Miracle-dz/UniFAR-FTUs huggingface dataset:
KLHL14: A Novel Prognostic Biomarker and Therapeutic Target for Ovarian Cancer

Ovarian cancer (OV) is a gynaecological malignancy that poses a serious risk to the health status of women. To date, effective molecular markers are unavailable for the diagnosis and management of ovarian malignancies. In this study, we aimed to investigate the molecular markers associated with the development of this cancer. We used bioinformatic analysis to determine the molecules and genes related to ovarian cancer using the gene expression profiling interactive analysis (GEPIA) and the cancer genome Atlas (TCGA) databases. In addition, we examined the genes and mechanisms underlying ovarian cancer. Our results showed that the KLHL14 gene is overexpressed in some cancers. An increase in the KLHL14 expression indicates a poor prognosis in patients with ovarian cancer. Results of immune cell infiltration analysis and half-maximal inhibitory concentration (IC50) analysis provide novel insights into the treatment of ovarian cancer. KLHL14 is anticipated to emerge as a novel molecular marker specifically for ovarian carcinoma.
The Influence of Globalization on the Development of Educational Management

The article substantiates the impact of globalization on the system of management of education and identifies the main directions of its impact on education. Management of the educational sphere in modern conditions determines the procedure for the establishment and legalization of educational institutions, formation of decisions in the educational sphere, support of the vital activity of the structure and control over functioning and development of educational institutions. In conditions of the globalized world in management of education the issues related to supporting educational initiatives and innovations, creating conditions for stable functioning and development of educational systems, development and self-realization of participants in the educational process, legal and economic protection of education, forecasting and making optimal decisions. designing optimal models of educational systems come to the forefront. On the basis of the analysis of scientific works of the leading domestic and European researchers, the tasks of management of education in conditions of globalization have been summarized: definition of strategies of educational activities, improvement of methodologies of quality of management of education taking into account current trends in social development, working out of innovative approaches to management of educational services, intensification of European integration processes, introduction of information technologies in the system of management of education, development of mechanisms for regulating educational activities in a market environment, modification of scientific approaches to human resources management in education and modernization of training of specialists in management of education. The main ways for improving modern management in the process of implementation of educational policy in Ukraine have been proposed.
Processed Dietary Patterns during Pregnancy Are Associated with Low Birth Weight at Term among Women of Advanced and Non-Advanced Age

Inappropriate dietary intake during pregnancy is a key factor in low birth weight (LBW). This study compares LBW between healthy and processed dietary patterns by focusing on women of advanced maternal age. A cross-sectional survey was conducted with 327 postpartum women in Taiwan. The participants were assigned to two groups according to their age (≥35 years, n = 151; and 20–34 years, n = 176). An online questionnaire asked women how often they consumed 27 food items during their pregnancy. The prevalence of LBW was higher in the processed dietary pattern (79.3%) than in the healthy pattern (13.78%, p < 0.001). LBW was positively correlated with advanced maternal age (≥35 ages), low pre-pregnancy weight (BMI less than 18.5 kg/m2), insufficient gestational weight gain (GWG), and processed dietary patterns. Older mothers were 5.8 times more likely to have infants with LBW (odds ratio = 5.8; 95% confidence interval 2.0–16.6). A processed dietary pattern was 9.4 times more likely to result in LBW. Insufficient GWG was significantly positively associated with LBW (OR = 4.0; 95%CI 1.4–11.6). Maternal diet during pregnancy is an important modifiable factor for LBW. Prenatal advice should emphasize optimal nutrition, especially in older and underweight women.
A Phase Normalization Scheme for Angle of Arrival based Bluetooth Indoor Localization

Precise and reliable indoor localization is a demanding task with a variety of possible applications. Besides other approaches, Angle of Arrival (AoA) based positioning systems evolved over the past decades. The introduction of Bluetooth 5.1 added support for AoA-based localization to the Bluetooth Core Specification and hence promised the development of low-cost, accurate, and highly-available location services. However, due to pseudo-random phase offsets between measurements on different Bluetooth channels, state-of-the-art AoA estimation algorithms cannot be applied in this context. In this work a phase normalization scheme and a corresponding data model are proposed that resolve these problems. For an experimental evaluation, a study of the capabilities of a Bluetooth localization system in a $100\mathrm{m} ^{2}$ real-world testbed is presented. It is shown that the localization accuracy could be significantly improved in comparison with existing techniques suitable for Bluetooth indoor positioning. Using the proposed method, a median localization accuracy of 18cm was achieved.
Accurate Localization Algorithm for Indoor Robots Using Branch and Bound Strategy

