Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Efficient Large-Scale Interprocedural Program Static Analysis on Distributed Data-Parallel Computation

Static program analysis has been widely applied along the whole process of the program development for bug detection, code optimization, testing, etc. Although researchers have made significant work in static program analysis, it is still challenging to perform sophisticated interprocedural analysis on large-scale modern software. The underlying reason is that interprocedural analysis for large-scale modern software is highly computation- and memory-intensive, leading to poor efficiency and scalability. In this article, we introduce an efficient distributed and scalable solution for sophisticated static analysis. Specifically, we propose a data-parallel algorithm and a join-process-filter computation model for the CFL-reachability-based interprocedural analysis. Based on that, an efficient distributed static analysis engine called BigSpa is developed, which is composed of an offline batch static program analysis system and an online incremental static program analysis system. The BigSpa system has high generality and can support all kinds of static analysis tasks that can be expressed as CFL reachability problems. The performance of BigSpa is evaluated on real-world large-scale software datasets. Our experiments show that the offline batch system can exceed an order of magnitude compared with the most advanced analysis tools available on performance, and for incremental analysis with small batch updates on the same data sets, the online analysis system can achieve near real-time response, which is very fast and flexible.
Comparative Analysis of Hot Carrier Degradation (HCD) in 10-nm Node nMOS/pMOS FinFET Devices

In 10-nm node core FinFETs, we analyzed the cause of higher hot carrier degradation (HCD) in pFinFETs than in nFinFETs. Self-heating effect is severe in pFinFETs because SiGe is used as the source/drain materials, which makes the device temperature higher than nFinFETs. Theoretically, because the lifetime of multiple particle (MP) mechanism decreases as temperature increases, degradation due to MP decreases. Therefore, it is difficult for the pure HCD mechanisms to occur more in pFinFETs, which has higher temperature than nFinFETs. However, in pFinFETs, unlike nFinFETs, interface traps can be generated due to negative-bias temperature instability (NBTI) that occurs by the reaction between inversion holes and electrons of Si–H bonds. Also, since NBTI deteriorates more as the temperature increases, the phenomenon of higher degradation in pFinFET than nFinFET can be explained with the NBTI mechanism. Therefore, we propose an additional NBTI mechanism that is caused by high device temperature in pFinFETs even in the HCD condition. In addition, the main components were investigated through measurements of current degradation rate in various voltage conditions, and it was found that NBTI is dominant in pFinFETs. Finally, NBTI that can occur in the HCD condition was predicted through technology computer-aided design (TCAD) simulation. As a result, degradation due to pure hot carriers without NBTI occurs more in nFinFETs than in pFinFETs.
Approaches to Improve Millimeter-Wave Spectrum Utilization Using Indoor Small Cells in Multi-Operator Environments Toward 6G

In this paper, we propose two spectrum utilization improvement approaches (SUIAs), namely SUIA 1 and SUIA 2, based on whether or not the licensed 28 GHz millimeter-wave (mmWave) spectrum is allocated equally to each mobile network operator (MNO) in a country. Principally, SUIA 1 concerns with improving spectrum utilization if the 28 GHz spectrum is allocated equally to each MNO statically, also termed as static licensed spectrum allocation (SLSA). Whereas, SUIA 2 concerns with improving spectrum utilization if the spectrum is allocated unequally to each MNO in a flexible manner, also termed as flexible licensed spectrum allocation (FLSA). Since sharing and reusing of the licensed spectrum allocated to each MNO using either SLSA or FLSA can be exploited, and the secondary spectrum trading is required only in case of SLSA to redistribute the assigned spectra among MNOs, SUIA 1 employs SLSA, spectrum trading, spectrum sharing, and spectrum reusing techniques, whereas SUIA 2 employs FLSA, spectrum sharing, and spectrum reusing techniques. We present mathematical models for each technique and derive average capacity, spectral efficiency (SE), and energy efficiency (EE) metrics for SUIA 1 and SUIA 2. Extensive numerical and simulation results and analyses for SUIA 1 and SUIA 2 are carried out. It is shown that the spectrum reusing technique influences mostly SE and EE performances. Moreover, SE and EE performances of an MNO in SUIA 1 do not differ considerably from that in SUIA 2 such that depending on the spectrum allocation policies and practices in a country, either SUIA 1 or SUIA 2 can be employed. Finally, it is shown that by applying both SUIA 1 and SUIA 2, the prospective average SE and average EE requirements for sixth-generation (6G) mobile networks can be satisfied.
Understanding disclosed and cryptic HIV transmission risk via genetic analysis: what are we missing and when does it matter?

