Miracle-dz/UniFAR-FTUs huggingface dataset:
Trends in Incidence and Prognostic Factors of Two Subtypes of Primary Liver Cancers: A Surveillance, Epidemiology, and End Results-Based Population Study

Objectives The objective of our study was to investigate and compare the epidemiologic characteristics, prognostic factors, and survival between hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) patients. Methods Age-adjusted incidence rates were evaluated from 1975 to 2016 using the Surveillance, Epidemiology, and End Results (SEER) database. Overall survival (OS) was investigated using the Kaplan–Meier method and log-rank test. Univariate and multivariate Cox regression analyses were performed to identify the independent prognostic factors for OS. Results In the last 10 years, the incidence rate of ICC increased rapidly by 109% (annual percentage change (APC) = 8.24, 95% CI = 6.64 to 9.86; P < . 001), compared with a much more modest 12% increase in the incidence of HCC (APC = 1.59, 95% CI = .56 to 2.62; P < .001). This trend persisted throughout the study across different age groups, sexes, and races. Males older than 70 years and of other races (non-African American and non-Caucasian) showed the highest incidence rates of HCC and ICC. Multivariate Cox regression analysis demonstrated that other race, married status, later year of diagnosis, more examined lymph nodes, and surgery were significant protective factors of OS in HCC patients. In contrast, the race and year of diagnosis were not independent prognostic factors, but radiation and chemotherapy were protective factors of OS in ICC patients. The median OS was 18 months and 12 months in HCC and ICC patients, respectively. Conclusion In the last 10 years, the incidence of HCC had a slow growth in the United States, whereas ICC showed a remarkable increase. The 5-year OS of the former has improved in recent years while that of the latter showed no significant improvement. Therefore, surgery could contribute to superior survival outcomes as compared to other treatments.
Lifetime Estimation of Aluminum Plate Fin Heat Exchangers

Aluminum Plate Fin Heat Exchangers (Al-PFHE) are often used in low temperature applications of chemical plants when huge heat transfer capacities are required. Typically the equipment is insulated or installed in insulated containments — so called “Cold Boxes”. Al-PFHE may either fail by corrosion or by mechanical overload due to trip scenarios or blockage / fouling. No failures due to mechanical overload should occur under the conditions of the ALPEMA [9] guideline (ALPEMA = Aluminum Plate-fin Heat Exchanger Manufacturer’s Association). However, ALPEMA doesn’t describe all operational situations in the exchanger block itself and the ALPEMA load conditions are not followed in all cases. The specific design of Al-PFHE does not allow standard inspection and maintenance procedures, which makes it difficult to evaluate the equipment condition and the expected remaining service life. Corrosion, blockage, fouling, and mechanical/thermal overload are the key degradation mechanisms that operators need to control to avoid premature failure of their aluminum plate fin heat exchangers. This paper describes how to incorporate finite element analysis and dynamic process simulation in the design and operation to evaluate the lifetime of Al-PFHE.Copyright © 2012 by ASME
Two-wheeled balancing robot controller designed using pid

Two wheeled self-balancing robot, which is based on an inverted pendulum system, is dynamically stable but statically unstable. The robot involves various physics and control theories. This project describes the modelling of the two wheeled self-balancing robot, designs the robot controller using PID and implements the controller on the robot. In this project, an inertial measurement unit (IMU) is used, which combines accelerometer and gyroscope measurement in order to estimate and obtain the tilt angle of the robot. The PID controller is applied to correct the error between the desired set point and the actual tilt angle and adjust the dc motor speed accordingly to balance the robot. The result obtained shows that the PID controller is able to balance the robot acceptably but with some limitations. The simulation result of the model is compared with the developed hardware and the performance of the controller is analyzed and discussed. In addition, the PID tuning using heuristic method is also performed and an improvement can clearly be seen in terms of the robot balancing.
Effect of Velocity Anisotropy in Shale on the Acoustic Emission Events Matching and Location

Accurate source event location is important in fracturing monitoring and characterization. Velocity anisotropy has a great influence on both events matching and events location. Failure to take into account the velocity anisotropy can lead to huge errors in locating events. In this article, we have presented an experimental study on lower Silurian shale from the Sichuan Basin. The experimental observations include ultrasonic measurements, acoustic emissions (AEs) in a three-point bend experiment, and CT scanning of the original sample and the fractured sample. The ultrasonic measurements show that the shale sample has strong velocity anisotropy. Initially, AEs are analyzed using the conventional event-matching method and event location method (Geiger’s method), and the detected events are compared to the X-ray image of the fracture. Event-matching aims to obtain AE signals from the same source event and thus assists in selecting valid AE signals that come from the same source and are received by at least four sensors, to determine the location of the source. Although many reliable signals are obtained by isotropic event-matching, fewer sources were located than expected, and the event location results did not match the fracture distribution. To address this problem, an improved event-matching method is proposed using a stricter matching threshold based on directional velocity rather than a single threshold same for all directions. In addition, we propose an improved Geiger’s method using the anisotropic velocity model. The new methods located more sources that better match fracture distribution than the results of the isotropic method. We have concluded that both event-matching and the source location of the fracturing are largely influenced by velocity anisotropy, and thus in practice, the velocity anisotropy information obtained from various measurements (e.g., laboratory measurements, well logs, VSP, and velocity analysis of reflected seismic surveys) should be involved in both processing procedures. This study can be useful to provide some background for monitoring and predicting dynamic geo-hazards in relation to the AE method.
An Accurate Loss Model for a Star Optical Burst-Switched Network