Accurate localization is a prerequisite for robots to realize autonomous navigation. This paper proposes a robot localization algorithm suitable for indoor environments to effectively solve the problem of global localization and position tracking. First, global localization is realized by employing a two-stage matching method involving coarse and fine levels based on a branch-and-bound algorithm and iterative nearest point (ICP) algorithm to estimate the initial pose of the robot. Second, a local map-based scan matching method is used to realize position tracking. To address the accumulated errors between local maps, we build a pose graph to achieve loop-closure optimization. Moreover, to decrease the computational complexity of loop-closure detection, the branch-and-bound algorithm is used to accelerate the search of the loop constraints. The performance of the proposed algorithm is comprehensively evaluated in real application scenarios using commercial logistics robots. The experimental results demonstrate that represents a highly accurate and robust localization algorithm.
Microstructure simulation and experimental evaluation of the anisotropy of 316 L stainless steel manufactured by laser powder bed fusion

Purpose The effect of processing parameters on the microstructure of steel produced by laser-based powder bed fusion (LPBF) is a recognized opportunity for property design through microstructure control. Because the LPBF generates a textured microstructure associated with high anisotropy, it is of interest to determine the fabrication plane that would generate the desired property distribution within a component. Design/methodology/approach The microstructure of 316 L produced by LPBF was characterized experimentally (optical, scanning electron microscopy, glow discharge emission spectrometry and X-ray diffraction), and a finite element method was used to study the microstructure features of grain diameter, grain orientation and thermal parameters of cooling rate, thermal gradient and molten pool dimensions. Findings The computational tool of Ansys Additive was found efficient in reproducing the experimental effect of varying laser power, scanning speed and hatch spacing on the microstructure. In particular, the conditions for obtaining maximum densification and minimum fusion defects were consistent with the experiment, and the features of higher microhardness near the component’s surface and distribution of surface roughness were also reproduced. Originality/value To the best of the author’s knowledge, this paper is believed to be the first systematic attempt to use Ansys Additive to investigate the anisotropy of the 316 L SS produced by LPBF.
Association of Short-Term Changes in Menstrual Frequency, Medication Use, Weight and Exercise on Bone Mineral Density in College-Aged Women

To evaluate if experiencing a short-term exposure (18-months) to factors such as menstrual irregularities, dieting, changes in exercise or body weight, and medication usage is associated with bone mineral density (BMD) in college-aged females. A retrospective survey assessing health behaviors during a recent 18-month time period and a DXA scan were completed in 641 females. A total of 45.5% of participants reported amenorrhea during the 18-month time period. Those who experienced amenorrhea had lower femoral neck BMD (p = 0.018), trochanter (p = 0.018) and spine BMD (p = 0.022) compared to eumenorrheic women. Lifetime oral contraceptive usage longer than six months was negatively associated with BMD at femoral neck (p = 0.018) and total hip (p = 0.021). Women who lost weight trended towards having the lowest BMD at all sites compared to women who gained weight. Following a very-low calorie diet during the time period was negatively correlated with spine BMD (p = 0.001). Time spent in vigorous and very vigorous activity was weakly correlated with some hip BMD sites but time spent in extremely vigorous activity was not. In conclusion, females who experienced weight loss, amenorrhea, or a very low-calorie diet within an 18-month period of time in young adulthood had lower BMD. Additionally, oral contraceptive usage for longer than six months during their lifetime was associated with lower BMD.
Targeted Long-Read Bisulfite Sequencing Identifies Differences in the TERT Promoter Methylation Profiles between TERT Wild-Type and TERT Mutant Cancer Cells

Simple Summary TERT promoter methylation is enriched in cancers lacking TERT genetic alterations (wild-type cancers), but its functional impact on TERT transcription remains elusive. We developed a long-read bisulfite-sequencing platform to characterize the TERT promoter methylation profile at a single-molecule level. In wild-type cancer cell lines, both epialleles were hypermethylated symmetrically on the TERT distal promoter. In the core and proximal promoter, by contrast, the transcribed epialleles were significantly more hypomethylated than the silent epialleles. Decitabine-therapy reduced the core and proximal (not the distal) promoter methylation and reactivated the silent allele. We showed that TERT allele-specific expression is amenable to in vitro epigenetic manipulation in wild-type cancers. Abstract Background: TERT promoter methylation, located several hundred base pairs upstream of the transcriptional start site, is cancer specific and correlates with increased TERT mRNA expression and poorer patient outcome. Promoter methylation, however, is not mutually exclusive to TERT activating genetic alterations, as predicted for functionally redundant mechanisms. To annotate the altered patterns of TERT promoter methylation and their relationship with gene expression, we applied a Pacific Biosciences-based, long-read, bisulfite-sequencing technology and compared the differences in the methylation marks between wild-type and mutant cancers in an allele-specific manner. Results: We cataloged TERT genetic alterations (i.e., promoter point mutations or structural variations), allele-specific promoter methylation patterns, and allele-specific expression levels in a cohort of 54 cancer cell lines. In heterozygous mutant cell lines, the mutant alleles were significantly less methylated than their silent, mutation-free alleles (p < 0.05). In wild-type cell lines, by contrast, both epialleles were equally methylated to high levels at the TERT distal promoter, but differentially methylated in the proximal regions. ChIP analysis showed that epialleles with the hypomethylated proximal and core promoter were enriched in the active histone mark H3K4me2/3, whereas epialleles that were methylated in those regions were enriched in the repressive histone mark H3K27me3. Decitabine therapy induced biallelic expression in the wild-type cancer cells, whereas the mutant cell lines were unaffected. Conclusions: Long-read bisulfite sequencing analysis revealed differences in the methylation profiles and responses to demethylating agents between TERT wild-type and genetically altered cancer cell lines. The causal relation between TERT promoter methylation and gene expression remains to be established.
A Novel Combinatoric Correntropy Algorithm: Properties and its Performance Analysis

