Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Functional and Nutritional Properties of Hydrolyzed Broad Bean and Quinoa Flours

In sports nutrition, protein intake is essential to stimulate protein synthesis and repair muscle damage caused by exercise. The search for non-traditional protein sources has increased in recent years. Quinoa (Chenopodium quinoa Wild) and broad beans (Vicia faba L.) grains could be used in the production of protein products. Broad beans are an introduced and widely expanded crop in South America; it is part of the Argentine Northwest Andean population diet. The aim of this work was to evaluate the functional and nutritional properties of hydrolyzed quinoa (HQF) and broad bean (HBF) flours for their use in the elaboration of protein foods for athletes. Both hydrolyzed flours were obtained using Flavourzyme at 50 °C and pH 8 for 3 and 1 h, respectively. HQF presented a higher degree of hydrolysis (21.79%), while HBF had higher protein content (57.31%), yield (32.14%), and protein recovery (71.31%). In HBF and HQF, Na and K were the most abundant minerals, both necessary for the replacement of electrolytes lost during physical training. HBF and HQF presented 5909.63 and 2708.91 mg/100 g of properties, respectively, and HQF presented higher emulsifying branched amino acids content, essential in sports nutrition. Regarding technological activity (61.30 m2/g), stability indexes (158.6 min), and foaming capacity (131%); HBF shows a wider range of solubility in function of pH, and good foaming stability (68–92%). These results indicate that HQF and HBF could be potential ingredients for athletes’ protein supplements formulation.
A new wavelength selective photoreceiver

A new kind of wavelength selective photoreceiver is proposed. It was constructed by a Fabry Perot (F P) etalon filter and a resonant cavity enhanced (RCE) photodetector. The photoreceiver′s spectral response is determined by the F P etalon filter with a FWHM of less than 4 nm. Moreover, with such a photoreceiver, the transmission loss of the F P etalon filter can be compensated to some extent. And this will benefit its applications.
Joining and Exiting the Value Chain of Multinationals and the Performance of Suppliers: Evidence from Inter-Firm Transaction Data

This paper investigates the productivity effects for domestic suppliers from joining and exiting the value chains of multinational enterprises (MNEs). The vast majority of prior literature has relied on sector-level input-output tables in estimating the effects of vertical linkages of FDI. Instead, our econometric analysis of the creation and destruction of backward linkages of MNEs is based on information on firm-to-firm transactions recorded in the valued added tax declarations data. Treatment analysis based on propensity score matching and panel data from Estonia suggests that starting to supply multinationals initially boosts the value added per employee of domestic firms, including effects on the scale of production and the capital-labour ratio. These first linkages to MNEs do not affect the total factor productivity (TFP) of domestic firms, suggesting that TFP effects take time to materialise. We further find that there are limits to the wider diffusion of the effects of linkages to MNEs. We find no significant positive effects on the second-tier suppliers: the positive effects are limited to the first-tier suppliers with direct links to MNEs. One novel result is the evidence that the productivity of suppliers does not fall, on average, after decreasing or ending supplier relationships with MNE customers.
Influence of Genotype on Endometrial Angiogenesis during Early Pregnancy in Piau and Commercial Line Gilts

Simple Summary Angiogenesis occurs physiologically in the maternal–fetal interface, and both maternal and fetal angiogenesis are required for a successful pregnancy. The relative transcript abundance of angiogenesis-related genes in the pig endometrium is controlled by factors that create a microenvironment that promotes successful embryo implantation. Therefore, we investigated the transcript abundance of angiogenesis-related genes in the endometrium of pregnant commercial line and Piau gilts, and their relationship with the phenotypic expression of genes important to the endometrium during early pregnancy (until 30 days). This research aimed to better understand the reproductive development of commercial and local Brazilian breeds, so that it can contribute to the knowledge and practice of pig farming. Abstract This study aimed to evaluate the endometrial angiogenesis of pregnant commercial line and Piau gilts during early pregnancy. We used 27 gilts, divided into three groups according to the type of mating: Commercial (n = 9), commercial line females mated with commercial line males; Cross-mated (n = 9), Piau females mated with commercial line males; and Piau (n = 9), Piau females mated with Piau males. Each group was divided into three subgroups based on gestational age at the time of slaughter (7, 15, and 30 days of pregnancy). Immediately after slaughter, endometrial samples were obtained for histological evaluation and for analysis of the relative transcript abundance (RTA) of angiogenesis-related genes (HIF1α, FGF9, ANG1, TEK, VEGFA, ANGPT1, and ANGPT2). The number of endometrial glands was similar among groups but decreased with gestational age (p < 0.05). Piau females showed a higher number of blood vessels (p < 0.05) at 7 and 15 days of pregnancy, but no differences were observed among groups at 30 days, suggesting an influence of the male genotype on the pattern of uterine vascularization. There were no differences among groups for RTA of the FGF9, HIF1α, TEK, VEGFA, ANGPT1, and ANGPT2 genes. The HIF1α-gene RTA was higher at 7 and 15 days of pregnancy; for TEK and ANGPT1, the RTA was higher at 15 days of pregnancy; and the RTA of VEGFA and ANGPT2 genes were higher at 30 days of pregnancy. The ANG1 RTA was similar for pregnancies in the commercial and Piau groups but was higher (p < 0.05) at 15 days in the Cross-mated group, suggesting an interaction between genotypes. Overall, the pattern found for the RTA of angiogenesis-related genes was similar among the groups in this study, although some phenotypic differences could be noted, such as the highest number of blood vessels being found during early pregnancy of Piau gilts. The results of the gene RTA when crossed with phenotypic data led to conclusions that are conflicting with those reported in the literature. However, noteworthy is that angiogenesis is a complex process in which the balance between stimulatory and inhibitory factors may be related to time.
Gear-Rack Tool for Generating an Involute Flank. Virtual Pole Method

