Miracle-dz/UniFAR-FTUs huggingface dataset:
A Versatile Method for Depth Data Error Estimation in RGB-D Sensors

We propose a versatile method for estimating the RMS error of depth data provided by generic 3D sensors with the capability of generating RGB and depth (D) data of the scene, i.e., the ones based on techniques such as structured light, time of flight and stereo. A common checkerboard is used, the corners are detected and two point clouds are created, one with the real coordinates of the pattern corners and one with the corner coordinates given by the device. After a registration of these two clouds, the RMS error is computed. Then, using curve fittings methods, an equation is obtained that generalizes the RMS error as a function of the distance between the sensor and the checkerboard pattern. The depth errors estimated by our method are compared to those estimated by state-of-the-art approaches, validating its accuracy and utility. This method can be used to rapidly estimate the quality of RGB-D sensors, facilitating robotics applications as SLAM and object recognition.
Epidemiological science and cancer control

Epidemiological methods are essential for the discovery of cancer risks and prognostic factors as well as for the evaluation of cancer prevention measures. In this review, we discuss epidemiological surveillance procedures for data collection and processing to guide and evaluate the consequences of anticancer efforts for populations, assess the identification of cancer risk factors, examine barriers to cancer screening and recommended rules for early diagnosis programs. Epidemiological studies have shown that hindrances to cancer information assessment are currently encountered in developing countries. Known cancer risk factors include social determinants, lifestyle factors, occupational exposures, infectious agents, and genetic and epigenetic alterations. Challenges remain in studying the effectiveness of cancer screening; screening can have detrimental effects, and few cancers clearly benefit from screening. Currently, epidemiology faces the challenge of dealing with distinct levels of data, including factors related to social status, lifestyle and genetics, to reconstruct the causal traits of cancer. Additionally, translating epidemiological knowledge into cancer control demands more implementation studies in the population.
Micro-/nano-topography of selective laser melting titanium enhances adhesion and proliferation and regulates adhesion-related gene expressions of human gingival fibroblasts and human gingival epithelial cells

Background Selective laser melting (SLM) titanium is an ideal option to manufacture customized implants with suitable surface modification to improve its bioactivity. The peri-implant soft tissues form a protective tissue barrier for the underlying osseointegration. Therefore, original microrough SLM surfaces should be treated for favorable attachment of surrounding soft tissues. Material and methods In this study, anodic oxidation (AO) was applied on the microrough SLM titanium substrate to form TiO2 nanotube arrays. After that, calcium phosphate (CaP) nanoparticles were embedded into the nanotubes or the interval of nanotubes by electrochemical deposition (AOC). These two samples were compared to untreated (SLM) samples and accepted mechanically polished (MP) SLM titanium samples. Scanning electron microscopy, energy dispersive spectrometry, X-ray diffraction, surface roughness, and water contact angle measurements were used for surface characterization. The primary human gingival epithelial cells (HGECs) and human gingival fibroblasts (HGFs) were cultured for cell assays to determine adhesion, proliferation, and adhesion-related gene expressions. Results For HGECs, AOC samples showed significantly higher adhesion, proliferation, and adhesion-related gene expressions than AO and SLM samples (P<0.05) and similar exceptional ability in above aspects to MP samples. At the same time, AOC samples showed the highest adhesion, proliferation, and adhesion-related gene expressions for HGFs (P<0.05). Conclusion By comparison between each sample, we could confirm that both anodic oxidation and CaP nanoparticles had improved bioactivity, and their combined utilization may likely be superior to mechanical polishing, which is most commonly used and widely accepted. Our results indicated that creating appropriate micro-/nano-topographies can be an effective method to affect cell behavior and increase the stability of the peri-implant mucosal barrier on SLM titanium surfaces, which contributes to its application in dental and other biomedical implants.
Does Chronic Ankle Instability Influence Knee Biomechanics of Females during Inverted Surface Landings?