Purpose of review To discuss the recent HIV phylogenetic analyses examining HIV transmission patterns among and within risk groups. Recent findings Phylodynamic analysis has recently been applied to multiple HIV outbreaks among people who inject drugs to determine whether HIV transmission is ongoing. Large-scale analyses of datasets of HIV sequences collected for drug-resistance testing provide population-level insights into transmission patterns. One focus across world regions has been to investigate whether age-disparity is a driver of HIV transmission. In sub-Saharan Africa, researchers have examined transmission between heterosexuals and MSM and between high prevalence fishing communities and inland communities. In the US and the UK, cryptic risk groups such as nondisclosed MSM and the partners of transgender women are increasingly being uncovered based on their position in densely sampled molecular transmission networks. Summary Analysis of HIV genetic sequence can resolve viral transmission patterns between risk groups at unprecedented scales and levels of detail. Future research should focus on understanding the effect of missing data on inferences and the biases of different methods. Uncovering groups and patterns obscured from traditional epidemiolocal analyses is exciting but should not compromise the privacy of the groups in question.
NOMA-based UAV-aided networks for emergency communications

High spectrum efficiency (SE) requirement and massive connections are the main challenges for the fifth generation (5G) and beyond 5G (B5G) wireless networks, especially for the case when Internet of Things (IoT) devices are located in a disaster area. Non-orthogonal multiple access (NOMA)-based unmanned aerial vehicle (UAV)-aided network is emerging as a promising technique to overcome the above challenges. In this paper, an emergency communications framework of NOMA-based UAV-aided networks is established, where the disasters scenarios can be divided into three broad categories that have named emergency areas, wide areas and dense areas. First, a UAV-enabled uplink NOMA system is established to gather information from IoT devices in emergency areas. Then, a joint UAV deployment and resource allocation scheme for a multi-UAV enabled NOMA system is developed to extend the UAV coverage for IoT devices in wide areas. Furthermore, a UAV equipped with an antenna array has been considered to provide wireless service for multiple devices that are densely distributed in disaster areas. Simulation results are provided to validate the effectiveness of the above three schemes. Finally, potential research directions and challenges are also highlighted and discussed.
For Physicians Managing Voiding Dysfunction, Improving the Detection Rate of Early Prostate Cancer and Discrimination From Benign Prostatic Hyperplasia, in a Molecular Biomarker Aspects

Prostate cancer (CaP) is the most common cancer diagnosed among men in the United States and the fifth most common cancer among men in Korea. Unfortunately, the early stages of CaP may have no symptoms. Thus, early detection is very important and physicians managing voiding dysfunction must have awareness about CaP. The traditional tests used for early detection of CaP are the prostate-specific antigen (PSA) blood test and digital rectal examination. However, a high PSA level is not specific for CaP. Benign prostatic hyperplasia, prostatitis, urinary tract infection, and urinary retention can all cause a high PSA level. Thus, no test shows sufficient accuracy to truly be useful for screening men for CaP. A prostate biopsy is the only method that yields a definitive diagnosis of CaP; however, this test is invasive and uncomfortable. Recently, new biomarkers for CaP detection have been proposed to improve the accuracy of the PSA test. In this review, we summarize our knowledge of various new biomarkers, including PSA-associated biomarkers (the prostate health index and 4Kscore), molecular biomarkers (PCA3, TMPRSS2: ERG fusion gene, and various miRNAs), and proteomics-associated biomarkers, and the ways in which they may improve the detection rate of CaP. Accordingly, this review can raise awareness about CaP to physicians managing voiding dysfunction and be a good reference for them.
Investigation of Voltage Drop across Reactance of Expanding Spark Channel