In the paper, an approach to the issue of gear-rack type tool profiling is proposed, based on the “virtual pole” method. The proposed issue has also been solved based on complementary fundamental theorems, but the virtual pole method has the advantage of a simplified form of writing the generating movements. This makes it possible to avoid the need to write the relative movements between the tool and the piece. The paper presents the application of the virtual pole method for generating an involute profile.
Projection Scheme and Adaptive Control for Symmetric Matrices With Eigenvalue Bounds

A projection scheme to handle eigenvalue bounds for adaptive control with uncertain symmetric matrix parameters is introduced. Conventional parameter projection techniques are generally unable to handle explicit eigenvalue bounds. The continuous projection scheme presented here maintains the closed-loop stability properties for adaptive controllers while simultaneously satisfying a priori available eigenvalue bounds of the uncertain symmetric matrix valued parameters. The projection scheme uses the eigen decomposition of the symmetric matrix parameter to project its eigenvalues to lie within the prescribed bounds. The eigenvalues of the symmetric matrix may be lower bounded or upper bounded or both. A direct adaptation over the eigenvalues and the eigen projections of the symmetric matrix parameter is also derived to help circumvent expensive eigen decomposition calculations. The new projection here shows improved performance in numerical simulations of rigid body attitude tracking control and trajectory tracking of robotic manipulators with unknown inertia parameters.
Psychophysiological responses of women with polycystic ovary syndrome during sessions of high-intensity interval training

Purpose. The study described psychophysiological responses (perceived exertion, affective response) of women with polycystic ovary syndrome (PcOS) throughout 10 sessions of high-intensity interval training (HIIT). Methods. Overall, 12 physically inactive women with PcOS (age: 26.2 ± 4.1 years; body mass index: 28.5 ± 6.3 kg/m 2 ) performed 10 running HIIT sessions of 50 min [10 × 1-min intervals, 90% of maximal heat rate (HRmax); 3-min active recovery periods, 70% HRmax], including 5-min warm-up and cool-down, with 48-hour intervals. HRmax, rating of perceived exertion (RPE, Borg cR10 scale), and affective responses (Feeling Scale) were assessed in the last 10 s of each interval and recovery period. Each session responses were grouped into session parts (beginning, 1–3; middle, 4–7; end, 8–10) for intervals and recovery periods separately. The generalized estimating equation model served to compare %HRmax, RPE, and affective valence between session parts. Results. The intensities of intervals ( p < 0.001) and recovery ( p < 0.001) increased from session beginning to end, as did RPE of intervals ( p < 0.001) and recovery ( p < 0.001). Interval affective responses were lower at end compared with beginning ( p < 0.040). HIIT intensity (%HRmax) presented a small coefficient of variation (cV, ca. 3%); RPE exhibited medium cV (ca. 20%) between 10 HIIT sessions. Conclusions. Psychophysiological responses of physically inactive PcOS women to running HIIT demonstrate positive affective valence at the beginning of HIIT sessions. As the session progresses, affective valence decreases to neutral and RPE increases.
Exploring the relationship between travel and online food souvenirs

ABSTRACT Many places are synonymous with specific foods. Advances in packaging science, supply chain management, and internet platforms now allow for the sale of place-specific food speciality items online direct to consumers. Thus, destinations such as those in the Caribbean, could capitalize on the increased interest in online speciality food ordering. However, little is known about the relationship between this popular phenomena and tourism. Thus, a qualitative content analysis study focusing on Caribbean cuisine was employed to examine how tourism and the online purchase of food speciality items intersect. Data revealed that the food products were intimately linked to travel. Suggestions for ways the Caribbean might exploit these connections to travel and support the fledgling tourism industry are discussed.
Prediction of 90-Day Local Complications in Patients After Total Knee Arthroplasty: A Nomogram With External Validation

