Miracle-dz/UniFAR-FTUs huggingface dataset:
Morphometry: Assessing Direct and Indirect Methods of Measuring the Diameters of Tubular Structures

Assessing direct and indirect methods of measuring the diameters of tubular structures. Int. J. 40(2) :314-319, 2022. SUMMARY: Knowledge of the diameter of a structure or particle is required for stereological calculations. However, there is no consensus on the methodology for its measurement. This study aims to assess the differences between direct and indirect methods of measuring diameter. It is hypothesised that kidneys were removed, fixed, processed, sectioned, and stained. The stained slides were imaged using a digital microscope. The images were processed using the ImageJ software. The diameters of the renal glomeruli and collecting tubules were measured using direct and indirect methods. The measured diameters were analysed using the SPSS software v20. The differences between the measurements were assessed using a Z-test and test of association, and P < 0.05 was considered significant. No significant differences were observed between the diameters of the glomeruli (P = 0.82) and proximal (P = 0.86) and distal (P = 0.55) convoluted tubules as measured via direct and indirect methods. There was a strong positive correlation between the diameters of glomeruli (P = 0.97) and proximal (P = 0.82) and distal (P = 0.93) convoluted tubules measured using the two methods, both of which are convenient, accurate and suitable. The P-values based on these measurements were more than 0.05. Therefore, the study hypothesis was rejected. There was no significant difference between the direct and indirect methods of measuring diameter, and the null hypothesis was rejected; thus, both methods can be applied either independently or jointly. distal; Convoluted tubules.
The Integrated Performance Modeling Environment a Tool for Simulating Human-System Performance

THE INTEGRATED PERFORMANCE MODELING ENVIRONMENT (IPME) The UK Centre for Human Sciences (CHS), DERA and Micro Analysis and Design have collaborated to develop a more complete environment for modeling human performance than has been available in the past. The first version of this tool was released in October 1996 and there are ongoing enhancements. In essence, we are seeking to take advantage of the base of human performance modeling technologies that have evolved over the past ten years, synthesize these technologies, and build significantly from that base. In this paper, we will discuss the base technologies (Micro Saint and Human Operator Simulator (HOS)) that have gone into IPME and then discuss some of the additional human performance modeling features that have been built into IPME to date and some that are planned.
Physiological characterisation of the calcified alga Corallina officinalis (Rhodophyta) from the leading to trailing edge in the Northeast Atlantic

Abstract Intertidal macroalgae are exposed to many biotic and abiotic stressors, including significant fluctuations in environmental parameters such as salinity, temperature, pH and solar radiation. This study characterized populations of the intertidal calcifying red alga Corallina officinalis across its geographic distribution in the North-east Atlantic. Processes examined included primary production, respiration, light and dark calcification, photosynthesis-irradiance, and calcification-irradiance evolution. Results confirmed significant differences in the physiology of C. officinalis between latitudes with a clear north-to-south gradient. Compared with central and southern populations of this species, northern populations appeared to be the most robust, showing potential for local physiological adaptation in response to increased variability in environmental factors present within their habitat. Conversely, southern populations displayed a distinct lack of local adaptation compared with northern populations. This is possibly due to southern populations being located within an environment at the upper limit of their stress tolerance, therefore restricting the species’ ability to adapt. As a result, future permanent decline, or even disappearance, of C. officinalis within southern locations of the North-east Atlantic could occur, a process that is likely to be accelerated by predicted future climatic changes. Furthermore, given the essential role these ecosystem engineers play within their habitat, any loss of C. officinalis is also expected to have a strongly negative impact on the surrounding environment. HIGHLIGHTS Decoupled photosynthesis and calcification in Corallina. officinalis show complex relationships, not direct dependencies. Most physiological characteristics in northern C. officinalis populations differ significantly from those in central and southern locations. Species adaptation is predominantly to lower light and temperature conditions.
Numerical Simulation Study on the Flow and Heat Transfer Characteristics of Subcooled N-Heptane Flow Boiling in a Vertical Pipe under External Radiation

In the top submerged lance (TSL) smelting process, flow boiling may occur in the lance’s inner pipe due to the heat coming from the furnace when liquid fuel is adopted. In the current study, a numerical simulation was carried out by coupling the Eulerian two-fluid model with the improved RPI wall boiling model to investigate the subcooled n-heptane flow boiling in the inner pipe. The effects of inlet velocity and pipe wall emissivity on two-phase flow and heat transfer are elucidated. The results show that, for pipes with inlet velocity ranging from 0.3 m·s−1 to 1.0 m·s−1, an increase in inlet velocity leads to a lower void fraction near the outlet, as well as a lower average velocity and a lower average temperature of each phase. Meanwhile, the Onset of Nucleate Boiling (ONB) position approaches to the outlet, and the total pressure drop of the entire pipe reduces when the inlet velocity increases. However, the opposite trends appear when increasing the pipe wall emissivity. The maximum wall temperature corresponding to the critical heat flux (CHF) point is slightly affected by inlet velocity but significantly affected by pipe wall emissivity. The non-equilibrium effect and the specific components of pressure drop are also further investigated.
Multiple species delimitation approaches with COI barcodes poorly fit each other and morphospecies – An integrative taxonomy case of Sri Lankan Sericini chafers (Coleoptera: Scarabaeidae)