A voltage drop across reactance of an expanding spark channel was numerically studied in the paper. Changes in the discharge current and radius of the conductive spark channel over time were determined by the spark expansion simulation. This data was used to calculate changes in channel inductance and voltage drop across the reactance of a spark. The analysis of the influence of energy stored in the channel inductance on the measurement of the discharge energy dissipated in the spark was carried out.
Neurobiological Determinants of Self-Organized Criticality in Neuronal Avalanches

Over the last two decades, self-organized criticality in brain activity has been widely discussed. The scale-free activation patterns, called neuronal avalanches, provide evidence for the postulation that the brain is operating in a critical state. Several neurobiological properties found in experiments are indicated to be important parameters in neuronal avalanches. Here, we developed a dynamic neural network model including these neurobiological properties, such as the balance between excitation and inhibition, the synaptic delay times, and the spatial connection structure, to theoretically test and verify the possibility of these neurobiological properties as the control parameters in tuning the network through criticality in neuronal avalanches.
The effect of hydroalcoholic Saffron (Crocus sativus L.) extract on fasting plasma glucose, HbA1c, lipid profile, liver, and renal function tests in patients with type 2 diabetes mellitus: A randomized double‐blind clinical trial

Diabetes mellitus is a metabolic disease that manifested as hyperglycemia due to the defect in secretion or function of insulin. Studies have shown that saffron and its derivatives cause a significant reduction in plasma glucose levels in experimental models. The purpose of this study was to investigate the effect of the saffron extract on fasting plasma glucose (FPG), glycated hemoglobin level (HbA1c), lipid profile, liver enzymes, and renal function tests in type 2 diabetic patients. In this double‐blind randomized clinical trial, 64 type 2 diabetic patients who were on oral anti‐diabetic drugs were examined. Participants received either 15 mg of saffron or placebo capsules (two pills per day) for 3 months. Anthropometric indices, dietary intake, FPG, HbA1c, lipid profiles, liver enzymes (ALT, AST, ALP), and renal function (BUN, Cr.) tests were measured pre and post intervention after 3 months. Independent t test and paired t test were used for data analysis. After 3‐months intervention, mean difference of FPG, Cholesterol, LDL‐c, and LDL/HDL ratio between two groups showed significant reduction(p < 0.0001), but HbA1c, HDL‐C, API, TG showed no significant differences (p > 0.05). In saffron group, FPG, HbA1c, cholesterol, LDL‐c, and LDL/HDL ratio decreased significantly after 3‐months intervention compare with baseline (p < 0.0001).
Workpiece Detection Based on Image Processing and Convolutional Neural Network

This paper presents a method on workpiece detection based on image processing and convolutional neural network(CNN). Firstly, four extreme points and center point of the workpiece are detected by image processing technologies such as canny edge detection operator, morphological processing and denoising processing. And the predicted boxes fitting the shape of image is generated. Then, according to the coordinates of the extreme points, the image with a single workpiece is cut out, and a novel CNN named workpiece-net(wp-net) is created to classify the object. As a result, the accuracy of image cutting is 0.9986, the average Intersection over Union(IoU) is 0.9235; the parameter size of wp-net is 98.25K and the average precision of classification is 0.9883. In addition, the average recall of classification is 0.9877 and the speed of classification is 0.1243s/fps without Graphics Processing Unit(GPU) and multithreading. Compared with the pure deep learning method, this method can detect more accurate coordinates which are consisted of extreme points. At the same time, the number of wp-net parameters and the complexity of the model structure used for classification are so far less than the popular deep neural network for detection that it can be easily deployed in embedded devices with limited storage space and computing power.
Integrated Bi-directional Buck-Boost Converter with Small Wind Turbine for Voltage Load Mitigation using Intelligent Controller

