Miracle-dz/UniFAR-FTUs huggingface dataset:
Current methods and new approaches to assess aqueous humor dynamics

ABSTRACT Introduction: Aqueous humor and its dynamics (AHD) serve numerous functions to sustain ocular health and clear vision. Current methods to assess AHD have led to improved understanding of ocular physiology, pathologies caused by abnormal intraocular pressures (IOP), and treatments to return IOP to healthy levels. However, the assumptions and limitations inherent in these methods have been problematic. New methods on the horizon are showing promise to greatly advance the field. Areas covered: This review summarizes AHD assessment techniques in use today including the noninvasive methods of fluorophotometry, tonometry, tonography, venomanometry, and invasive methods of cannulation, infusion, dissection. It also mentions emerging methods utilizing advanced imaging methods, smart phones, cameras, and software. Expert opinion: Soon new techniques will become available to measure each parameter and even subparts of each parameter of AHD with increased speed, accuracy, and safety. Along with these new methods and the data they generate could emerge the next version of the Goldmann Equation. These new methods would make AHD an important tool in the clinic for precision medicine and in the lab for exploring AHD on a new level.
Metagenome-validated Parallel Amplicon Sequencing and Text Mining-based Annotations for Simultaneous Profiling of Bacteria and Fungi: Vaginal Microbiome and Mycobiota in Healthy Women

Background: Amplicon sequencing of kingdom-specific tags such as 16S rRNA gene for bacteria and internal transcribed spacer (ITS) region for fungi are widely used for investigating microbial populations. So far most human studies have focused on bacteria while studies on host-associated fungi in health and disease have only recently started to accumulate. To enable cost-effective parallel analysis of bacterial and fungal communities in human and environmental samples, we developed a method where 16S rRNA gene and ITS-1 amplicons were pooled together for a single Illumina MiSeq or HiSeq run and analysed after primer-based segregation. Taxonomic assignments were performed with Blast in combination with an iterative text-extraction based filtration approach, which uses extensive literature records from public databases to select the most probable hits that were further validated by shotgun metagenomic sequencing. Results: Using 50 vaginal samples, we show that the combined run provides comparable results on bacterial composition and diversity to conventional 16S rRNA gene amplicon sequencing. The text-extraction-based taxonomic assignment guided tool provided ecosystem specific annotations that were confirmed by Metagenomic Phylogenetic Analysis (MetaPhlAn). The metagenome analysis revealed distinct functional differences between the bacterial community types while fungi were undetected, despite being identified in all samples based on ITS amplicons. Co-abundance analysis of bacteria and fungi did not show strong between-kingdom correlations within the vaginal ecosystem of healthy women.Conclusion: Combined amplicon sequencing for bacteria and fungi provides a simple and cost-effective method for simultaneous analysis of microbiota and mycobiota within the same samples. Text extraction-based annotation tool facilitates the characterization and interpretation of defined microbial communities from rapidly accumulating sequencing and metadata readily available through public databases.
Palynology and Sedimentology of the Pliocene Productive Series from Eastern Azerbaijan

ABSTRACT A palynological study of 239 outcrop samples and their sedimentological context was undertaken on the Pliocene Productive Series in the Kirmaky and Yasamal valleys, eastern Azerbaijan. The Productive Series is primarily a representation of the palaeo-Volga and forms the main hydrocarbon-producing reservoirs in the South Caspian Basin. Most sands are interpreted as fluvial, based on sedimentary characteristics. Mudstone and siltstones often contain freshwater and brackish assemblages interpreted as ‘Caspian lake’ transgressions, indicative of rapid Caspian Sea level change during the Pliocene. Most samples contain rich assemblages including pollen, spores, dinoflagellate cysts, algae and fungal bodies. Common tree pollen elements include Pinus, Alnus, Betula, Carya, Juglans, Pterocarya, Quercus and Ulmus, which all occur in present-day vegetation or pollen records from the Caucasus or Urals. Herbaceous pollen includes Amaranthaceae, Asteraceae (including Artemisia), Ephedra and Poaceae, commonly found in the drier Caspian regions. The dinoflagellate cysts include ‘Peri-paratethyan endemic’ taxa such as Caspidinium rugosum and Spiniferites cruciformis. ‘Pannonian’ species such as Thalassiphora balcanica, Romanodinium areolatum and Spiniferites oblongus confirm the persistence of these taxa into the early Pliocene in Eastern Paratethys, around five million years later than their first documented presence in Central Paratethys. ‘Caspian lake’ influences diminish up-section, as indicated by a progression from brackish to freshwater and sub-aerial conditions. Productive Series deposition was mainly driven by the combined effects of lake level and catchment climate. The principal hydrocarbon reservoir sands were deposited as a result of increased catchment humidity, whereas drying conditions led to reduced coarse clastic input and deposition of alluvial plain mudstones. Productive Series deposition terminated with the onset of the marine-influenced Akchagyl Series, which spans the Plio-Pleistocene boundary. The lowermost sediments of the Akchagyl Series are freshwater in origin and grade up-section into marine beds containing dinoflagellate cysts of Arctic affinity.
Empowered or patronized? The role of emotions in policies and professional discourses on birth care