Abstract DNA taxonomy including barcoding and metabarcoding is widely used to explore the diversity in biodiversity hotspots. In most of these hotspot areas, chafers are represented by a multitude of species, which are well defined by the complex shape of male genitalia. Here, we explore how well COI barcode data reflect morphological species entities and thus their usability for accelerated species inventorization. We conducted dedicated field surveys in Sri Lanka to collect the species‐rich and highly endemic Sericini chafers (Coleoptera: Scarabaeidae). Congruence among results of a series of protocols for de novo species delimitation and with morphology‐based species identifications was investigated. Different delimitation methods, such as the Poisson tree processes (PTP) model, Statistical Parsimony Analysis (TCS), Automatic Barcode Gap Discovery (ABGD), Assemble Species by Automatic Partitioning (ASAP), and Barcode Index Number (BIN) assignments, resulted in different numbers of molecular operational taxonomic units (MOTUs). All methods showed both over‐splitting and lumping of morphologically identified species. Only 18 of the observed 45 morphospecies perfectly matched MOTUs from all methods. The congruence of delimitation between MOTUs and morphospecies expressed by the match ratio was low, ranging from 0.57 to 0.67. TCS and multirate PTP (mPTP) showed the highest match ratio, while (BIN) assignment resulted in the lowest match ratio and most splitting events. mPTP lumped more species than any other method. Principal coordinate analysis (PCoA) on a match ratio‐based distance matrix revealed incongruent outcomes of multiple DNA delimitation methods, although applied to the same data. Our results confirm that COI barcode data alone are unlikely to correctly delimit all species, in particular, when using only a single delimitation approach. We encourage the integration of various approaches and data, particularly morphology, to validate species boundaries.
An Extensive Assessment of Network Embedding in PPI Network Alignment

Network alignment is a fundamental task in network analysis. In the biological field, where the protein–protein interaction (PPI) is represented as a graph, network alignment allowed the discovery of underlying biological knowledge such as conserved evolutionary pathways and functionally conserved proteins throughout different species. A recent trend in network science concerns network embedding, i.e., the modelling of nodes in a network as a low-dimensional feature vector. In this survey, we present an overview of current PPI network embedding alignment methods, a comparison among them, and a comparison to classical PPI network alignment algorithms. The results of this comparison highlight that: (i) only five network embeddings for network alignment algorithms have been applied in the biological context, whereas the literature presents several classical network alignment algorithms; (ii) there is a need for developing an evaluation framework that may enable a unified comparison between different algorithms; (iii) the majority of the proposed algorithms perform network embedding through matrix factorization-based techniques; (iv) three out of five algorithms leverage external biological resources, while the remaining two are designed for domain agnostic network alignment and tested on PPI networks; (v) two algorithms out of three are stated to perform multi-network alignment, while the remaining perform pairwise network alignment.
Coral Reef Bleaching under Climate Change: Prediction Modeling and Machine Learning

The coral reefs are important ecosystems to protect underwater life and coastal areas. It is also a natural attraction that attracts many tourists to eco-tourism under the sea. However, the impact of climate change has led to coral reef bleaching and elevated mortality rates. Thus, this paper modeled and predicted coral reef bleaching under climate change by using machine learning techniques to provide the data to support coral reefs protection. Supervised machine learning was used to predict the level of coral damage based on previous information, while unsupervised machine learning was applied to model the coral reef bleaching area and discovery knowledge of the relationship among bleaching factors. In supervised machine learning, three widely used algorithms were included: Naïve Bayes, support vector machine (SVM), and decision tree. The accuracy of classifying coral reef bleaching under climate change was compared between these three models. Unsupervised machine learning based on a clustering technique was used to group similar characteristics of coral reef bleaching. Then, the correlation between bleaching conditions and characteristics was examined. We used a 5-year dataset obtained from the Department of Marine and Coastal Resources, Thailand, during 2013–2018. The results showed that SVM was the most effective classification model with 88.85% accuracy, followed by decision tree and Naïve Bayes that achieved 80.25% and 71.34% accuracy, respectively. In unsupervised machine learning, coral reef characteristics were clustered into six groups, and we found that seawater pH and sea surface temperature correlated with coral reef bleaching.
Graduates Employability Skills and Placements - Mediating Role of Career Adaptability