In order to improve the flexibility of the correntropy that is usually in the form of a single kernel, this brief proposes a novel combinatoric maximum correntropy criterion (C-MCC), where the combinatoric correntropy (C-C) consists of two different single-type kernels. As a new form of correntropy, the C-C has a more generalized form than the traditional single-kernel correntropy, and the corresponding properties and proofs of the C-C are given in this brief. It is noticed that the combined kernel can become a single kernel by changing the combined parameters. Moreover, the adaptive filtering algorithm based on C-MCC is derived and the theoretical performance analysis of the C-MCC algorithm is also provided. Finally, the experimental simulations show that the proposed algorithm has better convergence speed and steady-state performance than MCC-type and other algorithms, and the proposed method of the theoretical analysis of C-MCC agrees well with simulation results.
Learning Behavior Trees for Autonomous Agents with Hybrid Constraints Evolution

Featured Application: The proposed approach can learn transparent behavior models represented as Behavior Trees, which could be used to alleviate the heaven endeavor of manual agent programming in game and simulation. Abstract: In modern training, entertainment and education applications, behavior trees (BTs) have already become a fantastic alternative to ﬁnite state machines (FSMs) in modeling and controlling autonomous agents. However, it is expensive and inefﬁcient to create BTs for various task scenarios manually. Thus, the genetic programming (GP) approach has been devised to evolve BTs automatically but only received limited success. The standard GP approaches to evolve BTs fail to scale up and to provide good solutions, while GP approaches with domain-speciﬁc constraints can accelerate learning but need signiﬁcant knowledge engineering effort. In this paper, we propose a modiﬁed approach, named evolving BTs with hybrid constraints (EBT-HC), to improve the evolution of BTs for autonomous agents. We ﬁrst propose a novel idea of dynamic constraint based on frequent sub-trees mining, which can accelerate evolution by protecting preponderant behavior sub-trees from undesired crossover. Then we introduce the existing ‘static’ structural constraint into our dynamic constraint to form the evolving BTs with hybrid constraints. The static structure can constrain expected BT form to reduce the size of the search space, thus the hybrid constraints would lead more efﬁcient learning and ﬁnd better solutions without the loss of the domain-independence. Preliminary experiments, carried out on the Pac-Man game environment, show that the hybrid EBT-HC outperforms other approaches in facilitating the BT design by achieving better behavior performance within fewer generations. Moreover, the generated behavior models by EBT-HC are human readable and easy to be ﬁne-tuned by domain experts.
Comparative Study of The Effect of Supervision and Leadership on Work Discipline on Male and Women Workers in Sharia Banking Institutions in Semarang City Banks

AbstractPurpose - This study aims to examine the effect of supervision and leadership on work discipline and to determine whether or not there are differences in work discipline among male and female workers in Islamic banking institutions in Semarang City.Method - The data collection needed was done through interviews using questionnaires and analysed using a regression test approach to test the effect between variables and a comparative test to examine differences in work discipline behaviour based on gender.Result - The results of the tests carried out in this study indicate that employee work discipline can be explained by supervision and leadership. This study also shows that there are no differences in work discipline for male and female employees who work in Islamic banking institutions in Semarang City.Implication - There is no difference in work discipline for male and female employees, so to improve work discipline, it is done by increasing supervision and leadership that applies fairly and equitably to male and female employees.Originality- Variables developed to explain work discipline behavior based on the results of previous research and have relevance to empirical phenomena. This study was also conducted a comparative study of work discipline behavior based on gender which had never been done in previous research.
SELECTIVE REINFORCEMENT OF JOINING INTERFACE USING NANOFIBERS IN SINGLE-LAP JOINTS OF THERMOPLASTIC COMPOSITES FABRICATED BY THE INJECTION OVERMOLDING PROCESS: CREEP DEFORMATION BEHAVIOUR

