Miracle-dz/UniFAR-FTUs huggingface dataset:
Generation of Istanbul road data set using Google Map API for deep learning-based segmentation

ABSTRACT Deep learning architectures are widely used for road segmentation studies. Data sets reflect the characteristics of the study region in which they are generated. The models that are trained with the data sets are unable to accurately forecast the region outside the area covered by the data sets. That is why local data sets must be generated to meet the requirements of navigation, military activities, urban planning and health management applications where road data are indispensable. In this study, satellite images and corresponding mask images of Istanbul city at different zoom levels were generated via Google Map Platform. Trained models were produced using Deep Residual U-Net. This study consists of three parts. The first part includes training each zoom level, from 14 to 17, separately. The recall statistics of models were found as 95%, 94%, 92% and 86%, and corresponding F1-Score statistics were calculated as 95%, 95%, 92% and 86%, respectively. Next, consecutive training with priory weight and regularization on satellite images were tested to increase the prediction results. The consecutive model and regularization methods resulted in an increase in both recall and F1-Score by 2−3%. In the third part, a new model was generated by combining all images which were produced at different levels. The combined model was found successful for the prediction of roads in all zoom levels. Finally, the performance of these models trained with the Istanbul data set was compared with well-known DeepGlobe and Massachusetts road data sets. Hence, this study illustrated that generating all data sets specifically for the area of interest is crucial.
Association of a Common NOS1AP Variant with Attenuation of QTc Prolongation in Men with Heroin Dependence Undergoing Methadone Treatment

Background: The effects of methadone-induced severe prolongation of the corrected QT interval (QTc) and sudden cardiac death appear unpredictable and sex-dependent. Genetic polymorphisms in the nitric oxide synthase 1 adaptor protein (NOS1AP) have been implicated in QTc prolongation in general populations. We investigated whether common NOS1AP variants interact with methadone in relation to QTc prolongation in patients with heroin dependence. Methods: We genotyped 17 NOS1AP variants spanning the entire gene in heroin-dependent patients who received a 12-lead electrocardiography (ECG) examination both at baseline and during maintenance methadone treatment in Cohort 1 and only during maintenance methadone treatment in Cohort 2. The QT interval was measured automatically by the Marquette 12SL program, and was corrected for heart rate using Bazett’s formula. Results: Cohort 1 consisted of 122 patients (age: 37.65 ± 8.05 years, 84% male, methadone dosage: 42.54 ± 22.17 mg/day), and Cohort 2 comprised of 319 patients (age: 36.9 ± 7.86 years, 82% male, methadone dosage: 26.08 ± 15.84 mg/day), with complete genotyping data for analyses. Before methadone, the QTc intervals increased with increasing age (r = 0.3541, p < 0.001); the age-adjusted QTc showed dose-dependent prolongation in men (r = 0.6320, p < 0.001), but abbreviation in women (r = −0.5348, p = 0.018) in Cohort 1. The pooled genotype-specific analysis of the two cohorts revealed that the QTc interval was significantly shorter in male carriers of the rs164148 AA variant than in male carriers of the reference GG genotype (GG: n = 262, QTc = 423 ± 1.4 ms; AA: n = 10, QTc = 404.1 ± 7 ms, p = 0.009), according to univariate analysis. The QTc remained shorter in male carriers of the rs164148 AA variant compared to GG genotype (423 ± 1.4 ms vs. 405.9 ± 6.9 ms, p = 0.016) in multivariate analysis after adjusting for age and methadone dosage. A cut-off QTc interval of <410 ms identifies 100% of AA carriers compared to none of GG carriers when receiving a daily methadone dosage of 30.6 ± 19.3 mg. There was no significant gene-drug interaction in contributing to the adjusted QTc (p = 0.2164) in male carriers of the rs164148 variants. Conclusions: Carriers of a common NOS1AP rs164148 AA genotype variant were associated with a shorter QTc interval in men receiving maintenance methadone treatment. This genetic polymorphism attenuates the QTc-prolonging effect by methadone, and thus may explain at least in part the unpredictable and heterogeneous risks for severe QTc prolongation and sudden cardiac death in patients on methadone.
Revamp Computer Education With Multimedia And Game Technologies