Load voltage stability is important in micro wind turbine standalone systems or in microgrids involving wind turbines. Inappropriate voltage load with nominal voltage is expected to have a bad impact and even damage to the load device. In this study, the proposed MSC (Machine Side Controller) and BBC (Bi-directional Buck Boost Converter) controllers are designed to mitigate over voltages caused by the use of MPPT (Maximum Power Point Tracking) in wind turbines. MSC is designed with dual loops. The first loop is the PI (Proportional Integral) Current Controller while the second loop is the SMSC (Sliding Mode Speed Controller). In addition, to mitigate the effects of over voltage, a dual loop SMCC (Sliding Mode Current Controller) with FVC (Fuzzy Voltage Controller) to control BBC is proposed. Simulation results show that the two proposed controllers are able to produce a good response with an indicator that the RMSE for rotational speed PMSG is 2.8576. While, the RMSE for voltage load is 0. 3250. This value is acceptable because the steady state error at the voltage load is less than 5%.
Binding of IFT22 to the intraflagellar transport complex is essential for flagellum assembly

Intraflagellar transport (IFT) relies on motor proteins and the IFT complex to construct cilia and flagella. The IFT complex subunit IFT22/RabL5 has sequence similarity with small GTPases although the nucleotide specificity is unclear because of non‐conserved G4/G5 motifs. We show that IFT22 specifically associates with G‐nucleotides and present crystal structures of IFT22 in complex with GDP, GTP, and with IFT74/81. Our structural analysis unravels an unusual GTP/GDP‐binding mode of IFT22 bypassing the classical G4 motif. The GTPase switch regions of IFT22 become ordered upon complex formation with IFT74/81 and mediate most of the IFT22‐74/81 interactions. Structure‐based mutagenesis reveals that association of IFT22 with the IFT complex is essential for flagellum construction in Trypanosoma brucei although IFT22 GTP‐loading is not strictly required.
Investigating the Significance of New Features Extracted from Long Bones X-ray Images

Bone fracture is a medical condition where the continuity of the bone is broken. Fractures can be simple or complicated, and sometimes can be difficult to be diagnosed by specialists. Medical image processing plays an important role in improving the health care system by guiding physicians to diagnose different types of diseases, and to make the right decision regarding the appropriate treatment option. In this paper, we propose to investigate different conditions of long bones using new features that describe the physical properties of the bone. The continuous wavelet analysis, gradient analysis, bone edge detection, and Principal Component Analysis (PCA) are discussed in this work and used to extract features. By taking the tibia bone as an example, the features of the injured bone using these methods are extracted and compared with the features of the contralateral un-injured bone (i.e. the normal tibia bone) for the same patient, taking advantage of human body symmetry. The novelty of this work, the idea has not been used before in the field of features extraction from long bones or in fracture detection processes. This work will help researchers to choose the most significant features of long bones, before using them in fracture detection and classification processes.
A Compact Short-Channel Analytical Drain Current Model of Asymmetric Dual-Gate TMD FET in Subthreshold Region Including Fringing Field Effects

