Miracle-dz/UniFAR-FTUs huggingface dataset:
Constraining the ocean's biological pump with in situ 1 optical observations and supervised learning. Part 2: 2 Carbon Flux

Export of sinking particles from the surface ocean is critical for carbon sequestration and for providing energy to the deep-ocean biosphere. The magnitude and spatial patterns of this flux have been estimated in the past by in situ flux observations, satellitebased algorithms, and ocean biogeochemical models; however, these estimates remain uncertain. Here, we use a novel machine learning reconstruction of global in situ ocean particle size spectra from Underwater Vision Profiler 5 (UVP5) measurements, to determine particulate carbon fluxes. We combine global maps of particle size distribution parameters for large sinking particles with observationally-constrained empirical relationships to calculate the sinking carbon flux from the euphotic zone and the wintertime mixed layer depth. Our flux reconstructions are comparable to prior estimates, but suggest a less variable seasonal cycle in the tropical ocean, and a more persistent export in the Southern Ocean than previously thought. Because our estimates are not bounded by a specific depth horizon, we reconstruct export at multiple depths, and find that export from the wintertime mixed layer globally exceeds that from the euphotic zone. Our estimates provide a baseline for more accurate understanding of particle cycles in the ocean, and open the way to fully three-dimensional global reconstructions of particle size spectra and fluxes in the ocean, supported by the growing database of optical observations.
Surface Characterisation of Human Serum Albumin Layers on Activated Ti6Al4V

Adpsortion of protein layers on biomaterials plays an important role in the interactions between implants and the bio-environment. In this context, human serum albumin (HSA) layers have been deposited on modified Ti6Al4V surfaces at different ultraviolet (UV-C) irradiation times to observe possible changes in the adsorbed protein layer. Protein adsorption was done from solutions at concentraions lower than the serum protein concentration, to follow the surface modifications at the beginning of the albumin adhesion process. For this purpose, the surface of the protein-coated samples has been characterized by time of flight secondary ion mass spectrometry (ToF-SIMS), contact angle and zeta potential measurements. The results obtained show a reduction in the total surface tension and zeta potential of samples treated with UV-C light when coated with a protein layer. Furthermore, the UV-C light treatment applied to titanium alloy surfaces is able to modify the conformation, orientation and packing of the proteins arranged in the adsorbed layer. Low irradiation time generates an unstable surface with the lowest protein adsorption and the highest hydrophobic/hydrophilic protein ratio, indicating a possible denaturalization of the protein on these surfaces. However, surface changes are stabilized after 15 h or UV-C irradiation, favoring the protein adsorption through electrical interactions.
A scale development study: Hemodialysis comfort scale version II

Aim Aim of this study was to develop a valid and reliable measuring tool in order to evaluate comfort of patients receiving hemodialysis treatment. Background There has been available a scale developed to evaluate comfort of hemodialysis patients “HDCS (Hemodialysis Comfort Scale). ” Due to HDCS consisted of nine items and evaluated comfort in two sub-dimensions, researchers who developed HDCS, stated that number of scale items and dimensions is not sufficient to fully evaluate comfort. Therefore, (Hemodialysis Comfort Scale Version II) HDCS-II was developed with this research and its development process were discussed in this article. Materials and Methods Sample of this methodological research was consisted of 436 chronic hemodialysis patients, treated at five hemodialysis centers between October 2018 and May 2019. In process of creation item pool, comfort theory and literature was examined. The items in the old scale were also revised and included. Thereby a new question pool of 87 items was created. This draft scale was sent for expert opinion. In validity of scale; content validity index, exploratory and confirmatory factor analysis were used. In reliability study; Item analysis, cronbach’s alpha reliability coefficient, parallel form reliability and item analysis based on upper-lower group averages were used. Results There was consistency between expert views relating to items in scale. According to exploratory factor analysis, scale consisted of six dimensions. Cronbach alpha coefficient of 26-item scale was 0.79. Alpha values of the six factor in scale were, respectively; for physical relief 0.83, for physical ease 0.71, for psychospiritual ease 0.87, for psychospiritual transcendence 0.85, for environmental transcendence 0.82, and for sociocultural ease 0.61. Conclusion HDCS-II is a 5-point likert type and consists of 26 items and 6 factors. This scale is a valid and reliable measurement tool that can be used to determine comfort of patients undergoing hemodialysis treatment.
Comparison of indoor and vehicle-borne thermography