This paper focused on examining the relationship exist between psychosocial variables, employability skills and career adaptability for procuring placements among management graduates; to ascertain the mediating effect of career adaptability skills in the relationship between employability skills and placements. The study opt, cross-sectional design. Data were gathered from management graduates (N=207), placed in varied job settings through academic placements. Hierarchical regression were performed to accomplish objectives of the study. The results showed positive and significant correlation among employability, career adaptability towards procuring placements. Further describes partial mediation effect of career adaptability in relationship between employability and placements obtained among graduates. The results proposes that management graduates need to possess more adaptability skills compared to employability skills in order to secure employment through placements. The career adaptability dimensions: control, curiosity, concern, confidence and major employability skills can be enhanced by providing academic workshops and training interventions to management graduates.
Digital Startups Fundamental Capabilities in New Product Development: Multiple Case Studies in Bandung, Indonesia

Digital startups compete by increasing their ability to innovate in new product development. New product development becomes one of the main processes for startups to scale their product quality. As there are many frameworks of new product development to follow, the particular new product development in digital startups should be established to contribute to the theory. Therefore, the research question of this study is: What are the fundamental capabilities of new product development in digital startups. This research uses the exploratory study approached by qualitative research, interviewing at least CEOs of four digital startups in Indonesia and a technology-based new ventures expert. From the study, there are three influential capabilities in the new product development in digital startups, such as financial, market, and technology. The connection between capabilities contributes to the theoretical framework. The implication of this study is to help practitioners to conduct an ideal new product development process. Keywords—Digital Startups ; Financial Capability; Market Capability; New Product Development; Technology Capability.
Optimal Sensor Placement for Modal-Based Health Monitoring of a Composite Structure

Optimal sensor placement is one of the important issues in monitoring the condition of structures, which has a major influence on monitoring system performance and cost. Due to this, it is still an open problem to find a compromise between these two parameters. In this study, the problem of optimal sensor placement was investigated for a composite plate with simulated internal damage. To solve this problem, different sensor placement methods with different constraint variants were applied. The advantage of the proposed approach is that information for sensor placement was used only from the structure’s healthy state. The results of the calculations according to sensor placement methods were subsets of possible sensor network candidates, which were evaluated using the aggregation of different metrics. The evaluation of selected sensor networks was performed and validated using machine learning techniques and visualized appropriately. Using the proposed approach, it was possible to precisely detect damage based on a limited number of strain sensors and mode shapes taken into consideration, which leads to efficient structural health monitoring with resource savings both in costs and computational time and complexity.
Neoadjuvant chemotherapy with quick cisplatin-VP 16 followed by robotic radical trachelectomy in FIGO 2018 stage 1B2 cervical cancer

Background : The typical treatment of the International Federation of Gynecology and Obstetrics 2018 stage IB2 cervical cancer is radical hysterectomy. With the trend of delayed childbearing, the importance of fertility sparing in the treatment of women with cervical cancer has drawn attention. Case : We report a case of stage IB2 cervical cancer treated by neoadjuvant chemotherapy with quick cisplatin-VP 16 followed by robotic radical trachelectomy. Conclusions : Neoadjuvant chemotherapy (NACT) using platinum-based therapy with cisplatin and trachelectomy performed through the vagina or abdominal approach was used in most previous cases. We successfully performed NACT with quick cisplatin-VP 16, followed by robotic radical trachelectomy in stage 1B2 cervical cancer. Further studies are needed to accumulate
Computational optics for high-throughput imaging of neural activity

Abstract. Optical microscopy offers a noninvasive way to image neural activity in the mouse brain. To simultaneously record neural activity across a large population of neurons, optical systems that have high spatiotemporal resolution and can access a large volume are necessary. The throughput of a system, that is, the number of resolvable spots acquired by the system at a given time, is usually limited by optical hardware. To overcome this limitation, computation optics that designs optical hardware and computer software jointly becomes a new approach that achieves micronscale resolution, millimeter-scale field-of-view, and hundreds of hertz imaging speed at the same time. This review article summarizes recent advances in computational optics for high-throughput imaging of neural activity, highlighting technologies for three-dimensional parallelized excitation and detection. Computational optics can substantially accelerate the study of neural circuits with previously unattainable precision and speed.
The Effect of Tailored, Daily, Smartphone Feedback to Lifestyle Self-Monitoring on Weight Loss at 12 Months: the SMARTER Randomized Clinical Trial