In this paper, we propose and analyze a new loss model to calculate the burst loss probability and the utilization over a star OBS network, where each edge node is linked to the core node via an upstream and a downstream fiber, each carrying the same number of wavelengths. The edge nodes can send bursts to all the other edge nodes and receive as well. A burst is dropped whenever it tries to leave the core node through an output port that has all the wavelengths that are busy. The burst arrival process from each source is modeled by an IDLE-ON process, which accurately captures the burst transmission. The results obtained from simulation confirm that our loss model exhibits a good accuracy under different input parameters.
Multi-input Serial Adders for FPGA-like Computational Fabric

In this paper, we present a new functional unit to replace the LUT in an FPGA-like computational fabric designed specifically for use to accelerate instance-specific sparse integer matrix multiplication. We use a suite of matrices, the VPR place-and-route tool, and modern architecture representations of the interconnect to examine this architectural idea. The new cell, called the K--ADD, increases density by 2.5x to 4x, and increases performance by 8% to 30% by simultaneously increasing the clock rate and reducing the number of cycles to compute the product. This benefit magnifies the two-orders-of-magnitude advantage of using instance-specific matrix multipliers demonstrated in prior work. We investigate the cluster size, N, across multiple technology nodes. In that investigation, we see a sustained benefit to a larger cluster size (N=8). This observation holds for both netlists mapped to a 6--LUT and to a 6--ADD, which implies this behavior has more to do with the peculiar structure of these matrix multiplication netlists, not the different functional unit.
Enhancing the Adoption of Computational Thinking Education Among the Malaysians to Prepare for Future Industrial Revolution

This study explains the factors that enhance Computational Thinking (CT) in the education of Malaysia, specifically for undergraduate students. The purpose of strengthening the CT among the undergraduate students is to ensure the readiness and preparation for the coming industrial revolution, such as Industry Revolution 4.0 and beyond. This study proposes integrating Technology Readiness Index(TRI) and Technology Acceptance Model (TAM) as main factors to examine how it enhances the CT in Malaysian education. In addition, this integration will operate as the main theoretical framework for this research study and form a model in this research study, namely Technology Readiness Acceptance Model (TRAM). This study shall establish a suitable adoption model to integrate computational thinking from the Malaysian education perspective for the future industrial revolution. The discussion and explanation on the factors that enhance CT in Malaysian education are discussed further in the paper.
HMT: A Hardware-Centric Hybrid Bonsai Merkle Tree Algorithm for High-Performance Authentication

Merkle tree is a widely used tree structure for authentication of data/metadata in a secure system. Even though recent state-of-the art systems use MAC based authentication to protect the actual data, they still use smaller-sized MT, namely Bonsai Merkle Tree (BMT) to protect the metadata such as encryption counters. Common BMT algorithms were designed for traditional von Neumann architecture with software-centric implementations in mind, hence they use a lot of recursions and are often sequential in nature. The predominantly recursive and sequential nature of these traditional BMT algorithms make them largely unsuitable for use and challenging to implement in the modern heterogeneous computing platforms employing Field-Programmable Gate Array (FPGA) devices. Our goal for this work is to introduce HMT, a hardware-friendly BMT algorithm that enables the verification and update processes to function independently and provides the benefits of relaxed update while being comparable to eager update in terms of update complexity. Deploying this new algorithm, we have designed a new BMT controller with a dataflow architecture and speculative buffers that allow multiple parallel authentication on-flight which was not possible with the conventional algorithms. This new MT subsystem enables up to 7x improvement in bandwidth while also exhibiting up to 4.5x reduction in latency over the baseline.
Absolute Winding Number Differentiates Mouse Spatial Navigation Strategies With Genetic Risk for Alzheimer’s Disease

