Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Single Nucleotide Non-coding Driver Mutations in Cancer

Recent whole-genome sequencing studies have identified millions of somatic variants present in tumor samples. Most of these variants reside in non-coding regions of the genome potentially affecting transcriptional and post-transcriptional gene regulation. Although a few hallmark examples of driver mutations in non-coding regions have been reported, the functional role of the vast majority of somatic non-coding variants remains to be determined. This is because the few driver variants in each sample must be distinguished from the thousands of passenger variants and because the logic of regulatory element function has not yet been fully elucidated. Thus, variants prioritized based on mutational burden and location within regulatory elements need to be validated experimentally. This is generally achieved by combining assays that measure physical binding, such as chromatin immunoprecipitation, with those that determine regulatory activity, such as luciferase reporter assays. Here, we present an overview of in silico approaches used to prioritize somatic non-coding variants and the experimental methods used for functional validation and characterization.
TrackCC: A Practical Wireless Indoor Localization System Based on Less-Expensive Chips

This paper aims at proposing a new wireless indoor localization system (ILS), called TrackCC, based on a commercial type of low-power system-on-chip (SoC), nRF24LE1. This type of chip has only l output power levels and acute fluctuation for a received minimum power level in operation, which give rise to many practical challenges for designing localization algorithms. In order to address these challenges, we exploit the Markov theory to construct a (l+1)×(l+1) -sized state transition matrix to remove the fluctuation, and then propose a priority-based pattern matching algorithm to search for the most similar match in the signal map to estimate the real position of unknown nodes. The experimental results show that, compared to two existing wireless ILSs, LANDMARC and SAIL, which have meter level positioning accuracy, the proposed TrackCC can achieve the decimeter level accuracy on average in both line-of-sight (LOS) and non-line-of-sight (NLOS) senarios.
Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses.
Single Operation Multiple Data - Data Parallelism at Subroutine Level

The parallel nature of the multi-core architectural design can only be fully exploited by concurrent applications. This status quo pushed productivity to the forefront of the language design concerns. The community is demanding for new solutions in the design, compilation, and implementation of concurrent languages, making this research area one of great importance and impact. To that extent this paper proposes the expression of data parallelism at subroutine level. The calling of a subroutine in this context spawns several execution flows, each operating on distinct partitions of the input dataset. Such computations can be expressed by simply annotating sequential subroutines with data distribution and reduction policies, delegating the management of the parallel execution to a dedicated runtime system. The paper overviews the key concepts of the model, illustrating them with some small programming examples, and describes a Java implementation built on top of the X10 [1] runtime system. A performance evaluation attests that this approach can provide good performance gains without burdening the programmer with the writing of specialized code.
Authors' reply

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TrkB Modulates Fear Learning and Amygdalar Synaptic Plasticity by Specific Docking Sites

Understanding the modulation of the neural circuitry of fear is clearly one of the most important aims in neurobiology. Protein phosphorylation in response to external stimuli is considered a major mechanism underlying dynamic changes in neural circuitry. TrkB (Ntrk2) neurotrophin receptor tyrosine kinase potently modulates synaptic plasticity and activates signal transduction pathways mainly through two phosphorylation sites [Y515/Shc site; Y816/PLCγ (phospholipase Cγ) site]. To identify the molecular pathways required for fear learning and amygdalar synaptic plasticity downstream of TrkB, we used highly defined genetic mouse models carrying single point mutations at one of these two sites (Y515F or Y816F) to examine the physiological relevance of pathways activated through these sites for pavlovian fear conditioning (FC), as well as for synaptic plasticity as measured by field recordings obtained from neurons of different amygdala nuclei. We show that a Y816F point mutation impairs acquisition of FC, amygdalar synaptic plasticity, and CaMKII signaling at synapses. In contrast, a Y515F point mutation affects consolidation but not acquisition of FC to tone, and also alters AKT signaling. Thus, TrkB receptors modulate specific phases of fear learning and amygdalar synaptic plasticity through two main phosphorylation docking sites.
IR thermographic evaluation of thermal diffusivity anisotropy: comparative analysis of some algorithms

Theoretical and experimental results for determining thermal diffusivity components in anisotropic Carbon Fiber Reinforced Plastic laminates up to 5 mm thick are presented. The effectiveness of the theory is evaluated by using a 3D numerical model. IR thermographic implementation of the Parker's technique has been used for determining transverse diffusivity. Both spot- and slit-mask techniques have been applied for analyzing thermal diffusivity components.
Human bone perivascular niche-on-a-chip for studying metastatic colonization