One of the tools traditionally used in assessments of the thermal status of buildings is the application of JR-techniques. This application has to a large extent been restricted to indoor inspections of attics, external walls and basements, or to roof inspections by means of aerial thermography, or to detection of air leaks by pressurisation of the building. These applications have, in general, been very successful. In this paper is presented an evaluation of a staged process where major building envelope anomalies have been detected by outdoor thermography, classified using indoor thermography, moisture meters and fiber optics techniques, and evaluated with regard to their impact on energy consumption and envelope performance. In the evaluation of this process, inspections of external walls using indoor thermography and vehicleborne outdoor thermography have been compared to one another regarding factors such as the number of suspected thermal anomalies detected, the accuracy in predicting real damages, the time required for the operation and the image analysis, factors limiting operational efficiency, and the ease of the operation. Also, the measured external surface temperatures have been compared to those predicted by an analytical calculation. It is concluded that vehicle-borne JR-inspections may provide a quick way of detecting building thermal anomalies. The prediction accuracy relative to indoor inspections to some extent depends on the building design. However, most major damages detected by indoor thermography can, under suitable operating conditions, be detected also from the outside. Thus, a process combining outdoor thermography to detect building anomalies and indoor thermography to survey selected details, in a cost-efficient way gives a rather complete picture of building damages and building thermal status. To make an efficient use of the thermographic data collected, the information should be stored in a data base containing also other data on the building, for example, data on building function,design and operation. The whole process of gathering data by IR-techniques should be integrated into already existing schemes for building management, operation and maintenance.
Coffee industry waste-derived biochar: characterization and agricultural use evaluation according to Brazilian legislation

The agricultural use of biochar has been the focus of much research in the last decade due to the improvement of soil chemical, physical, and biological attributes. Nonetheless, Brazil still has no specific legislation for biochar, limiting its agricultural use. The objective of the present work is to evaluate the use of biochar produced from spent coffee grounds (SCG) and coffee parchment (CP) by slow pyrolysis at 700 °C according to the existing framework of the Brazilian Ministry of Agriculture, Livestock, and Food Supply (MAPA) legislation for organic fertilizer, soil conditioner or plant substrate. Biochar was characterized according to normative instructions No. 17, 31, 61, 7, 5 and 35. Although not required by the addressed legislation, the semitotal content of macroand micronutrients was also determined. While CP biochar could be used as an organic fertilizer or plant substrate, SCG biochar, due to its higher Ni content and lower than required cation exchange capacity (CEC), did not meet MAPA legislation criteria to allow for its agricultural use. Future regulations can be based on the current standards, and structural attributes, such as total C content, particle size distribution, and complete macroand micronutrient determination should be included. Further research may also indicate the viability of biochar use as a soil conditioner based on a more representative set of biomasses with a higher CEC. These considerations will help to take advantage of the benefits of biochar to soil, contributing to a circular economy, which is still at a difficult stage in Brazil.
Analysis of Wettability and Surface-Roughness of Titanium Grade 2 in Milling Process