The booming computer technology has changed our daily lives dramatically in the past decade. We witnessed the microprocessor changing from 8-bit to 64-bit and the display from monochrome monitor to millions of colors LCD screen. However, the teaching of college level computer classes does not catch up with the pace. This widens the gap between advanced computing technology and the college computer education. Especially facing the fact that today’s youngsters are grown up in a computerized multimedia world – they are enthusiasts of internet, video games, ipod, MySpace, face book, and etc. even before they enter college. Having known lots of popular fancy applications using computer techniques, their expectation of their first computer class is not the same as students of twenty years ago. But the struggling for their first computing class in college resulted in low retention rate reported by many institutions. To address this issue, a group of faculty members from computing discipline investigated to teach the traditional topics of computer courses unconventionally. Instead of working in a console environment (with text-based outputs), we explored new teaching approaches that allow students to learn computing by writing programs that produce graphics, manipulate images, working with audio and video, and developing computer games. Focuses are placed on students’ first computing class in two categories: Engineering major and non-Engineering major. C++ is the computing fundamental class for engineering majors. In order to avoid overwhelming students with game theory or the intricacies of a graphics library such as DirectX or OpenGL, we used the Microsoft product, Dark GDK (a free library that makes graphics programming simple enough for beginners), as the platform, so that students can focus on the fundamentals while creating interesting graphics and game programs. While covering the fundamental topics (such as data types, variables, input, output, control structures, functions, arrays, files classes, and objects), students learn to draw with primitive graphics, load and manipulate images, create sprites and animations, play music and sound effects. For non-engineering majors, the course is non C++ based computer application course. We choose Vizard—a popular virtual reality programming environment—to design course teaching modules to make the course learning full of fun since there is no need to teach this group of students as software developers, instead, they should be taught as tool modifiers. In this project, faculty members developed new course modules and introduced them into the corresponding computing classes. Preliminary results were obtained and obstacles were discussed, and in the future, we are going to develop more new course modules and also involve more computing courses to be enhanced.
GRADISTAT in environmental sciences: a sampled review of the 21 years of the program application in environmental sciences

: The study of sediment dynamics using grain size parameters is well established in sedimentology and earth sciences. To help the wide-ranging needs of researchers in the fields of earth and depositional sciences, Blott and Pye (2001) wrote a GRADISTAT program that is integrated into a Microsoft Excel spreadsheet. This study reviewed 66 scientific articles principally found in ScienceDirect. Sampled research papers are categorised into six general groups and summarised in terms of the most environmental themes addressed. The themes covered in this paper are: the understanding of land-sea interactions and processes; sediment contaminations and pollution; impacts of sediment variables and transportation on macrofauna, vegetation and habitat; microplastics; soil genesis and movement; and, palaeontology. The ubiquitous nature of this application has shown it applied in many parts of the world. The GRADISTAT will continue to be a relevant environmental advance that is essential in classifying sediments in depositional environments.
Intestinal Flora: A Potential New Regulator of Cardiovascular Disease

Although substantial progress has been made in reducing the burden of the disease by preventing the risk factors of cardiovascular disease (CVD), potential risk factors still exist and lead to its progression. In recent years, numerous studies have revealed that intestinal flora can interfere with the physiological processes of the host through changes in composition and function or related metabolites. Intestinal flora thus affects the occurrence and development of a variety of CVDs, including atherosclerosis, ischemic heart disease, and heart failure. Moreover, studies have found that interventions for intestinal flora and its metabolites provide new opportunities for CVD treatment. This article mainly discusses the interaction between the human intestinal flora and its metabolites, the occurrence and development of CVD, and the potential of intestinal flora as a new target for the diagnosis and treatment of CVD.
PFoPID CONTROL DESIGN OF GRID-CONNECTED PV INVERTER FOR MPPT USING HYBRID ALGORITHM