Significance Improved human preclinical models are needed to better predict patients’ responses to anticancer drugs. Increasing the complexity of models may be a successful strategy only if crucial components of a tumor are identified, replicated, and controlled in vitro. We developed a perivascular niche to study metastatic colonization of the bone. Using a microfluidic chip, we exposed the niche to interstitial flow, oxygen gradients, and external forces, and established a dense vascular network. Cancer cells colonizing the bone resisted targeted therapy by entering a slow proliferative state. We expect that microfluidic niche-on-chip models will facilitate the development of drugs targeting persistent tumor cells into the bone and help manage the risk of metastatic relapse. Eight out of 10 breast cancer patients die within 5 years after the primary tumor has spread to the bones. Tumor cells disseminated from the breast roam the vasculature, colonizing perivascular niches around blood capillaries. Slow flows support the niche maintenance by driving the oxygen, nutrients, and signaling factors from the blood into the interstitial tissue, while extracellular matrix, endothelial cells, and mesenchymal stem cells regulate metastatic homing. Here, we show the feasibility of developing a perfused bone perivascular niche-on-a-chip to investigate the progression and drug resistance of breast cancer cells colonizing the bone. The model is a functional human triculture with stable vascular networks within a 3D native bone matrix cultured on a microfluidic chip. Providing the niche-on-a-chip with controlled flow velocities, shear stresses, and oxygen gradients, we established a long-lasting, self-assembled vascular network without supplementation of angiogenic factors. We further show that human bone marrow-derived mesenchymal stem cells, which have undergone phenotypical transition toward perivascular cell lineages, support the formation of capillary-like structures lining the vascular lumen. Finally, breast cancer cells exposed to interstitial flow within the bone perivascular niche-on-a-chip persist in a slow-proliferative state associated with increased drug resistance. We propose that the bone perivascular niche-on-a-chip with interstitial flow promotes the formation of stable vasculature and mediates cancer cell colonization.
Targeting ABCB1 (MDR1) in multi-drug resistant osteosarcoma cells using the CRISPR-Cas9 system to reverse drug resistance

Background Multi-drug resistance (MDR) remains a significant obstacle to successful chemotherapy treatment for osteosarcoma patients. One of the central causes of MDR is the overexpression of the membrane bound drug transporter protein P-glycoprotein (P-gp), which is the protein product of the MDR gene ABCB1. Though several methods have been reported to reverse MDR in vitro and in vivo when combined with anticancer drugs, they have yet to be proven useful in the clinical setting. Results The meta-analysis demonstrated that a high level of P-gp may predict poor survival in patients with osteosarcoma. The expression of P-gp can be efficiently blocked by the clustered regularly interspaced short palindromic repeats (CRISPR)-associated Cas9 system (CRISPR-Cas9). Inhibition of ABCB1 was associated with reversing drug resistance in osteosarcoma MDR cell lines (KHOSR2 and U-2OSR2) to doxorubicin. Materials and Methods We performed a meta-analysis to investigate the relationship between P-gp expression and survival in patients with osteosarcoma. Then we adopted the CRISPR-Cas9, a robust and highly efficient novel genome editing tool, to determine its effect on reversing drug resistance by targeting endogenous ABCB1 gene at the DNA level in osteosarcoma MDR cell lines. Conclusion These results suggest that the CRISPR-Cas9 system is a useful tool for the modification of ABCB1 gene, and may be useful in extending the long-term efficacy of chemotherapy by overcoming P-gp-mediated MDR in the clinical setting.
Plasmonic Refractive Index Sensor with High Figure of Merit Based on Concentric-Rings Resonator

A plasmonic refractive index (RI) sensor based on metal-insulator-metal (MIM) waveguide coupled with concentric double rings resonator (CDRR) is proposed and investigated numerically. Utilizing the novel supermodes of the CDRR, the FWHM of the resonant wavelength can be modulated, and a sensitivity of 1060 nm/RIU with high figure of merit (FOM) 203.8 is realized in the near-infrared region. The unordinary modes, as well as the influence of structure parameters on the sensing performance, are also discussed. Such plasmonic sensor with simple framework and high optical resolution could be applied to on-chip sensing systems and integrated optical circuits. Besides, the special cases of bio-sensing and triple rings are also discussed.
Deductive refinement of species labelling in weakly labelled birdsong recordings