Titanium Grade 2 is a material that is widely applied in biomedical implant materials. Titanium Grade 2 has a good corrosion resistance and good biocompatibility in the body. However, due to the low thermal conductivity, it is necessary to select the appropriate machining parameter in order to produce a good surface roughness value. The purpose of this study was to determine the surface characteristics of Titanium Grade 2 which include wettability and surface roughness on milling process. The research design used the full factorial L9 method, with 2 factors and 3 levels. The spindle speed variable has a p-value of 0.039 and the feeding speed variable has a p-value of 0.025. This shows that the two independent variables have a significant effect on the surface roughness response. The lowest surface roughness can be achieved by setting the spindle rotation at 700 rpm and the feed speed at 25 mm/min. All specimens showed contact angle measurement results below 90ᵒ, which means hydrophilic. Titanium Grade 2 material with this milling machining process can be used as an alternative to semi-permanent implant fabrication methods such as maxillofacial bone implants, bones of the fingers and toes, and others.
Equivariant estimation following selection from two normal populations having common unknown variance

For estimating the mean of the selected normal population (the one corresponding to the larger sample mean), we prove some admissibility and minimaxity results for the estimators belonging to the class of linear, affine and permutation equivariant estimators under the criteria of scaled mean squared error and scaled absolute bias. We derive a sufficient condition for inadmissibility of any affine and permutation equivariant estimator under the scaled mean squared error criterion. Consequently, all linear, affine and permutation equivariant estimators (except the naive estimator, larger of the two sample means) and some estimators proposed in Hsieh [On estimating the mean of the selected population with unknown variance. Commun Stat-Theor Methods. 1981;10(18):1869–1878] become inadmissible under scaled mean squared error criterion. We further show that under the scaled mean squared error criterion, the naive estimator is minimax, admissible and generalized Bayes with respect to the Jeffreys' prior. We analyse a real data set for illustration purpose and provide a simulation study to compare the performances of various competing estimators.
Driveline Modeling With Transmission Loss and Robust Torque Observer Design for Dual Clutch Transmission

This paper presents a design of driveline torque observer with dual clutch transmission (DCT). A goal of this study is to improve estimation performance of the observer. To increase the observer’s performance, it is important to make an accurate driveline model and a robust observer. First, to increase the accuracy of the model, we propose lumped driveline efficiency which is a parameter that expresses driveline transmission loss. In addition, a recursive least square estimation (RLSE) algorithm is proposed to estimate the parameter using driving data. Then, the model is updated using the estimated parameter value. Second, a reduced order observer is proposed to estimate transmitted torques of driveline in both driving and gear shifting process. Moreover, the observer, which is robust against measurement noise and disturbance, is designed through frequency domain analysis. For frequency domain analysis, an eigenstructure assignment method is applied to tune observer gains. Performance of the proposed RLSE algorithm and the observer are verified through simulation and testbench experiments.
An Investigation of the Educational Challenges During COVID-19: A Case Study of Saudi Students' Experience

The outbreak of Coronavirus disease (COVID-19) has shaken the world, forcing countries to implement a state of emergency, including the education system. Students have been forced to remain in hostels or houses since they cannot get to university campuses. As a result of this predicament, university authorities have no option but to implement an online learning environment. Specifically, Saudi universities have faced numerous difficulties in bringing the online learning systems to continue the educational process. On the other hand, students faced difficulties to cope with such circumstances (complete online learning) without any preparation or backup plan. According to the findings of the literature research, students experienced difficulties that were difficult to overcome. The aim of this study was to determine the challenges that first-year students of the University faced. The present research got a total of 234 valid responses from the participants. The findings indicate that respondents were not fully prepared in this situation in terms of physical, environmental, and psychological readiness, with some variances in viewpoints depending on their gender and age. Respondents expressed concern about the effect of lockdown on their ability to perform well academically. In this study, the researchers found that switching suddenly to an all-online alternative cause significant obstacles for students. It was determined that the present blended learning model, which utilizes online learning to support face-to-face instruction, has encountered a critical challenge when it comes towards replacing it, particularly with underprepared learners.
Sensitivity analysis for dam breach parameters using different approaches for earth-fill dam