This paper aims to model a novel “passive fractional-order proportional-integral-derivative (PFoPID) controller” for photovoltaic (PV) inverter via reshaping energy, in such a way that the MPPT is attained through P&O system under diverse atmospheric states. Depending on passivity concept, storage, related to the DC-link current and DC-link voltage, in addition to q -axis current is initially build-up for a PV system, where every variable will be examined systematically when the advantageous terms are retained carefully so as to exploit the features of PV system. Here, the residual energy is reshaped by the FoPID control model, where the control constraints are optimally tuned by a new hybrid algorithm, which hybrids the concept of Cat Swarm Optimization (CSO) and Fireﬂy Algorithm (FF), so that a ﬁnest controlling performance could be attained. As both the concepts of FF and CSO are in-cluded, the adopted model is known as Combined FF-CSO scheme (CFF-CSO).
Stress management using fNIRS and binaural beats stimulation.

In this study, we investigate the effectiveness of binaural beats stimulation (BBs) in enhancing cognitive vigilance and mitigating mental stress level at the workplace. We developed an experimental protocol under four cognitive conditions: high vigilance (HV), vigilance enhancement (VE), mental stress (MS) and stress mitigation (SM). The VE and SM conditions were achieved by listening to 16 Hz of BBs. We assessed the four cognitive conditions using salivary alpha-amylase, behavioral responses, and Functional Near-Infrared Spectroscopy (fNIRS). We quantified the vigilance and stress levels using the reaction time (RT) to stimuli, accuracy of detection, and the functional connectivity metrics of the fNIRS estimated by Phase Locking Values (PLV). We propose using the orthogonal minimum spanning tree (OMST) to determine the true connectivity network patterns of the PLV. Our results show that listening to 16-Hz BBs has significantly reduced the level of alpha amylase by 44%, reduced the RT to stimuli by 20% and increased the accuracy of target detection by 25%, (p < 0.001). The analysis of the connectivity network across the four different cognitive conditions revealed several statistically significant trends. Specifically, a significant increase in connectivity between the right and left dorsolateral prefrontal cortex (DLPFC) areas and left orbitofrontal cortex was found during the vigilance enhancement condition compared to the high vigilance. Likewise, similar patterns were found between the right and left DLPFC, orbitofrontal cortex, right ventrolateral prefrontal cortex (VLPFC) and right frontopolar PFC (prefrontal cortex) area during stress mitigation compared to mental stress. Furthermore, the connectivity network under stress condition alone showed significant connectivity increase between the VLPFC and DLPFC compared to other areas. The laterality index demonstrated left frontal laterality under high vigilance and VE conditions, and right DLPFC and left frontopolar PFC while under mental stress. Overall, our results showed that BBs can be used for vigilance enhancement and stress mitigation.
A distribution balance-based data augmentation method for light-trap pest detection

Agriculture pest disaster is one of the most important reasons that reduce grain yield. Accurate recognition and detection are the core of integrated pest management (IPM). Existing deep learning-based methods improve the capacity of feature extraction, but ignore the imbalance of object number and size distribution result in insufficient performance. Therefore, we design a joint balance-distribution oriented composition (JBDOC) to detect multi-class pests with the synthetic dataset. Object bounding boxes and white background boards are used to construct the balanced synthetic dataset for training the convolutional neural network (CNN). Our JBDOC solves the distribution imbalance without methods restriction and improves the test performance without extra time consumption. We combine the JBDOC with current popular detection methods to verify the validity. Experimental results show that the JBDOC greatly improves the performance of deep learning-based detectors in the pest field.
Studies in Rats of Combined Muscle and Liver Perfusion and of Muscle Extract Indicate That Contractions Release a Muscle Hormone Directly Enhancing Hepatic Glycogenolysis