Many approaches have been used in bird species classification from their sound in order to provide labels for the whole of a recording. However, a more precise classification of each bird vocalization would be of great importance to the use and management of sound archives and bird monitoring. In this work, we introduce a technique that using a two step process can first automatically detect all bird vocalizations and then, with the use of ‘weakly’ labelled recordings, classify them. Evaluations of our proposed method show that it achieves a correct classification of 75.4% when used in a synthetic dataset.
The lived experience of individuals in cardiac rehabilitation who have a positive outlook on their cardiac recovery: A phenomenological inquiry

Background: Cardiac rehabilitation is often under-utilized despite its well-known benefits. Individuals with cardiac disease who exhibit a positive outlook often experience improved health outcomes. This study tried to explore the question: “What are the lived experiences of cardiac recovery in cardiac rehabilitation individuals with a predominantly positive outlook in the context of an acute cardiac event? ” Aims: Our primary aim explored the experiences of cardiac recovery in cardiac rehabilitation participants with a predominantly positive outlook, within the context of an acute cardiac event, including exploring barriers and facilitators of cardiac recovery. Our secondary aim explored how a positive outlook impacted completion of phase two of the cardiac rehabilitation program. Methods: Husserlian phenomenology guided this study. A purposive sample of 10 individuals who had experienced an acute cardiac event and had a predominantly positive outlook were interviewed. Data were analyzed using Colaizzi’s method. Results: Three themes emerged from the data. The first was “choosing life over death,” where participants discussed how they made a decision to improve their health. The second theme was “learning to live a new self,” where participants described the changes they had to make in order to improve their health. The third theme was “a life-transforming cardiac event” where participants shared how the cardiac event had changed their life. Conclusion: The participants’ decisions to choose to live, led them to embrace their cardiac recovery. It is important for nurses to identify individuals in cardiac rehabilitation that need additional support. In addition, alternative models of cardiac rehabilitation programs need to be explored.
Nanoscale MOS Transistors

Written from an engineering standpoint, this book provides the theoretical background and physical insight needed to understand new and future developments in the modeling and design of nand p-MOS nanoscale transistors. A wealth of applications, illustrations, and examples connect the methods described to all the latest issues in nanoscale MOSFET design. Key areas covered include: • Transport in arbitrary crystal orientations and strain conditions, and new channel and gate stack materials; • All the relevant transport regimes, ranging from low field mobility to quasi-ballistic transport, described using a single modeling framework; • Predictive capabilities of device models, discussed with systematic comparisons to experimental results.
Topology Optimization of Geometrically Non-Linear Structures Using Iso-XFEM Method

Iso-XFEM is an evolutionary-based topology optimization method which couples the extended finite element method (X-FEM) with an isoline/isosurface optimization approach, enabling a smooth and accurate representation of the design boundary in a fixed-grid finite element mesh. This paper investigates the application of the Iso-XFEM method to the topology optimization of structures which experience large deformation. The total Lagrangian formulation of the finite element method is employed to model the geometrically non-linear behaviour and equilibrium is found by implementing the Newton-Raphson method in each evolution. A cantilever beam is considered as a test case and the Iso-XFEM solutions obtained from linear and non-linear designs are compared with bi-directional evolutionary structural optimization (BESO) solutions.
Vehicle detection and pose estimation by probabilistic representation

The ability to recognize a vehicle and estimate its pose is important for to a wide range of practical scenarios. Recently, it has been shown that several vehicle components could be a discriminative visual pattern during recognition and detection. To detect these components, our observation is that it is more reliable to build probabilistic prediction maps rather than simply relying on region proposals. Another key insight here is that the spatial relationship between these vehicle components shows some consistent patterns, and is able to provide strong semantic cues for vehicle pose estimation. In this paper, we propose a supervised learning framework with Fully Convolutional Network (FCN) to build probabilistic prediction maps of vehicle components, then vehicle pose is estimated based on the absence/presence and the spatial relationship (e.g. the relative distance, scales, angles) of these components. The proposed method is evaluated with three state-of-the-art approaches on public vehicle image datasets and achieve superior performance.
Missing Data Recovery Based on Tensor-CUR Decomposition

Tensor completion is a higher way analog of matrix completion, which has proven to be a powerful tool for data analysis. In this paper, we formulate the missing data recovery problem of a three-way tensor as a tensor completion problem. We propose a novel tensor completion method based on tensor-CUR decomposition to estimate the missing data from limited samples. Computational experiments demonstrate that the proposed method yields a superior performance over other existing approaches.
Defects in Nematic Liquid Crystal Film with Geometric Grooves

