell morphology and rapid proliferation with high cellular viability after 14 days of culture. Dental pulp stem cells seeded in chitosan/β-glycerophosphate/hydroxyapatite hydrogels had a higher alkaline phosphatase activity and better up-regulation of gene expression levels of Runx-2, Collagen I, alkaline phosphatase and osteocalcin than in chitosan /β-glycerophosphate hydrogels after osteogenic differentiation. These results demonstrated that the chitosan/β-glycerophosphate/hydroxyapatite hydrogel had excellent cellular compatibility and the superiority in promoting dental pulp stem cells osteogenic differentiation in vitro, showing that the combination of dental pulp stem cells and chitosan/β-glycerophosphate/hydroxyapatite hydrogel has the potential to be used for bone tissue engineering.
Dynamic objects detection and tracking for a laser scanner and camera system

Dynamic object detection and tracking from complex scenes is a challenge in the field of robot vision. In this paper, we exploit a laser scanner associated with a camera to achieve the map reconstruction, removing and tracking dynamic objects. Laser-based and image-based dynamic detection method are proposed, and their quality is analyzed respectively. Efficiency and accuracy are enhanced by a hybrid method associated 3D and 2D information. A 3D Gaussian mixture probability hypothesis density-based (GM-PHD) filter is designed to track the motion trajectories of multiple dynamic objects. The experimental result conducted on KITTI public dataset show the effectiveness of our method.
Buyer Uncertainty About Seller Capacity: Causes, Consequences, and a Partial Solution

Employers in an online labor market often pursue workers with little capacity to take on more work. The pursuit of low-capacity workers is consequential, as these workers are more likely to reject employer inquires, causing a reduction in the probability that a job opening is ultimately filled. In an attempt to shift more employer attention to workers with greater capacity, the market-designing platform examined in this paper introduced a new signaling feature into the market. It was effective, in that when a worker signaled having high capacity, he or she received more invitations from employers, rejected a smaller fraction of those invitations, quoted lower prices to do the work, and was more likely to be hired. A back-of-the-envelope calculation suggests the signaling feature alone could increase market surplus by as much as 6%, both by increasing the number of matches formed and by helping to allocate projects to workers with lower costs. This paper was accepted by Lorin Hitt, information systems.
An overview of on-chip cache coherence protocols

Cache coherence protocols have significant impact on the performance of distributed and centralized shared-memory of a multiprocessor, and they are required for maintaining data consistency in a chip-multiprocessor system (CMP). Thus, cache protocols play a major role in improving the performance of multiprocessor systems. Specifically, an efficient cache coherence protocol should ensure the updating of processor data, broadcasting valid data other processors and main memory to prevent the main memory or other processors from loading invalid values. To address this issue of efficiency in maintaining cache coherency, several contribution, such as using invalidation-based protocols with a write through cache coherence, have been made over the past years. This paper presents an overview of emerging cache coherence protocols which aim at improving the performance of CMPs. Furthermore, an example of using an invalidation-based protocol with a write through for solving cache's coherency is provided.
Cell-intrinsic, Bmal1-dependent Circadian Regulation of Temozolomide Sensitivity in Glioblastoma

The safety and efficacy of chemotherapeutics can vary as a function of the time of their delivery during the day. This study aimed to improve the treatment of glioblastoma (GBM), the most common brain cancer, by testing whether the efficacy of the DNA alkylator temozolomide (TMZ) varies with the time of its administration. We found cell-intrinsic, daily rhythms in both human and mouse GBM cells. Circadian time of treatment affected TMZ sensitivity of murine GBM tumor cells in vitro. The maximum TMZ-induced DNA damage response, activation of apoptosis, and growth inhibition occurred near the daily peak in expression of the core clock gene Bmal1. Deletion of Bmal1 (Arntl) abolished circadian rhythms in gene expression and TMZ-induced activation of apoptosis and growth inhibition. These data indicate that tumor cell-intrinsic circadian rhythms are common to GBM tumors and can regulate TMZ cytotoxicity. Optimization of GBM treatment by timing TMZ administration to daily rhythms should be evaluated in prospective clinical trials.
Hepatitis B synthetic immunogen comprised of nucleocapsid T-cell sites and an envelope B-cell epitope.