The prediction of dams breach geometry crucial in studies of dam breaking. The hydrographs characteristics of flood that resulting from breaking of dam is mainly depend on the geometry of breach and the time formation of breach. Five approaches (Froehlich, Macdonald and Langridge-Monopolis, Von thun & Gillete, USBR and Singh % Snorrason) was used in order to predict dam breach parameters (breach width, breach side slope, breach formation time). The Sensitivity analysis was performed in order to assess the effect of each parameter on the resulting hydrograph of the flood. HEC-RAS model was used to calculate the effect of each parameter on the hydrograph of the flood that resulted. The width of breach (Bavg), side slope (z) and formation time of breach (tf) increased by 25%, 50%, 75% and 100% and decreased by 25%, 50% and 75%, respectively. Flood hydrograph was estimated at the dam site for each case. Sensitivity analysis was performed in order to check the effect of each parameter of breach and time of breaching. Sensitivity analysis was performed with Froehlich method with the mode of overtopping failure and maximum operating level at 107.5 meter above sea level. Result of sensitivity analysis show that peak discharge and time to reach it is adequately sensitive to breach side slope, highly sensitive to the breach formation time and less sensitive to breach width.
Traffic Monitoring of Motorcycles during Special Events Using Video Detection

Because of a recent federal initiative, states are required to submit motorcycle vehicle miles traveled data to the FHWA. Data are needed to obtain better counts of motorcycles to evaluate their impact on crashes and traffic flow, but there is concern about the quality of data. Many states have identified problems with automatic traffic recorders accounting for motorcycle traffic. Existing sensors exhibit difficulties counting motorcycles that travel side by side or close behind each other, they have difficulty distinguishing larger motorcycles from passenger vehicles, and magnetic counters in particular do not sense motorcycles that do not pass over or travel close enough to sensors. Alternatively, some states conduct manual classification counts, which are labor intensive and lead to sparse data. Because classification counts are frequently conducted during the week, they do not capture weekend numbers. This paper evaluates a video-based traffic monitoring system that was developed at Clemson University and can classify vehicles, including motorcycles. The processor uses vehicle tracking, rather than virtual detection, to collect vehicle count, speed, and classification data. An algorithm calculates a motorcycle's length, width, and height through a series of frames. The system is evaluated by using traffic data for more than 2,000 motorcycles, collected at two locations in Myrtle Beach, South Carolina, during a motorcycle rally. The difference between actual and system motorcycle counts ranged from 0.6% to just over 6%, depending on direction and location. The difference for all vehicles ranged from 0.25% to 3.6%. While the system successfully classifies motorcycles traveling in close pairs and in small groups, it experienced difficulty in cases of severe occlusion.
Stress Analysis in Fruits

It is a known phenomenon that loads during fruit treatment (e.g., harvesting, transport, and manipulating) result in the damage of product parts, primarily below the surface. The maximum stress likely develops inside the fruit, which leads to its damage. This phenomenon was analysed in a general manner (general material properties, unit load) by finite element method (FEM) simulations on an apple and a pear. The shell was found to have a significant effect on the developed stress state, especially for juicy fruits. The mechanism that determines how the stress properties of tomatoes affect the stress state was analysed. According to our model, the stress maxima develop in the middle of the analysed fruits. Such stress maxima might be the reason for the inner damage, which, in the case of a missing healing period, results in fruit breakage.
Reliability of MEM relays for zero leakage logic

Micro-electro-mechanical (MEM) relays are an intriguing alternative to transistors for ultra-low-power digital logic applications [1]. This paper investigates various failure modes for logic relays. Experimental results are presented to show that structural fatigue, dielectric charging, and contact stiction are not reliability-limiting issues. Contact resistance instability caused by surface oxidation and contamination is the primary challenge, and can be influenced by device design and operating conditions.
Hypoxia Promotes Proliferation and Inhibits Apoptosis of Pulmonary Arterial Smooth Muscle Cells via Modulating TRPC6