An injection overmolding process enables molding and welding at the same time: a discontinuous fiberreinforced thermoplastic is injected onto the thermoformed continuous fiber-reinforced thermoplastic composites for the fabrication of complex shape parts, namely, ribs and bosses. Since the joining strength is significantly influenced by process parameters, such as resin temperature and molding pressure during the overmolding process, achieving reliable joining strength is important for increasing the load bearing capacity. The nanofibers have great potential to increase the toughness of fiber reinforced composites as secondary reinforcement. Furthermore, selective reinforcement is allowed by nanofiber addition in the matrix onto the fiber surface or interlaminar region of laminated composites. Thus, we previously proposed the selective addition of nanofillers at the joining interfaces to increase the joining strength. In this study, we attempt to reveal the effect of cellulose nanofiber (CNF) addition on creep properties for long-term use under constant load. The shear creep test was conducted under various loads and various temperatures using a self-designed fixture. Furthermore, the debonded surface of a single lap joint was observed by optical microscopy and scanning electron microscopy. We discovered that 1.0 wt% CNF addition increased the creep failure time and decreased the creep strain at the same load. Furthermore, the creep rate was significantly decreased by CNF addition regardless of temperature.
Dynamic experience of spaciousness, surprise and preference through indoor spaces (Experiencia dinámica de espaciosidad, sorpresa y preferencia en espacios interiores)

ABSTRACT In theory, preference should increase with spaciousness and moderate surprise, levelling off or decreasing for high surprise. To test this we created three simulated indoor spaces — SMALL (smallest size, dimmest light, smallest window), MEDIUM (medium size, light and window size) and LARGE (largest size, brightest light, largest windows) — and virtual reality walks through each possible pair of spaces. Three groups of 30 students (46 men, 44 women) rated either spaciousness, surprise or preference. Manipulation checks confirmed postulated effects of SMALL, MEDIUM and LARGE on judged spaciousness and of the size of the discrepancy between each pair of spaces on judged surprise. For preference, participants rated a space as more preferred if preceded by a smaller space and less preferred if preceded by a larger one. Preference also increased from low to moderate surprise but decreased slightly for high surprise. Research could consider adult responses to real spaces. Designers would do well to consider dynamic experience.
β2-Microglobulin exacerbates neuroinflammation, brain damage, and cognitive impairment after stroke in rats

β2-Microglobulin (β2M), a component of the major histocompatibility complex class I molecule, is associated with aging-related cognitive impairment and Alzheimer’s disease. Although upregulation of β2M is considered to be highly related to ischemic stroke, the specific role and underlying mechanistic action of β2M are poorly understood. In this study, we established a rat model of focal cerebral ischemia by occlusion of the middle cerebral artery. We found that β2M levels in the cerebral spinal fluid, serum, and brain tissue were significantly increased in the acute period but gradually decreased during the recovery period. RNA interference was used to inhibit β2M expression in the acute period of cerebral stroke. Tissue staining with 2,3,5-triphenyltetrazolium chloride and evaluation of cognitive function using the Morris water maze test demonstrated that decreased β2M expression in the ischemic penumbra reduced infarct volume and alleviated cognitive deficits, respectively. Notably, glial cell, caspase-1 (p20), and Nod-like receptor pyrin domain containing 3 (NLRP3) inflammasome activation as well as production of the inflammatory cytokines interleukin-1β, interleukin-6, and tumor necrosis factor-α were also effectively inhibited by β2M silencing. These findings suggest that β2M participates in brain injury and cognitive impairment in a rat model of ischemic stroke through activation of neuroinflammation associated with the NLRP3 inflammasome.
Automated Video-Based Air Traffic Surveillance System for Counting General Aviation Aircraft Operations at Non-Towered Airports

The vast majority of U.S. airports are not equipped with control towers, which limits their ability to keep records of flight operations. Attempts have been made to use sensor-based technologies to count aircraft operations at non-towered airports; however, they exhibit limited accuracy. To this end, we developed an automated video-based surveillance system capable of detecting general aviation aircraft departure and landing operations, which comprise the vast majority of operations at non-towered airports. The proposed computer vision method is comprised of three modules: aircraft detection, aircraft tracking, and operations count and classification. We explored different camera layouts and state-of-the-art machine learning and deep learning methods to determine the best settings to extract operations trajectory features for operations count and classification. The proposed method was tested at five non-towered airports. Integrating deep-neural-network-based aircraft detectors and image-correlation-based aircraft trackers achieved an accuracy of about 95%, while ensuring processing times that are needed for real-time implementation.