Abstract The primary purpose of the study was to determine whether atypical knee biomechanics are exhibited during landing on an inverted surface. A seven-camera motion analysis system and two force plates were used to collect lower extremity biomechanics from two groups of female participants: 21 subjects with chronic ankle instability (CAI) and 21 with pair-matched controls. Subjects performed ten landings onto inverted and flat platforms on the CAI/matched and non-test limbs, respectively. Knee and ankle joint angles, joint angular displacements, joint moments and eccentric work were calculated during the landing phase and/or at the initial contact. Paired t-tests were used to compare between-group differences (p<0.05). We observed that CAI group displayed a significantly increased knee flexion angle, knee flexion displacement, peak knee extension moment and internal rotation moment, and eccentric work in the sagittal plane, possibly due to altered ankle biomechanics. Participants with CAI employed some compensatory strategy to improve their ankle and postural stability during landing onto the tilted surface. The increased knee extension and internal rotation moments of CAI participants could potentially result in a greater ACL loading. In future studies, it may be worthwhile to measure or estimate the ACL loading to confirm whether CAI could relate to the mechanism of ACL injury.
Comparison of culture, microscopic smear and molecular methods in diagnosis of tuberculosis

ABSTRACT Objectives Tuberculosis (TB) is a public health problem worldwide, with the highest mortality . The development of nucleic acid-based tests for detection of Mycobacterium tuberculosis complex (MTBC) has significantly increased sensitivity compared to conventional smear microscopy and provides results within a matter of hours compared to weeks for solid culture, which is the current gold standart. The aim of this study was to compare the culture, microscopic smear and molecular method in the diagnosis of TB . Material and methods Seven hundred ninety specimens belonging to clinically suspected cases of TB were studied retrospectively. The specimens were grouped as respiratory and non-respiratory and the groups were compared for mycobacterial detection assays. The culture and the molecular diagnostic GeneXpert MTB/RIF (GX) assay method were compared. Results When culture was used as the reference standart, 32 (4.05%) specimens were positive for MTBC. Of the 32 culture positive clinical specimens 24 (3.03%) were respiratory and 8 (1.01%) were non-respiratory specimens. All 24 of the 24 respiratory specimens were positive by the GX test, Seven of the eight non-respiratory specimens positive for culture were positive by GX assay. Five of the seven hundred fifty-eight samples of culture negative were positive with GX assay. Sensitivity and specificity of GX were found to be 96.8 % and 99.3 %, respectively. Concluisons Molecular methods to acquire time in diagnosis as well as the increase in linearity gives a different perspective to the diagnosis of tuberculosis. The GX assay has a diagnostic utility for rapid diagnosis of TB.
Multi-domain Longitudinal Modeling: An Application to the International Index of Erectile Function

Individual domains of multi-domain, patient-reported outcome instruments are typically analyzed independently, without considering inherent interdependency. The authors assessed correlations across time (longitudinal) and across domains of a multi-domain instrument, simultaneously, in a single, unified, and cohesive integrated model. International Index of Erectile Function (IIEF) data from a trial of sildenafil in erectile dysfunction were used. For the multi-domain longitudinal modeling, covariance of response was constructed using (1) the Kronecker product of an unstructured covariance matrix to model across domains, with an unstructured covariance matrix to model across time, and (2) a completely general, unstructured covariance matrix. Treatment effects for all IIEF domain scores calculated using individual or multi-domain modeling were similar, reflecting the robust application of the integrated model to these data. In conclusion, modeling correlations simultaneously across domains and across time more rigorously address the natural interrelationship between domains and can provide a more accurate representation of treatment effects.
CD44 expression in pleomorphic adenoma, carcinoma ex pleomorphic adenoma and their adjacent normal salivary glands