Spatial navigation and orientation are emerging as promising markers for altered cognition in prodromal Alzheimer’s disease, and even in cognitively normal individuals at risk for Alzheimer’s disease. The different APOE gene alleles confer various degrees of risk. The APOE2 allele is considered protective, APOE3 is seen as control, while APOE4 carriage is the major known genetic risk for Alzheimer’s disease. We have used mouse models carrying the three humanized APOE alleles and tested them in a spatial memory task in the Morris water maze. We introduce a new metric, the absolute winding number, to characterize the spatial search strategy, through the shape of the swim path. We show that this metric is robust to noise, and works for small group samples. Moreover, the absolute winding number better differentiated APOE3 carriers, through their straighter swim paths relative to both APOE2 and APOE4 genotypes. Finally, this novel metric was sensitive to sex differences, supporting increased vulnerability in females. We hypothesized differences in spatial memory and navigation strategies are linked to differences in brain networks, and showed that different genotypes have different reliance on the hippocampal and caudate putamen circuits, pointing to a role for white matter connections. Moreover, differences were most pronounced in females. This departure from a hippocampal centric to a brain network approach may open avenues for identifying regions linked to increased risk for Alzheimer’s disease, before overt disease manifestation. Further exploration of novel biomarkers based on spatial navigation strategies may enlarge the windows of opportunity for interventions. The proposed framework will be significant in dissecting vulnerable circuits associated with cognitive changes in prodromal Alzheimer’s disease.
Rheological transition driven by matrix makes cancer spheroids resilient under confinement

Cancer metastasis through a confining peritoneal fluid microenvironment is mediated by spheroids: clusters of disseminated transformed cells. Ovarian cancer spheroids are frequently cavitated and their ‘blastuloid’ morphology is correlated with an extracellular matrix (ECM) coat. Here, we investigate the effects of such morphology on the mechanical integrity of confined cancer spheroids. Atomic force microscopy showed higher elastic modulus for blastuloid spheroids relative to their prefiguring non-lumen ‘moruloid’ counterparts. Subsequently, spheroids were flowed through microfluidic conditions mimicking peritoneal confinement. Traversing moruloids exhibited asymmetric cell flows during entry, often deformed and disintegrated through travel, and showed an incomplete- and slow shape recovery upon exit. In contrast, blastuloids traveled faster, exhibited rapid and efficient shape recovery upon exit, symmetric vector flows, and lesser disintegration. A multiscale computational model predicted higher intercellular adhesion and a dynamical lumen make blastuloids resilient. Although, E-cadherin overexpression in moruloids did not affect their resilience, blastuloid ECM-debridement decreased E-cadherin membrane localization, obliterated the lumen, and reversed the rheological properties of blastuloids to those typifying moruloids. The ECM-induced lumen therefore drives spheroidal transition from a labile viscoplastic to a resilient elastic state allowing them to survive spatially-constrained peritoneal flows.
Transgenic microalgae expressing double-stranded RNA as potential feed supplements for controlling white spot syndrome in shrimp aquaculture

Viral infection of farmed fish and shellfish represents a major issue within the aquaculture industry. One potential control strategy involves RNA interference of viral gene expression through the oral delivery of specific double-stranded RNA (dsRNA). In previous work we have shown that recombinant dsRNA can be produced in the chloroplast of the edible microalga, Chlamydomonas reinhardtii and used to control disease in shrimp. Here we report a significant improvement in antiviral dsRNA production and its use to protect shrimp against white spot syndrome virus (WSSV). A new strategy for dsRNA synthesis was developed that uses two convergent copies of the endogenous rrnS promoter to drive high level transcription of both strands of the WSSV gene element in the chloroplast. New vectors were designed that allow rapid Golden Gate-mediated assembly of a transformation plasmid in which the ‘dual promoter-WSSV DNA’ cassette is targeted into the chloroplast genome, with selection based on the restoration of photosynthesis. PCR analysis of transformant lines confirmed the integration of the cassette and homoplasmy of the polyploid genome. Transcribed sense and antisense VP28-RNA were hypothesised to form an RNA duplex in the chloroplast stroma, and quantitative RT-PCR indicated that ∼100 μg dsRNA is produced per litre of transgenic microalgae culture. This represents an ∼10,000-fold increase in dsRNA relative to previous reports using convergent psaA promoters. The engineered alga was assessed for its ability to prevent WSSV infection when fed to shrimp larvae prior to a challenge with the virus. Survival of shrimp fed with dsRNA-expressing C. reinhardtii was significantly enhanced (68.3%) relative to the negative control. The study suggests that this new dsRNA production platform is significantly more efficient than that reported previously, and merits further scale-up and downstream processing studies.
Host variation in type I interferon signaling genes (MX1), CCR5Δ32, and MHC class I alleles in treated HIV+ non-controllers predict viral reservoir size