While the focus on emotions has been associated with the rise of psychosocial welfare and has promised a gateway to accommodate individually diversified needs of citizens in policies, the article shows that the role of emotions needs to be better understood. Highlighting emotions can serve both to empower and to patronize those who experience them. Referring to emotions can thus strengthen hierarchies and downplay individual requests to initiate a change. The analysis of professional discourses on birth care in Czechia shows the value of contextualising emotions. While midwifery discourses apply the emotional context of birth to support women in their specific birth choices, medical discourses use the emotional context to patronize them and to limit their requirements. As a result, policy demands are seen as illegitimate when coming from midwives, who want to see women’s choices more respected in care. We analyse this dynamic through intimacy. As a conceptual framework used in sociology of care, ‘intimacy’ ties individual emotional experiences to collective discourses on care, the body and related feelings. Viewing professional discourses on birth care through intimacy reveals the role of emotions in the collective recognition of the personal struggle for the right to give birth in conditions that respect bodily and emotional integrity, which informs how we think of the role of emotions in policies in general.
Leading at the crossroads: Understanding how identity influences presidential communication for Black community college presidents

Research on leadership is historically biased, with little consideration for different experiences of leaders of color. In this study, we applied the integrated race and leadership framework (Ospina & Foldy, 2009) and utilized a case study approach focused on the context of institutional communication to analyze the experiences of six Black community college presidents. The study was guided by the overarching question of how Education Policy Analysis Archives Vol. 29 No. 39 SPECIAL ISSUE 2 racial identity guided what and how presidents communicated. Our findings indicate that these presidents of color viewed their communication through a social justice lens, while also recognizing their responsibility to the institution. Five themes were identified that highlight the strategies and approaches these presidents take when communicating to their campus, including: 1) a consciousness of who is listening, 2) a sense of racial battle fatigue, 3) a focus on local impact, 4) connection and support from the community, and 5) the skill of racial and social adaptation.
Improving the Production of Riboflavin by Introducing a Mutant Ribulose 5-Phosphate 3-Epimerase Gene in Bacillus subtilis

Ribulose 5-phosphate (Ru5P) and guanosine 5′-triphosphate (GTP) are two key precursors of riboflavin, whereby Ru5P is also a precursor of GTP. Ribulose 5-phosphate 3-epimerase (Rpe) catalyzes the conversion of ribulose 5-phosphate into xylulose 5-phosphate. Inactivation of Rpe can reduce the consumption of Ru5P, enhancing the carbon flux toward riboflavin biosynthesis. Here we investigated the effect of mutation of rpe and other related genes on riboflavin production, physiological and metabolic phenotypes in Bacillus subtilis LY (BSLY). Introducing single nucleotide deletion (generated BSR) or nonsense mutation (generated BSRN) on the genomic copy of rpe, resulting in more than fivefold increase of riboflavin production over the parental strain. BSR process 62% Rpe activity, while BSRN lost the entire Rpe activity and had a growth defect compared with the parent strain. BSR and BSRN exhibited increases of the inosine and guanine titers, in addition, BSRN exhibited an increase of inosine 5′-monophosphate titer in fermentation. The transcription levels of most oxidative pentose phosphate pathway and purine synthesis genes were unchanged in BSR, except for the levels of zwf and ndk, which were higher than in BSLY. The production of riboflavin was increased to 479.90 ± 33.21 mg/L when ribA was overexpressed in BSR. The overexpression of zwf, gntZ, prs, and purF also enhanced the riboflavin production. Finally, overexpression of the rib operon by the pMX45 plasmid and mutant gnd by pHP03 plasmid in BSR led to a 3.05-fold increase of the riboflavin production (977.29 ± 63.44 mg/L), showing the potential for further engineering of this strain.
The Effectiveness of Acceptance and Commitment Therapy and Combined with Aerobic Training on Anxiety Symptoms, Insulin Resistance and Lipid Profile in Women with Type 2 Diabetes