Background: CD44 is a transmembranous proteoglycan, with a main role of cell adhesion to other cells and to extracellular matrix involved in the preservation of three-dimensional structure of organs. Pleomorphic adenoma (PA) is a common benign salivary gland tumor, composed of myoepithelial and ductal components. Carcinoma ex-PA (CXPA) is malignant transformation of the epithelial elements in PA. The aim of this study was to evaluate CD44 expression by immunohistochemistry in these two tumors and normal salivary gland near these tumors. Materials and Methods: In this cross-sectional immunohistochemical study, 40 paraffin blocks (formalin fixed, paraffin embedded) with thirty belonging to PA and ten blocks of CXPA and 18 paraffinized blocks of normal salivary glands' tissue adjacent to tumoral tissue (13 in the vicinity of PA and 5 in the vicinity of CXPA) were selected. Immunohistochemical expression of CD44 was observed and compared with each other. For data analysis, we used Chi-square, Kruskal–Wallis, and Mann–Whitney tests and the quantity of P values was considered 0.05. Results: There was a significant difference in CD44 expression frequency between PA, CXPA, and normal salivary glands with higher expression noted in CXPA. Furthermore, expression frequency of CD44 in adjacent normal salivary gland of CXPA was significantly higher than PA. There was no significant difference in the expression of CD44 with respect to lymph node metastasis. Conclusion: Higher expression of CD44 in CXPA might illustrate CD44's role in malignant transformation of PA.
A critical role of the transient receptor potential melastatin 2 channel in a positive feedback mechanism for reactive oxygen species‐induced delayed cell death

Transient receptor potential melastatin 2 (TRPM2) channel activation by reactive oxygen species (ROS) plays a critical role in delayed neuronal cell death, responsible for postischemia brain damage via altering intracellular Zn2+ homeostasis, but a mechanistic understanding is still lacking. Here, we showed that H2O2 induced neuroblastoma SH‐SY5Y cell death with a significant delay, dependently of the TRPM2 channel and increased [Zn2+]i, and therefore used this cell model to investigate the mechanisms underlying ROS‐induced TRPM2‐mediated delayed cell death. H2O2 increased concentration‐dependently the [Zn2+]i and caused lysosomal dysfunction and Zn2+ loss and, furthermore, mitochondrial Zn2+ accumulation, fragmentation, and ROS generation. Such effects were suppressed by preventing poly(adenosine diphosphate ribose, ADPR) polymerase‐1‐dependent TRPM2 channel activation with PJ34 and 3,3′,5,5′‐tetra‐tert‐butyldiphenoquinone, inhibiting the TRPM2 channel with 2‐aminoethoxydiphenyl borate (2‐APB) and N‐(p‐amylcinnamoyl)anthranilic acid, or chelating Zn2+ with N,N,N,N‐tetrakis(2‐pyridylmethyl)‐ethylenediamine (TPEN). Bafilomycin‐induced lysosomal dysfunction also resulted in mitochondrial Zn2+ accumulation, fragmentation, and ROS generation that were inhibited by PJ34 or 2‐APB, suggesting that these mitochondrial events are TRPM2 dependent and sequela of lysosomal dysfunction. Mitochondrial TRPM2 expression was detected and exposure to ADPR‐induced Zn2+ uptake in isolated mitochondria, which was prevented by TPEN. H2O2‐induced delayed cell death was inhibited by apocynin and diphenyleneiodonium, nicotinamide adenine dinucleotide phosphate hydrogen (NADPH) oxidase (NOX) inhibitors, GKT137831, an NOX1/4‐specific inhibitor, or Gö6983, a protein kinase C (PKC) inhibitor. Moreover, inhibition of PKC/NOX prevented H2O2‐induced ROS generation, lysosomal dysfunction and Zn2+ release, and mitochondrial Zn2+ accumulation, fragmentation and ROS generation. Collectively, these results support a critical role for the TRPM2 channel in coupling PKC/NOX‐mediated ROS generation, lysosomal Zn2+ release, and mitochondrial Zn2+ accumulation, and ROS generation to form a vicious positive feedback signaling mechanism for ROS‐induced delayed cell death.
SECS: Efficient Deep Stream Processing via Class Skew Dichotomy