Objective Prior genomewide association studies have identified variation in MHC Class I alleles and CCR5Δ32 as genetic predictors of viral control, especially in “elite” controllers, individuals who remain virally suppressed in the absence of therapy. Design Cross-sectional genomewide association study. Methods We analyzed custom whole exome sequencing and direct HLA typing from 202 ART-suppressed HIV+ non-controllers in relation to four measures of the peripheral CD4+ T cell reservoir: HIV intact DNA, total (t)DNA, unspliced (us)RNA, and RNA/DNA. Linear mixed models were adjusted for potential covariates including age, sex, nadir CD4+ T cell count, pre-ART HIV RNA, timing of ART initiation, and duration of ART suppression. Results Previously reported “protective” host genetic mutations related to viral setpoint (e.g., among elite controllers) were found to predict smaller HIV reservoir size. The HLA “protective” B*57:01 was associated with significantly lower HIV usRNA (q=3.3×10−3), and among the largest subgroup, European ancestry individuals, the CCR5Δ32 deletion was associated with smaller HIV tDNA (p=4.3×10−3) and usRNA (p=8.7×10−3). In addition, genomewide analysis identified several SNPs in MX1 (an interferon stimulated gene) that were significantly associated with HIV tDNA (q=0.02), and the direction of these associations paralleled MX1 gene eQTL expression. Conclusions We observed a significant association between previously reported “protective” MHC class I alleles and CCR5Δ32 with the HIV reservoir size in non-controllers. We also found a novel association between MX1 and HIV total DNA (in addition to other interferon signaling relevant genes, PPP1CB, DDX3X). These findings warrant further investigation in future validation studies.
Multimodal Explanations for User-centric Medical Decision Support Systems

Based on empirical evidence indicating that different types of explanations should be used to satisfy different users in terms of their information needs and to increase trust in the system, we motivate the use of multimodal explanations for decisions made by a machine learning model to support medical diagnoses. We present a system through which medical professionals or students can obtain verbal explanations for a classiﬁcation by means of a dialogue and to which they can make queries to get prototypical examples in the form of images showing typical health conditions. Our approach could be used for validating algorithmic decisions using a human-in-the-loop method or for medical education.
Induction of subsets of MUP genes in the liver by different patterns of GH administration

Group 1 major urinary protein (Mu? ) genes can be divided into subgroups named Mup-1.1A, Mup-1.1B, Mup-1.1C and Mup1. 1D. Allelic genes in Balb/c and C57BL/6 inbred strains of mice are referred to as Mup1. 1AR and Mup_1. lAk respectively. Expression of MUP genes in the liver is sexually dimorphic, however, the relative expression in males and females varies between subgroups and between allelic genes within a subgroup. Genes from two subgroups, Mup-1.1A and Mup-1. 1C code for proteins which are synthesized at higher levels in male than female liver. In contrast, genes from two other subgroups, Mup-1.1B and Mup-1.1D code for proteins synthesized in male liver but undetectable in female liver. The Mup-1.1C subgroup contains two single copy allelic genes, Mup-1.10 and Mup_1.1Cb_. In C57BL/6 expression of Mup-1.1cP in the liver of males is twice as high as females, whereas in Balb/c, expression of Mup-1. 1Ccin males is seven to twenty times as high as females. Several genes in the Mup-1.1B subgroup differ between Balb/c and C57BL/6 mice, however, expression in the liver ofenes in this subgroup is the same in both strains and is approximately one hundred times higher in males than females. In the livers of growth hormone (GH) deficient lit/lit C57BL/6 mice MUP mRNA levels are approximately one hundred fold lower than in phenotypically normal lit/+ C57BL/6 males. The sexually dimorphic pattern of MU? expression is also absent. Administration of GH to male lit/lit mice by one regime caused a large increase in the levels of particular MU? mRNAs in the liver, whereas administration by another regime did not. Altering the GH regime affected some MU? mRNAs more than others.
Two-Stage Hybrid Machine Learning Model for High-Frequency Intraday Bitcoin Price Prediction Based on Technical Indicators, Variational Mode Decomposition, and Support Vector Regression

Due to the inherent chaotic and fractal dynamics in the price series of Bitcoin, this paper proposes a two-stage Bitcoin price prediction model by combining the advantage of variational mode decomposition (VMD) and technical analysis. VMD eliminates the noise signals and stochastic volatility in the price data by decomposing the data into variational mode functions, while technical analysis uses statistical trends obtained from past trading activity and price changes to construct technical indicators. The support vector regression (SVR) accepts input from a hybrid of technical indicators (TI) and reconstructed variational mode functions (rVMF). The model is trained, validated, and tested in a period characterized by unprecedented economic turmoil due to the COVID-19 pandemic, allowing the evaluation of the model in the presence of the pandemic. The constructed hybrid model outperforms the single SVR model that uses only TI and rVMF as features. The ability to predict a minute intraday Bitcoin price has a huge propensity to reduce investors’ exposure to risk and provides better assurances of annualized returns.