iabetes is a non-communicable disease with a silent epidemic and can have a profound effect on a person’s individual, social, and psychological functioning (1). Hyperglycemia is caused by impairments in insulin secretion and insulin D 1. PhD Student, Department of Psychology, Tabriz Branch, Islamic Azad University, Tabriz, Iran. 2. Department of Psychology, Tabriz Branch, Islamic Azad University, Tabriz, Iran. 3. Department of Exercise Physiology, South Tehran Branch, Islamic Azad University, Tehran, Iran. 4. Internal Department, Endocrinologist and Member of Endocrine Research Center, Associate Professor, Tabriz Branch, University of Medical Sciences, Tabriz, Iran.
Cryptocurrency direction forecasting using deep learning algorithms

Recently, the deep learning architecture has been used with an increasing rate for forecasting in financial markets. In this paper, the LSTM model is used to forecast the daily closing price direction of the BTC/USD. Both model accuracy and the profit or loss of the trades made based on the proposed model are analyzed. In addition, the effects of the MACD indicator and the input matrix dimension on forecasting accuracy are evaluated. The potential risks and actual risks encountered by the trader who trades based on the proposed model were also analyzed. The obtained results indicate that the optimization of the LSTM parameters using the Bayesian optimization model has enhanced the model’s accuracy. The results obtained from analyzing the drawdown and reward/risk resulting from the trades made based on the model show that the model enables the trader to trade with peace of mind due to the low level of actual risks and potential risks.
Factorial and criterion validity of the Role Ambiguity Scale – Brief (RASB) in team sport contexts

ABSTRACT Role clarity/ambiguity represents the degree to which group members understand their role responsibilities within their group. Previous research has shown that greater role clarity perceptions held by athletes are associated with numerous adaptive outcomes. Most research in this area has used the Role Ambiguity Scale (RAS) to assess role clarity; however, its length (i.e., 40 items) poses practical challenges. In addition, previous research has provided mixed findings regarding the factor structure of role clarity assessed based on responses to the RAS. The purpose of the present study was to evaluate a 12-item measure of role clarity in team sport contexts (Role Ambiguity Scale-Brief; RASB). Based on data from 440 current or former competitive interdependent sport athletes, exploratory structural equation modelling was used to examine the factor structure of role clarity assessed through responses to the RASB. Measurement invariance was tested in terms of gender, starting status, participation status (i.e., current vs. former athletes), and age group (i.e., youth vs. adult). Criterion validity was assessed by examining whether dimensions of role clarity predicted dimensions of role satisfaction. The results provided support for a three-factor structure of role clarity that included dimensions of role scope/behaviour, role evaluation, and role consequences. Measurement invariance was also supported. The dimensions of role clarity accounted for substantial variance in all dimensions of role satisfaction, demonstrating evidence of criterion validity. Overall, the RASB provides an option for researchers to assess athletes’ role clarity in a concise manner.
A Proposed Speaker Recognition Method B Based on Long-Term Voice Features and Fuzzy Logic