Despite that accelerating convolutional neural network (CNN) receives an increasing research focus, the save on resource consumption always comes with a decrease in accuracy. To both increase accuracy and decrease resource consumption, we explore an environment information, called class skew, which is easily available and exists widely in daily life. Since the class skew may switch as time goes, we bring up probability layer to utilize class skew without any overhead during the runtime. Further, we observe class skew dichotomy that some class skew may appear frequently in the future, called hot class skew, and others will never appear again or appear seldom, called cold class skew. Inspired by techniques from source code optimization, two modes, i.e., interpretation and compilation, are proposed. The interpretation mode pursues efficient adaption during runtime for cold class skew and the compilation mode aggressively optimize on hot ones for more efficient deployment in the future. Aggressive optimization is processed by class-specific pruning and provides extra benefit. Finally, we design a systematic framework, SECS, to dynamically detect class skew, processing interpretation and compilation, as well as select the most accurate architectures under the runtime resource budget. Extensive evaluations show that SECS can realize end-to-end classification speedups by a factor of 3x to 11x relative to state-of-the-art convolutional neural networks, at a higher accuracy.
Benchmarking the Study Initiation Process

The study start-up phase of a trial is an area that pharmaceutical and biotechnology companies are focusing on in order to reduce delays and improve efficiency. To better understand and examine metrics within study start-up, the Tufts Center for the Study of Drug Development, in collaboration with 11 pharmaceutical and biotechnology companies, examined a comprehensive set of metrics and analyzed study data from 105 global clinical trials. The results indicate that the early stages of the site initiation process are areas that accounted for the majority of cycle time. An examination of cycle time to the first patient in by therapeutic area also reveals variation. Variations in cycle time to the first patient occur by site type as well as by region. Academic institutions and government-funded sites were longest to the first patient in, while physician practices were fastest.
A Meta-Analysis of the Effect of Multisession Transcranial Direct Current Stimulation on Cognition in Dementia and Mild Cognitive Impairment

There have been increasing efforts to investigate the effects of neuromodulation techniques, such as transcranial direct current stimulation (tDCS), on cognitive impairment in dementia and related conditions. In this systematic review and meta-analysis, we assessed the efficacy of multisession anodal tDCS compared with sham stimulation for improving global cognition and specific cognitive domains in both Alzheimer’s disease and mild cognitive impairment. Eight articles meeting the criteria for inclusion in the meta-analysis were selected. Five studies used the Mini-Mental State Examination to examine mild cognitive impairment and dementia. In a fixed-effect model, there was a mean difference in the change score of −0.13 points. Three trials for dementia using the Alzheimer’s Disease Assessment Scale–Cognition showed a mean difference of −0.53 points. At present, there is a lack of clear evidence concerning the efficacy of multisession anodal tDCS due to the small number of studies and different measures used. This underscores the need for further investigations using larger samples and common outcome measures.
Effect of a Health Coach Intervention for the Management of Individuals With Type 2 Diabetes Mellitus in China: A Pragmatic Cluster Randomized Controlled Trial

Aim: To determine the effect of a health coach intervention for the management of glycemic control, as well as physiological, psychological and self-care outcomes of patients with type 2 diabetes mellitus (T2DM), compared with usual care. Methods: This pragmatic cluster RCT was conducted in the Fengtai district of Beijing from August 2011 to December 2013. Forty-one community health stations (CHSs) were cluster randomized (stratified geographically, 1:1 ratio) and eligible, randomly selected T2DM patients were sequentially contacted by CHSs. Control participants received usual care according to the Chinese Guideline for Diabetes Prevention and Management. Intervention participants received 18-months of health coaching based on principles of Motivational Interviewing (MI) plus usual care. Medical and pathology fees were waived for both groups. Outcome assessment was performed at baseline, 6, 12, and 18-months. The primary outcome was glycated hemoglobin (HbA1c); secondary outcomes encompassed a suite of physiological, psychological and self-care measures. Results: No differential treatment effect was found at 18-months for HbA1c (adj. difference −0.07, 95% CI −0.53 to 0.39, p = 0.769) or any specified secondary outcomes. Interestingly, both groups displayed a statistically and clinically significant within-group improvement of the same magnitude at 18-months for HbA1c (intervention: mean change −3.65, 95% CI −3.92 to −3.37; control: mean change −3.38, 95% CI −3.67 to −3.08). Conclusions: The lack of differential treatment effects observed indicate that it may be premature to recommend the routine delivery of health coach interventions based on MI principles for the management of T2DM in China. However, the large, comparable within-group improvement in mean HbA1c promotes the establishment of free, regular clinical health assessments for individuals with T2DM in China. Trial Registration: ISRCTN registry - ISRCTN01010526 (https://doi.org/10.1186/ISRCTN01010526)
Towards human-like artificial intelligence using StarCraft 2