Previous studies located T-cell recognition of the nucleocapsid of the hepatitis B virus (HBcAg) to residues 120-140 in mice bearing the H-2s or H-2b haplotypes. Herein, we demonstrate that B10.S (H-2s) and B10 (H-2b) H-2 congenic strains recognize distinct T-cell sites within the p120-140 (a synthetic peptide corresponding to residues 120-140 of HBcAg) sequence defined by p120-131 and p129-140, respectively. Peptide p120-131 stimulates B10.S HBcAg-primed T cells, and reciprocally p120-131-primed T cells recognize HBcAg. Similarly, the p129-140 sequence is a T-cell recognition site relevant to the native HBcAg in the B10 strain. It is also shown that these 12-residue peptides efficiently prime T-helper cells, which are capable of eliciting antibody production to HBcAg in vivo. These observations prompted us to examine the ability of the HBcAg-specific p120-140 sequence to function as a T-cell carrier moiety as a component of a totally synthetic hepatitis B vaccine. For this purpose a synthetic B-cell epitope from the pre-S(2) region (p133-140) of the viral envelope was chosen because this sequence represents a dominant antibody-binding site of the envelope. Immunization of B10.S and B10 strains with the synthetic composite peptide c120-140-(133-140) elicited anti-peptide antibody production, which was crossreactive with the native viral envelope. Furthermore, c120-140-(133-140) immunization primed p120-131-specific T cells in the B10.S strain and p129-140-specific T cells in the B10 strain, which recognized HBcAg and provided T-helper cell function for anti-envelope antibody production in vivo. These results demonstrate the feasibility of constructing complex synthetic immunogens that represent multiple proteins of a pathogen and are capable of engaging both T and B cells relevant to the native antigens.
Distribution Matching with the Bhattacharyya Similarity: A Bound Optimization Framework

We present efficient graph cut algorithms for three problems: (1) finding a region in an image, so that the histogram (or distribution) of an image feature within the region most closely matches a given model; (2) co-segmentation of image pairs and (3) interactive image segmentation with a user-provided bounding box. Each algorithm seeks the optimum of a global cost function based on the Bhattacharyya measure, a convenient alternative to other matching measures such as the Kullback-Leibler divergence. Our functionals are not directly amenable to graph cut optimization as they contain non-linear functions of fractional terms, which make the ensuing optimization problems challenging. We first derive a family of parametric bounds of the Bhattacharyya measure by introducing an auxiliary labeling. Then, we show that these bounds are auxiliary functions of the Bhattacharyya measure, a result which allows us to solve each problem efficiently via graph cuts. We show that the proposed optimization procedures converge within very few graph cut iterations. Comprehensive and various experiments, including quantitative and comparative evaluations over two databases, demonstrate the advantages of the proposed algorithms over related works in regard to optimality, computational load, accuracy and flexibility.
Involvement of Cholinergic Dysfunction and Oxidative Damage in the Effects of Simulated Weightlessness on Learning and Memory in Rats

The present study aimed to determine how the learning and memory gradually change with the prolonged hindlimb unloading (HU) treatment in rats. Different HU durations (7 d, 14 d, 21 d, and 28 d) in Sprague-Dawley (SD) rats were implemented. Cognitive function was assessed using the Morris water maze (MWM) and the shuttle box test. Additionally, parameters about cholinergic activity and oxidative stress were tested. Results showed that longer-than-14 d HU led to the inferior performances in the behavioral tasks. Besides, acetylcholine esterase (AChE) activity, malondialdehyde (MDA) level in brain, reactive oxygen species (ROS), and 8-hydroxy-2-deoxyguanosine (8-OHdG) concentrations of HU rats were significantly increased. Furthermore, choline acetyltransferase (ChAT), superoxide dismutase (SOD), and catalase (CAT) activity in brain were notably attenuated. Most of these effects were more pronounced after longer exposure (21 d and 28 d) to HU, although some indicators had their own characteristics of change. These results indicate that cholinergic dysfunction and oxidative damage were involved in the learning and memory impairments induced by longer-than-14 d HU. Moreover, the negative effects of HU tend to be augmented as the HU duration becomes longer. The results may be helpful to present possible biochemical targets for countermeasures development regarding the memory deficits under extreme environmental conditions.
Thermal and Electrical Transport Properties of Spark Plasma‐Sintered HfB2 and ZrB2 Ceramics

The thermal and electrical transport properties of various spark plasma-sintered HfB2- and ZrB2-based polycrystalline ceramics were investigated experimentally over the 298–700 K temperature range. Measurements of thermal diffusivity, electrical resistivity, and Hall coefficient are reported, as well as the derived properties of thermal conductivity, charge carrier density, and charge carrier mobility. Hall coefficients were negative confirming electrons as the dominant charge carrier, with carrier densities and mobilities in the 3–5 × 1021 cm−3 and 100–250 cm2·(V·s)−1 ranges, respectively. Electrical resistivities were lower, and temperature coefficients of resistivity higher, than those typically reported for HfB2 and ZrB2 materials manufactured by the conventional hot pressing. A Wiedemann–Franz analysis confirms the dominance of electronic contributions to heat transport. The thermal conductivity was found to decrease with increasing temperature for all materials. Results are discussed in terms of sample morphology and compared with data previously reported in the scientific literature.
A broadband pattern reconfigurable patch antenna for 60GHz wireless communication