Speaker recognition depends on specific predefined steps. The most important steps are feature extraction and features matching. In addition, the category of the speaker voice features has an impact on the recognition process. The proposed speaker recognition makes use of biometric (voice) attributes to recognize the identity of the speaker. The long-term features were used such that maximum frequency, pitch and zero crossing rate (ZCR). In features matching step, the fuzzy inner product was used between feature vectors to compute the matching value between a claimed speaker voice utterance and test voice utterances. The experiments implemented using (ELSDSR) data set. These experiments showed that the recognition accuracy is 100% when using text dependent speaker recognition.
Corn silk methanolic extract improves oxidative stress and inflammatory responses in rats’ excision wound model

Anti-inflammatory and antioxidant activities of corn silk (Stigma maydis of Zea mays L.) extract were investigated in excision wound model. Twenty male Wistar rats (130-150g) were grouped into four (n=5/group): Control rats received 0.5 mL distilled water, the experimental groups received distilled water (0.5 mL), aqueous corn-silk extract (ACSE; 500 mg/kg) and methanolic corn-silk extract (MCSE; 500 mg/kg), twice/day orally, three weeks before and three weeks after they had 1.5 × 1.0 cm excision wound. Rats were sacrificed and blood was collected. Serum was separated while wound tissues were removed, homogenised and supernatant was stored. Antioxidant enzymes, malondialdehyde, hydroxyproline, cyclooxygenase-2 and NO were measured in wound tissues colorimetrically, while serum cytokines were measured using enzyme linked immunosorbent assay. MCSE significantly (p˂0.05) increased glutathione peroxidase, superoxide dismutase, catalase, hydroxyproline and total protein content but decreased significantly (p˂0.05) malondialdehyde, cyclooxygenase-2, IL-1β, TNF-α, and IFN-γ when compared with untreated wound. ACSE increased significantly (p<0.05) glutathione peroxidase and superoxide dismutase but decreased significantly (p<0.05) malondialdehyde and cyclooxygenase-2. However, it produced no significant effect on catalase, IL-1β, TNF-α, and IFN-γ when compared with untreated wound. MCSE attenuated oxidative and inflammatory responses in excision wound rat model.
First-principles study of mechanical and thermodynamic properties of W-V alloys

The lattice structure, mechanical properties, electronic structure and thermodynamic properties of W1−xVx alloys (x = 0, 0.0625, 0.125, 0.25, 0.3125, 0.5 and 1) were calculated and simulated by first-principles method based on DFT. The mechanical properties including Poisson’s ratio, elastic moduli and B/G ratio were analysed via V concentration. The simulated results showed the ductility of alloys getting improved while the strength decreased with the addition of vanadium. And we calculated the anisotropy of Young’s modules and ideal tensile strength. The projected density of states is calculated to analyse the electronic structure. Furthermore, thermodynamic properties like Debye temperature and low temperature heat capacity were also calculated in this work. All the results can provide reference for selecting plasma facing materials in fusion reactor design.
Computational Methods for Detecting Large-Scale Structural Rearrangements in Chromosomes

License: This open access article is licenced under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) https://creativecommons.org/licenses/by-nc/4.0/ Abstract: Large-scale structural chromosomal rearrangements or structural variants, such as insertions, deletions, translocations, and inversions may result in the exchange of coding or regulatory DNA/RNA sequences between genes, which can lead to gene fusion or the loss/gain of genetic material. Gene fusion events are common in multiple types of cancer. High-throughput DNA and RNA sequencing methods produce large amounts of genomic data. Due to the massive amounts of data and the fact that structural variants account for just a small fraction of the data, efficient and accurate search methods are required for the detection of chromosomal breakpoints and structural variations. Robust identification of structural variants remains paramount for accurate inference of long-range interactions from high-throughput chromosome conformation capture (Hi-C) data. This chapter is a survey of computational methods based on paired end reading, efficient search techniques and parallel computing to detect structural variants in both whole genome and transcriptome sequences, as well as Hi-C data.
Numerical study of activation energy and thermal radiation effects on Oldroyd‐B nanofluid flow using the Cattaneo–Christov double diffusion model over a convectively heated stretching sheet