Received: Revised: Accepted: Published online: March 10, 2021 April 10, 2021 April 15, 2021 April 29, 2021 Ascites syndrome (AS) is a common nutritional metabolic disease in broilers that results in major loss to the breeding industry. The occurrence of AS is closely related to the abnormal proliferation of pulmonary artery smooth muscles cells (PASMCs) caused by hypoxia. The transient receptor potential cation channel subfamily C member 6 (TRPC6) is a Ca channel situated on cell membranes, and belongs to the proliferation of PASMCs caused by hypoxia in mammals. However, its role in hypoxic PASMCs in broilers remains unclear. Here, we investigated the effects of TRPC6 on the proliferation and apoptosis of primary chicken PASMCs under hypoxic conditions using an in vitro model. Primary chicken PASMCs were cultured under normoxic or hypoxic conditions (3% O2). The hypoxic cells were treated with 10 μM of SKF 96365 or 50 μM of fluofenamic acid (FFA) to inhibit or activate TRPC6, respectively. Cell viability was detected by CCK-8, intracellular Ca levels, cell cycle and cell apoptosis were assayed by a flow cytometric assay, the mRNA levels of TRPC6 were measured by digital-droplet PCR (ddPCR), the protein levels of TRPC6 were tested by immunoblotting, and the mRNA levels of caspase3 were detected by RT-PCR. Our results revealed that exposing PASMCs to hypoxic conditions for 48h increased cell viability and intracellular Ca levels. Additionally, hypoxic conditions increased the expression of TRPC6 and promoted cell cycle progression, but decreased cell apoptosis and caspase 3 mRNA levels. When the hypoxic PASMCs were treated with SKF 96365, inhibition of TRPC6 and cell proliferation and promotion of apoptosis were observed only in the first 24h of treatment. Treatment with FFA for 24h had the opposite effects. These results suggested that TRPC6-mediated Ca entry contributed to hypoxia-induced PASMCs proliferation and apoptosis resistance, which identified TRPC6 as a possible key target in vascular remodeling in chicken. ©2021 PVJ. All rights reserved
Virtual Generalist: Modeling Co-morbidities in Synthea TM

The Synthea TM Patient Generator presents important new opportunities to create simulated data for health care and research. To achieve this purpose, however, Synthea must optimally reflect real medical encounters and disease states, which are often complex and nuanced. Most of the current Synthea modules function as “virtual specialists” that each focus on a relatively narrow scope of practice. To optimize Synthea’s functionality and application to the real world, a Virtual Generalist is required to generate a very wide range of complex combinations of conditions in statistically appropriate distributions. We developed hand-curated maps to compare observations made on real patients (coded in ICD10) to Synthea simulations (which use SNOMED concepts). Using these concept maps on a large clinical dataset, we were able to use machine learning (ML) on a scalable Spark platform to extract conditional probability tables (CPTs) that we incorporated into a Synthea simulation module. Our Virtual Generalist CKD module is notable in that it operates entirely by modifying attributes used by other modules, acting as a statistical supervisor to adjust population distributions. We validate the improved realism of the results using statistical measurements to compare distributions between simulated and real populations, and describe this validation approach in a detailed Appendix. Taking advantage of our current modeling of a comprehensive EMR dataset, we applied our existing methods to improvements in the Synthea simulation tools. Notebooks on our GitHub repository provide working examples other investigators can use to train and evaluate models on their own clinical data, to learn CPTs for other conditions. Importantly, we demonstrate our complex feature engineering and modeling approaches using Synthea data, which enables us to share working examples. Our tools, example module, and technical approaches help to democratize the use of ML models that can extract conditional probability tables, which are particularly suitable for use in Synthea's new lookup_table_transition state. Broad use of appropriate CPTs promises to add significant statistical sophistication to this simulation system. We provide a set of recommended design patterns for module authors that aim to increase Synthea modules’ amenability to the sort of statistical intervention that is possible with a Virtual Generalist. Together these tools and approaches empower developers to build simulation models with increased sophistication for complex disease conditions.