Background: Established neuroendocrine signals do not sufficiently account for the exercise-induced increase in glucose production. Using an innovative, yet classical cross-circulation procedure, we studied whether contracting muscle produces a factor that directly stimulates hepatic glycogenolysis. Methods: Isolated rat hindquarters were perfused in series with isolated livers. Results: Stimulation of the sciatic nerve of one or both legs resulted in an increase in force, which rapidly waned. During one-legged contractions, hepatic glucose production increased initially (from −0.9 ± 0.5 (mean ± SE) to 3.3 ± 0.7 µmol/min, p < 0.05). The peak did not differ significantly from that seen after 20 nM of epinephrine (5.1 ± 1.2 µmol/min, p > 0.05). In response to two-legged contractions, the increase in hepatic glucose production (to 5.4 ± 1.3 µmol/min) was higher (p < 0.05) and lasted longer than that seen during one-legged contractions. During contractions, peak hepatic glucose output exceeded concomitant hepatic lactate uptake (p < 0.05), and glucose output decreased to basal levels, while lactate uptake rose to a plateau. Furthermore, in separate experiments an increase in lactate supply to isolated perfused livers increased lactate uptake, but not glucose output. In intact rats, intra-arterial injection of extract made from mixed leg muscle elicited a prolonged increase (p < 0.05) in plasma glucose concentration (from 5.2 ± 0.1 mM to 8.3 ± 1.5 mM). In perfused livers, muscle extract increased glucose output dose dependently. Fractionation by chromatography of the extract showed that the active substance had a MW below 2000. Conclusion: This study provides evidence that contracting skeletal muscle may produce a hormone with a MW below 2000, which enhances hepatic glycogenolysis according to energy needs. Further chemical characterization is warranted.
Encapsulation of Catechin into β-Glucan Matrix Using Wet Milling and Ultrasonication as a Coupled Approach: Characterization and Bioactivity Retention

In this study, the nanoencapsulation of catechin into the β-glucan matrix from oats [O-Glu (C)] and barley [B-Glu (C)] was performed using the coupled approach of ultrasonication and wet milling. The nanoencapsulated catechin was characterised by particle size distribution, surface charge, SEM, and FTIR. The particle size was found to be 200 nm and 500 nm while zeta potential was found −27.13 and −24 mV for O-Glu (C) and B-Glu (C), respectively. The encapsulation efficiency of O-Glu (C) and B-Glu (C) was found to be 86.5% and 88.2%. FTIR and SEM revealed successful entrapment of catechin in β-glucan. The encapsulated capsules showed sustainable release during simulated gastrointestinal conditions. Moreover, both O-Glu (C) and B-Glu (C) showed that biological activity such as lipase inhibition activity and antioxidant assay were retained after in vitro digestion. It was concluded that O-Glu (C) and B-Glu (C) can be used as functional ingredients effectively in food as well as in the pharmaceutical field.
Hundred years of experience in the dynamic thermal modelling of power transformers

Loading capability of transformers depends strongly on their thermal conditions which can be investigated by means of a dynamic thermal model. It is typically a set of simple differential equations representing very complex physical phenomena; however, there are several factors affecting the accuracies of the models which should be kept in mind while using these models. This study provides a review on the dynamic thermal models of power transformers from very simple to rather complex thermal models proposed in the last hundred years, the affecting factors on their accuracies, and their fields of applications. It is worthwhile to note that this study focuses on the thermal models which are simple and accurate and able to be integrated into monitoring systems.
Efficacy of Lipid Nanoparticle-Loaded Sorafenib Combined with Hepatic Artery Chemoembolization in the Treatment of Primary Hepatocellular Carcinoma Complicated with Microvascular Invasion