Background Self-monitoring (SM) is the centerpiece of behavioral weight loss treatment, but the efficacy of smartphone-delivered SM feedback (FB) has not been tested in large, long-term, randomized trials. Objective The aim of this study was to establish the efficacy of providing remote FB to diet, physical activity (PA), and weight SM on improving weight loss outcomes when comparing the SM plus FB (SM+FB) condition to the SM-only condition in a 12-month randomized controlled trial. The study was a single-site, population-based trial that took place in southwestern Pennsylvania, USA, conducted between 2018 and 2021. Participants were smartphone users age ≥18 years, able to engage in moderate PA, with a mean BMI between 27 and 43 kg/m2. Methods All participants received a 90-minute, one-to-one, in-person behavioral weight loss counseling session addressing behavioral strategies, establishing participants’ dietary and PA goals, and instructing on use of the PA tracker (Fitbit Charge 2), smart scale, and diet SM app. Only SM+FB participants had access to an investigator-developed smartphone app that read SM data, in which an algorithm selected tailored messages sent to the smartphone up to 3 times daily. The SM-only participants did not receive any tailored FB based on SM data. The primary outcome was percent weight change from baseline to 12 months. Secondary outcomes included engagement with digital tools (eg, monthly percentage of FB messages opened and monthly percentage of days adherent to the calorie goal). Results Participants (N=502) were on average 45.0 (SD 14.4) years old with a mean BMI of 33.7 (SD 4.0) kg/m2. The sample was 79.5% female (n=399/502) and 82.5% White (n=414/502). At 12 months, retention was 78.5% (n=394/502) and similar by group (SM+FB: 202/251, 80.5%; SM: 192/251, 76.5%; P=.28). There was significant percent weight loss from baseline in both groups (SM+FB: –2.12%, 95% CI –3.04% to –1.21%, P<.001; SM: –2.39%, 95% CI –3.32% to –1.47%; P<.001), but no difference between the groups (–0.27%; 95% CI –1.57% to 1.03%; t =–0.41; P=.68). Similarly, 26.3% (66/251) of the SM+FB group and 29.1% (73/251) of the SM group achieved ≥5% weight loss (chi-square value=0.49; P=.49). A 1% increase in FB messages opened was associated with a 0.10 greater percent weight loss at 12 months (b=–0.10; 95% CI –0.13 to –0.07; t =–5.90; P<.001). A 1% increase in FB messages opened was associated with 0.12 greater percentage of days adherent to the calorie goal per month (b=0.12; 95% CI 0.07-0.17; F=22.19; P<.001). Conclusions There were no significant between-group differences in weight loss; however, the findings suggested that the use of commercially available digital SM tools with or without FB resulted in a clinically significant weight loss in over 25% of participants. Future studies need to test additional strategies that will promote greater engagement with digital tools. Trial Registration Clinicaltrials.gov NCT03367936; https://clinicaltrials.gov/ct2/show/NCT03367936
Research Status and Development Tendency of Well Location Layout Technology of CBM Development in Mining Area Surface Wells

With the high strength of coal mining,the underground gas drainage is not sufficient to solve the problem of the gas.The research of surface borehole drilling extraction has been becoming a hot spot in domestic.Through sorting out and analyzing the related surface borehole drilling material of domestic mining area,the paper demonstrates the mechanism of surface borehole drilling extraction pressure released gas of the mining area,pointes out the research situation of current mining area surface borehole drilling technology.The paper points that utilizing the relation among stress fields,seepage field and fractures field,considering the system research of surface drilling control range of different mines and different geological condition will provide theoretical support for stope strike separation layout of surface drilling in mining area.
Pedestal High-Contrast Gratings for Biosensing

High-contrast gratings (HCG) are an excellent candidate for label-free detection of various kinds of biomarkers because they exhibit sharp and sensitive optical resonances. In this work, we experimentally show the performance of pedestal HCG (PHCG), which is significantly enhanced in comparison with that of conventional HCG. PCHGs were found to provide a 11.2% improvement in bulk refractive index sensitivity, from 482 nm/RIU for the conventional design to 536 nm/RIU. The observed resonance was narrower, resulting in a higher Q-factor and figure of merit. By depositing Al2O3, HfO2, and TiO2 of different thicknesses as model analyte layers, surface sensitivity values were estimated to be 10.5% better for PHCG. To evaluate the operation of the sensor in solution, avidin was employed as a model analyte. For avidin detection, the surface of the HCG was first silanized and subsequently functionalized with biotin, which is well known for its ability to bind selectively to avidin. A consistent red shift was observed with the addition of each of the functional layers, and the analysis of the spectral shift for various concentrations of avidin made it possible to calculate the limit of detection (LoD) and limit of quantification (LoQ) for the structures. PHCG showed a LoD of 2.1 ng/mL and LoQ of 85 ng/mL, significantly better than the values 3.2 ng/mL and 213 ng/mL respectively, obtained with the conventional HCG. These results demonstrate that the proposed PHCG have great potential for biosensing applications, particularly for detecting and quantifying low analyte concentrations.