In nanometer scale, the defects in a liquid crystal film with geometric grooves exhibit two forms, namely, surface-induced (−1/2 and +1/2) and −1/2 body defects. When the geometric condition is changed, surface-induced and body defects compete with each other in the liquid crystal film. The order reconstruction of the body and surface-induced defects occurs when the gap is smaller than the threshold value. The effects of the free and periodic boundaries as the boundary conditions for left and right walls on the defects structures are compared in our paper.
CAMDroid: An Adaptation Framework for Android Context-Aware Multitasking

Mobile phones have become an indispensable part of our daily life. For the sake of portability and energy conservation, battery-powered mobile phones have inherent features: small screens, short sessions, single window visible at one time, and variant connectivity. These features limit the user interaction of mobile phones to the foreground application on the small screen, hindering the interaction with background applications even when using mobile multitasking. To interact with background applications, users have to call one of them into foreground first. We believe such an interaction mechanism deprive the benefit of multitasking. The background application is more like "holding" than "running" in the background because they cannot access the external resources or interact with the users. In this paper, we propose CAMDroid, an architecture that involves human status into the loop of multitasking. CAMDroid brings context-awareness into the internal mobile OS and enhances the multitasking abilities of mobile phones by providing support to the interactions between users and the background applications. Therefore, CAMDroid improves the whole system performance, compared to the traditional Android OS without context-awareness.
Post‐diagnosis alcohol intake and prostate cancer survival: A population‐based cohort study

Alcohol consumption has been declared a Group 1 carcinogen by the International Agency for Research on Cancer (IARC) and is a potential risk factor for several types of cancer mortality. However, evidence for an association with prostate cancer survival remains inconsistent. We examined how alcohol consumption post‐diagnosis was associated with survival after prostate cancer diagnosis. Men diagnosed with prostate cancer (n = 829) in Alberta, Canada between the years 1997 and 2000 were recruited into a population‐based case–control study and then followed for up to 19 years for survival outcomes. Pre‐ and post‐diagnosis alcohol consumption, clinical characteristics and lifestyle factors were collected through in‐person interviews shortly after diagnosis and again 2–3 years post‐diagnosis. Cox proportional hazards were used to examine how post‐diagnosis alcohol consumption was associated with all‐cause and prostate cancer‐specific mortality (competing risk analysis too), in addition to first recurrence/progression or new primary cancer. Most participants reported drinking alcohol (≥once a month for 6 months) post‐diagnosis (n = 589, 71.0%). Exceeding Canadian Cancer Society (CCS) alcohol consumption recommendations (≥2 drinks/day) post‐diagnosis was associated with prostate cancer‐specific mortality relative to non‐drinkers (aHR: 1.82, 95% CI: 1.07–3.10) with borderline evidence of a linear trend. Interestingly, those in the highest quartile of drinks/week pre‐ and post‐diagnosis also had a twofold increase for prostate‐specific mortality (aHR: 2.67, 95% CI: 1.28–5.56) while controlling for competing risks. Our results support post‐diagnosis alcohol consumption was associated with increased mortality after prostate cancer diagnosis, specifically for prostate cancer‐related death. Future studies focused on confirming this burden of disease are warranted.
Isolated symptomatic middle cerebral artery stenosis in young adults: clinical prognosis and vascular change

Background and purpose: To investigate the clinical prognosis and vascular outcome of ischemic stroke patients with isolated symptomatic middle cerebral artery stenosis, and further analysis of the predictors associated with the results. Methods: Ischemic stroke patients aged 18–55 years old with isolated symptomatic middle cerebral artery stenosis were evaluated and followed up prospectively for six months. Logistic regression was used to detect predictors of ipsilateral stroke recurrence, and factors associated with the dynamic changes of lesion vascular were analyzed. Results: Eighty patients were included, with a mean age of 41.8 ± 8.3 years old. Males predominated in this cohort at a proportion of 78.8% (63/80). Twenty percent of patients presented with ipsilateral ischemic stroke recurrence during this time but mostly with a good outcome (70% mRS ≤ 1); multiple logistic regression indicated that diabetes mellitus is an independent predictor for stroke recurrence; 38.6% patients presented with significant vascular changes during the follow-up, with progression in 12 (17.1%) and regression in 15 (21.4%) patients individually. No variables were detected as predictors of cerebral vascular progression. Conclusion: Isolated symptomatic middle cerebral artery stenosis in young adults had unaccepted high rates of recurrence but comparatively good prognosis; despite the dramatic change of lesion artery in the short period after stroke, no factors were detected as the probable factors associated with the dynamic process.