60GHz wireless communication technology has become one of the most potential technologies for the future wireless communication because of its high speed and high bandwidth free spectrum resources. In this paper, a broadband pattern reconfigurable stacked patch antenna with IEEE 802.11ad standard (WiGig) is designed. The pattern reconfigurable antenna consists of a substrate integrated cavity-backed slot coupled driven patch antenna and a parasitic layer placed above it. The surface of the parasitic layer has a grid of 9 square-shaped patches. The pattern reconfigurability property is realized by connecting the nine parasitic patches to change the geometry of the parasitic surface, which in turn changes the current distribution on the parasitic layer. Simulation results show that the antenna is aimed to steer nine directions in the semisphere space over the 57–64GHz frequency band. The beam shift has a stable radiation pattern and the realized gain is above 8.1dB in each mode of operation, which meets the requirements of 60GHz wireless communication system.
The prevalence of depression in general hospital inpatients: a systematic review and meta-analysis of interview-based studies

Abstract Background Comorbid depression in the medically ill is clinically important. Admission to a general hospital offers an opportunity to identify and initiate treatment for depression. However, we first need to know how common depression is in general hospital inpatients. We aimed to address this question by systematically reviewing the relevant literature. Methods We reviewed published prevalence studies in any language which had used diagnostic interviews of general hospital inpatients and met basic methodological quality criteria. We focussed on interview-based studies in order to estimate the proportion of patients with a diagnosis of depressive illness. Results Of 158 relevant articles, 65 (41%) describing 60 separate studies met our inclusion criteria. The 31 studies that focussed on general medical and surgical inpatients reported prevalence estimates ranging from 5% to 34%. There was substantial, highly statistically significant, heterogeneity between studies which was not materially explained by the covariates we were able to consider. The average of the reported prevalences was 12% (95% CI 10–15), with a 95% prediction interval of 4–32%. The remaining 29 studies, of a variety of specific clinical populations, are described. Conclusions The available evidence suggests a likely prevalence high enough to make it worthwhile screening hospital inpatients for depression and initiating treatment where appropriate. Further, higher quality, research is needed to clarify the prevalence of depression in specific settings and to further explore the reasons for the observed heterogeneity in estimates.
Cepharanthine Prevents Estrogen Deficiency-Induced Bone Loss by Inhibiting Bone Resorption

Osteoporosis is a common health problem worldwide caused by an imbalance of bone formation vs. bone resorption. However, current therapeutic approaches aimed at enhancing bone formation or suppressing bone resorption still have some limitations. In this study, we demonstrated for the first time that cepharanthine (CEP, derived from Stephania cepharantha Hayata) exerted a protective effect on estrogen deficiency-induced bone loss. This protective effect was confirmed to be achieved through inhibition of bone resorption in vivo, rather than through enhancement of bone formation in vivo. Furthermore, the in vitro study revealed that CEP attenuated receptor activator of nuclear factor κB ligand (RANKL)-induced osteoclast formation, and suppressed bone resorption by impairing the c-Jun N-terminal kinase (JNK) and phosphatidylinositol 3-kinase (PI3K)-AKT signaling pathways. The inhibitory effect of CEP could be partly reversed by treatment with anisomycin (a JNK and p38 agonist) and/or SC79 (an AKT agonist) in vitro. Our results thus indicated that CEP could prevent estrogen deficiency-induced bone loss by inhibiting osteoclastogenesis. Hence, CEP might be a novel therapeutic agent for anti-osteoporosis therapy.
Flow-Based Influence Graph Visual Summarization

Visually mining a large influence graph is appealing yet challenging. Existing summarization methods enhance the visualization with blocked views, but have adverse effect on the latent influence structure. How can we visually summarize a large graph to maximize influence flows? In particular, how can we illustrate the impact of an individual node through the summarization? Can we maintain the appealing graph metaphor while preserving both the overall influence pattern and fine readability? To answer these questions, we first formally define the influence graph summarization problem. Second, we propose an end-to-end framework to solve the new problem. Last, we report our experiment results. Evidences demonstrate that our framework can effectively approximate the proposed influence graph summarization objective while outperforming previous methods in a typical scenario of visually mining academic citation networks.