A compact drain current model is developed for an asymmetric, dual gate, monolayer <inline-formula> <tex-math notation="LaTeX">$2-D$ </tex-math></inline-formula> Transition metal dichalcogenide (TMD) field effect transistor (FET) in the subthreshold region. The work includes the effect of source to drain tunneling and gate dielectric fringing effects. The model is systematically derived for an asymmetric, dual gate structure. The model developed is also extended into a dual-gate symmetric structure. The characteristic length expression has only physical and dimensional parameters including the contribution of fringing field effects from both front and back gate dielectric. The model is validated with simulation results obtained using NEGF based nanodevice simulators and experimental data of <inline-formula> <tex-math notation="LaTeX">$WSe_{2}$ </tex-math></inline-formula> p-channel FET. Also, transfer characteristics, output characteristics, subthreshold swing and output resistance are compared with reported data in literatures. A close agreement is observed with some disparity arising because of the non-inclusion of back gate fringing effects and source to drain tunneling in their models. The proposed model captures the effects of different high-<inline-formula> <tex-math notation="LaTeX">$\kappa $ </tex-math></inline-formula> gate dielectric materials and its thicknesses. Impact of temperature is also studied on transfer characteristics. The model is also scalable from ultrashort channel regime to long channel regime. Finally, the model can be applicable not only for TMD materials but other <inline-formula> <tex-math notation="LaTeX">$2-D$ </tex-math></inline-formula> materials also.
The Importance of Predefined Rules and Prespecified Statistical Analyses: Do Not Abandon Significance.

For decades, statisticians and clinicians have debated the meaning of statistical and clinical significance. In general, most journals remain married to the frequentist approach to statistical testing and using the term statistical significance. A recent proposal to ban statistical significance gained campaign-level momentum in a commentary with 854 recruited signatories.1 The petition proposes retaining P values but abandoning dichotomous statements (significant/nonsignificant), suggests discussing “compatible” effect sizes, denounces “proofs of the null,” and points out that “crucial effects” are dismissed on discovery or refuted on replication because of nonsignificance. The proposal also indicates that “we should never conclude there is ‘no difference’ or ‘no association’ just because a P value is larger than a threshold such as 0.05 or, equivalently, because a confidence interval includes zero,”1 and that categorization based on other statistical measures (eg, Bayes factors) should be discouraged. Other recent articles have also addressed similar topics, with an entire supplemental issue of a statistics journal devoted to issues related to P values.2 Changing the approach to defining statistical and clinical significance has some merits; for example, embracing uncertainty, avoiding hyped claims with weak statistical support, and recognizing that “statistical sig-
Do Children With Attention-Deficit/Hyperactivity Disorder (ADHD) Have Set Shifting Deficits?

Objective: Set shifting, or cognitive flexibility, is a core executive function involving the ability to quickly and efficiently shift back and forth between mental sets. Meta-analysis suggests medium-magnitude shifting impairments in attention-deficit/hyperactivity disorder (ADHD). However, this conclusion may be premature because the evidence-base relies exclusively on tasks that have been criticized for poor construct validity and may better reflect general neuropsychological functioning rather than shifting specifically. Method: A well-characterized sample of 77 children ages 8–13 (M = 10.46, SD = 1.54; 32 girls; 66% Caucasian/non-Hispanic) with ADHD (n = 43) and without ADHD (n = 34) completed the criterion global-local set shifting task and 2 counterbalanced control tasks that were identical in all aspects except the key processes. Results: The experimental manipulation was successful at evoking set shifting demands during the global-local versus both nonshift control tasks (p < .001; &ohgr;2 = .12–.14). Mixed-model analyses of variance (ANOVAs) revealed that the ADHD group did not demonstrate disproportional decrements in speed shift costs on the shifting versus nonshift control tasks (p = .30; &ohgr;2 = .002), suggesting no evidence of impaired set shifting abilities in ADHD. In contrast, the ADHD group made disproportionately more shifting errors than the non-ADHD group (p = .03; &ohgr;2 = 0.03) that were more parsimoniously attributable to prerequisite (nonshifting) processes necessary for successful performance on the global-local task. Conclusions: Children with ADHD’s impaired performance on shifting tasks may be attributable to difficulties maintaining competing rule sets and/or inhibiting currently active rule sets prior to shifting. However, when these higher-order processes are executed successfully, there is no significant evidence to suggest a unique set shifting deficit in ADHD.