This work was to evaluate the therapeutic effect of lipid nanoparticle-loaded sorafenib combined with transcatheter artery chemoembolization (TACE) in patients with primary hepatocellular carcinoma (HC) complicated with microvascular invasion (MVI). In this work, 102 patients with primary HC combined with MVI after radical resection were divided into 4 groups according to different treatment methods. Experimental group 1 was treated with lipid nanoparticle-loaded sorafenib combined with TACE treatment group; experimental group 2 was treated with lipid nanoparticle-loaded sorafenib treatment group; experimental group 3 was TACE treatment group; control group was postoperative routine nursing group. Sorafenib lipid nanoparticles were prepared. The basic information, operation, MVI degree, tumor recurrence, and survival time of patients in each group were recorded and compared to evaluate the therapeutic effect of combined way. No great difference was found in MVI grade, average age, sex ratio, preoperative tumor markers, tumor size, number of patients with liver cirrhosis, operation time, and intraoperative bleeding among the four groups (P > 0.05). In addition, the tumor free survival time (TFST), overall survival time (OST), and postoperative 1-year and 2-year survival rates of patients in test group 1 were greatly higher than those in single mode treatment group and control group (P < 0.05). In summary, sorafenib nanoparticles combined with TACE can improve the survival status of patients after resection and delay the time of postoperative tumor recurrence.
Feasibility of 18F-Fluorocholine PET for Evaluating Skeletal Muscle Atrophy in a Starved Rat Model

Imaging techniques for diagnosing muscle atrophy and sarcopenia remain insufficient, although various advanced diagnostic methods have been established. We explored the feasibility of 18F-fluorocholine (18F-FCH) positron emission tomography/computed tomography (PET/CT) for evaluating skeletal muscle atrophy, as an imaging technique that tracks choline level changes in muscles. Cell uptake in L6 cells by 18F-FCH was performed in a complete medium containing serum (untreated group, UN) and a serum-free medium (starved group, ST). Small-animal-dedicated PET/CT imaging with 18F-FCH was examined in in-vivo models with rats that were starved for 2 days to cause muscle atrophy. After the hind limbs were dissected, starvation-induced in-vivo models were anatomically confirmed by reverse-transcription polymerase chain reaction to evaluate the expression levels of the atrophy markers muscle RING-finger protein-1 (MuRF-1) and atrogin-1. 18F-FCH uptake was lower in the starvation-induced cells than in the untreated group, and in-vivo PET uptake also revealed a similar tendency (the average standardized uptake value (SUVmean) = 0.26 ± 0.06 versus 0.37 ± 0.07, respectively). Furthermore, the expression levels of MuRF-1 and atrogin-1 mRNA were significantly increased in the starvation-induced muscle atrophy of rats compared to the untreated group. 18F-FCH PET/CT may be a promising tool for diagnosing skeletal muscle atrophy.
Research Progress in the Application of Lycium Barbarum Polysaccharide in Ophthalmic Diseases

Lycium barbarum polysaccharides (LBP) are widely used in age-related macular degeneration, glaucoma, diabetic retinopathy, and other eye diseases. With further studies on the pharmacological action of Lycium barbarum polysaccharides in recent years, researchers have found that Lycium barbarum polysaccharides (LBP) play a protective role in the treatment of various eye diseases through anti-oxidation, scavenging oxygen free radicals, and inhibiting inflammatory reaction as well as cell senescence. This paper reviews the application of Lycium barbarum polysaccharides in ophthalmology.
Delay-Sensitive Task Assignment for Spatial Crowdsourcing

In spatial crowdsourcing, mobile workers are recruited to perform special tasks related to location and time. The task assignment has been a focus of the research community due to its importance in spatial crowdsourcing. However, most of the existing efforts focus on optimizing the task requester’s goal and do not consider the requirements and constraints of workers. Unlike the existing methods, we consider task assignment comprising the goals of both the workers and the requesters, that is, the trade-off regarding the reward and travel cost of a worker and the delay of a task. We formulate the delay-sensitive task assignment (DSTA) problem that optimizes the combined goal of minimizing costs and maximizing rewards of a worker; meanwhile, reducing the delay to wait until the task is assigned. The DSTA algorithm based on greed idea (DSTA-G) is proposed to address the problem. To improve the efficiency, we introduce the Geohash algorithm and propose a new solution DSTA-GH, which is scalable to large-scale datasets. Moreover, the task assignment method that only considers the worker’s objective (TAW) is proposed as the baseline. Finally, extensive experiments offer evidence that DSTA and DSTA-GH outperform the baseline in terms of performance and DSTA-GH only takes about 0.03% of the CPU time as compared to DSTA-G.