This paper investigates a theoretical model of a mixed convective Oldroyd‐B nanofluid with thermal radiation and activation energy effects. A thorough analysis is done by employing the nonhomogeneous Buongiorno model in the presence of velocity slip and suction. The surface is porous in nature, and nanoparticle mass flux is maintained passively at the surface. The thermal and concentration equations are modeled with the Cattaneo–Christov theory of heat and mass flux, respectively. Proper transformations are utilized for the conversion of transport equations and boundary conditions. The similarity solution is obtained through a numerical approach by utilizing the Runge–Kutta–Fehlberg method and shooting technique. The vital outcomes of this study and the influence of controlling parameters on the flow field, temperature, and concentration profiles are discussed graphically and in a tabular manner. Furthermore, a detailed discussion is provided to explain the results physically. The velocity of the nanofluid increases when the porosity parameter is increased, and temperature decreases with increasing thermal relaxation parameter. The outcomes elucidate that the suction parameter, thermal radiation parameter, and thermal relaxation parameter are positively correlated with the heat transfer coefficient. The result of passive control of nanoparticles at the surface is that the Brownian motion parameter has no influence on the temperature of the Oldroyd‐B nanofluid flow and rate of heat transfer at the surface.
Cadmium stress causes differential effects on growth and the secretion of carbon-degrading enzymes in four mycorrhizal basidiomycetes

We hypothesised that cadmium exposure would hinder growth and secretion of carbon-degrading enzymes by mycorrhizal fungi, and that this would vary according to their tolerance to cadmium stress. The enzymes measured were β-Glucosidase, β-Xylosidase, β-D-cellubiosidase, N-acetyl-β-Glucosaminidase in three strains of ectomycorrhizal fungi Hebeloma subsaponaceum, Scleroderma sp. , Hebeloma sp. and a feremycorrhizal fungus Austroboletus occidentalis. Fungi were subjected to cadmium stress for 28 d (in modified Melin-Norkrans liquid medium). The results showed unanticipated differential response of enzyme activities among the fungal species, including potential hormesis effects. Austroboletus occidentalis showed an increase in enzyme activity under cadmium stress.
A Review on Condition Assessment Methods of Ball Bearing

A growing discipline, prognostics and health management, uses scientific methods to monitor the health of building systems and the vital parts that make them up. This area is made up of three main parts which are constructing health indicators, predicting Remaining Useful Life (RUL), and managing health. The goal of health indicators is to assess a system or component's current state. Accurately forecasting RUL is essential in determining when a system or component will stop working as intended, based on an evaluation of health indicators. Health management involves creating maintenance schedules, assessing the general health of a system, and determining the cost of replacing parts. Since bearings are crucial components of rotating machinery, vibration signals are frequently used to create bearing health indicators. Nonetheless, analyzing and measuring bearing health can be a complex process. This review paper assesses mechanical data processing, modeling, and machine learning methods for developing vibration-based bearing health indicators. It facilitates the creation of more complex bearing health metrics and gives a foundation for forecasting the RUL of bearings. Most of the above stated bearing indicators relate to laboratory run-to-failure data rather than synthetic bearing fault data.
Composite Error-Based Intelligent Adaptive Sliding Mode Control for Uncertain Bilaterally Symmetrical Hybrid Robot with Variational Desired Trajectories

Some challenging issues exist in trajectory tracking control of an uncertain bilaterally symmetrical hybrid robot (UBSHR) with variational desired trajectories, mainly the uncertainty problem of UBSHR, the synchronization problem of UBSHR’s active joints and bilateral symmetrical hybrid mechanisms, and the flexible control problem of active adaption to different technological requirements without artificially adjusting the control parameters or switching the hardware system. To solve these problems, an adaptive fuzzy neural network in conjunction with subtractive clustering algorithm (SC-AFNN) for UBSHR is proposed. More specifically, a novel composite error is incorporated into the second-order sliding mode control method to generate ideal training data samples and to improve the uncertain system robustness and synchronization performance simultaneously. Furthermore, the SC-AFNN is introduced to realize self-learning and self-adjusting of control rules and control parameters and to enhance the flexible control performance of UBSHR with variational desired trajectories. Strict theoretical proof of the defined errors’ relationship and the stability of the poposed control method is given. Ultimately, simulations and experiments for the prototype system of an UBSHR are conducted to verify the effectiveness of the proposed control method.