On our path towards artificial general intelligence, video games have become excellent tools for research. Reinforcement learning (RL) algorithms are particularly successful in this domain, with the added benefit of having fairly well established biological foundations. To improve how artificial intelligence research and the cognitive sciences can inform each other, we argue the StarCraft II Learning Environment is an ideal candidate for an environment where humans and artificial agents can be tested on the same tasks. We present an upcoming study using this environment, where the goal is to investigate how RL can be extended to enable abstract human abilities such as moments of insight. We claim this is valuable for advancing our understanding of both artificial and natural intelligence, thereby leading to improved models of player behaviour and for general video game playing.
Proteomics Analysis of Myocardial Tissues in a Mouse Model of Coronary Microembolization

Coronary microembolization (CME) is an important clinical problem, and it is related to poor outcome. The specific molecular mechanisms of CME are not fully understood. In the present study, we established a mice model of CME. Isobaric tags for relative and absolute quantitation (iTRAQ) and liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) technologies identified 249 differentially expressed proteins in the myocardial tissues of CME mice as compared with sham-operated mice. Bioinformatics analysis demonstrated that these differentially expressed proteins were enriched in several energy metabolism or cytoskeleton organization related processes or pathways. Quantitative PCR and Western blotting validation experiments revealed that succinate dehydrogenase (SDHA and SDHB) were upregulated, Rho GDP dissociation inhibitor α (RhoGDIα) and Filamin-A (FLNA) were downregulated significantly in CME mice. These findings indicated that the alternations of the cytoskeleton and energy metabolism pathways play important roles in the pathogenesis of CME, future studies are warranted to verify if targeting these molecules might be useful to alleviate CME injury or not.
Subjectively correlated estimation of noise due to blurriness distortion based on auto-regressive model using the Yule-Walker equations

In this study, a block-based estimation of noise due to blurriness distortion is proposed based on auto-regressive (AR) modelling. In the proposed method; a de-correlated, low-energy version of the blurred image is auto regressively modelled. To this end, AR parameters are estimated using the Yule–Walker equations. As these equations include auto-correlation function (ACF) coefficients, ACF estimation is also required. The Yule–Walker equations are solved making use of Durbin–Levinson algorithm. Finally, noise energy is mathematically defined and computed for each block. Since blurriness is a signal-dependent image distortion, estimating and describing its characteristics via a noise like that of the AR model input, is significant. In fact, extracting features of such ‘noise’ can lead to the design and development of a new method of image quality metrics. Inspired by the ‘stem cells’ concept in medical science that is convertible to other cell types, the AR model input is called ‘stem noise’. To visualise contribution of the ‘Stem Noise’ in the reconstruction of blurriness image distortion, a map called stem noise energy map is created. It is shown that the characteristics of the estimated noise energy are well correlated with the human subjective scores.
Recurrent neural networks for remote sensing image classification

Automatically classifying an image has been a central problem in computer vision for decades. A plethora of models has been proposed, from handcrafted feature solutions to more sophisticated approaches such as deep learning. The authors address the problem of remote sensing image classification, which is an important problem to many real world applications. They introduce a novel deep recurrent architecture that incorporates high-level feature descriptors to tackle this challenging problem. Their solution is based on the general encoder–decoder framework. To the best of the authors’ knowledge, this is the first study to use a recurrent network structure on this task. The experimental results show that the proposed framework outperforms the previous works in the three datasets widely used in the literature. They have achieved a state-of-the-art accuracy rate of 97.29% on the UC Merced dataset.