Background: Local complications after total knee arthroplasty (TKA) significantly affect the patient’s prognosis. Nomograms can be a useful tool for predicting such complications. Purpose: To compare the preoperative and intraoperative factors of patients who underwent TKA with and without complications and to construct and validate a nomogram based on selective predictors of local complications within 90 days postoperatively. Study Design: Case-control study; Level of evidence, 3. Methods: The nomogram was developed in a primary cohort that consisted of 410 patients who underwent primary TKA at the authors’ institution between January 2015 and September 2018. Predictor variables included 4 major local complications that can occur within 90 days: reoperation (including implant revision or removal for any reason and manipulation under anesthesia), infection, bleeding requiring ≥4 unit transfusion of red blood cells within 72 hours of surgery, and peripheral nerve injury. The authors used least absolute shrinkage and selection operator (LASSO) regression analysis for data dimension reduction and feature selection. Multivariable logistic regression analysis was used to develop the nomogram. Performance of the nomogram was assessed using C-index, calibration plot, area under the receiver operating characteristic curve (AUC), and decision curve analysis (DCA). The model was subjected to bootstrap validation and external validation using a prospective cohort of 249 patients. Results: Four significantly prognostic factors were incorporated into the nomogram: age-adjusted Charlson Comorbidity Index, American Society of Anesthesiologists score, tourniquet time, and estimated intraoperative blood loss. The model displayed good discrimination, with a C-index of 0.819 and an AUC of 0.819. The calibration curves showed optimal agreement between nomogram prediction and actual observation. A high C-index value of 0.801 could still be reached in bootstrap validation. Application of the nomogram in the validation cohort showed good discrimination (C-index, 0.731) and good calibration. DCA demonstrated that the nomogram was clinically useful. Conclusion: The authors developed and validated a novel nomogram that can provide individual prediction of local complications within 90 days for patients after TKA. This practical tool may be conveniently used to estimate individual risk and help clinicians take measures to minimize or prevent the incidence of complications.
Deep Learning for Depression Detection from Textual Data

Depression is a prevalent sickness, spreading worldwide with potentially serious implications. Timely recognition of emotional responses plays a pivotal function at present, with the profound expansion of social media and users of the internet. Mental illnesses are highly hazardous, stirring more than three hundred million people. Moreover, that is why research is focused on this subject. With the advancements of machine learning and the availability of sample data relevant to depression, there is the possibility of developing an early depression diagnostic system, which is key to lessening the number of afflicted individuals. This paper proposes a productive model by implementing the Long-Short Term Memory (LSTM) model, consisting of two hidden layers and large bias with Recurrent Neural Network (RNN) with two dense layers, to predict depression from text, which can be beneficial in protecting individuals from mental disorders and suicidal affairs. We train RNN on textual data to identify depression from text, semantics, and written content. The proposed framework achieves 99.0% accuracy, higher than its counterpart, frequency-based deep learning models, whereas the false positive rate is reduced. We also compare the proposed model with other models regarding its mean accuracy. The proposed approach indicates the feasibility of RNN and LSTM by achieving exceptional results for early recognition of depression in the emotions of numerous social media subscribers.
Petrochemical wastewater treatment with a pilot-scale bioaugmented biological treatment system

In solving the deterioration of biological treatment system treating petrochemical wastewater under low temperatures, bioaugmentation technology was adopted by delivering engineering bacteria into a pilot-scale two-stage anoxic-oxic (A/O) process based on previous lab-scale study. Experimental results showed that when the concentrations of COD and NH4+-N of the influent were 370–910 mg/L and 10–70 mg/L, the corresponding average concentrations of those of effluent were about 80 mg/L and 8 mg/L respectively, which was better than the Level I criteria of the Integrated Wastewater Discharge Standard (GB8978-1996). According to GC-MS analysis of the effluents from both the wastewater treatment plant (WWTP) and the pilot system, there were 68 kinds of persistent organic pollutants in the WWTP effluent, while there were only 32 in that of the pilot system. In addition, the amount of the organics in the effluent of the pilot system reduced by almost 50% compared to that of the WWTP. As a whole, after bioaugmentation, the organic removal efficiency of the wastewater treatment system obviously increased.
Effective of Smart Mathematical Model by Machine Learning Classifier on Big Data in Healthcare Fast Response

In the past few years, big data related to healthcare has become more important, due to the abundance of data, the increasing cost of healthcare, and the privacy of healthcare. Create, analyze, and process large and complex data that cannot be processed by traditional methods. The proposed method is based on classifying data into several classes using the data weight derived from the features extracted from the big data. Three important criteria were used to evaluate the study as well as to benchmark the current study with previous studies using a standard dataset.
Facilitators and Barriers to Research Participation in Care Homes: Thematic Analysis of Interviews with Researchers, Staff, Residents and Residents’ Families

Following the global health pandemic of COVID-19, a spotlight has been placed on care homes in the UK and the disproportionate impact the virus has had, and continues to have (Hanratty et al., 2020). There is an urgent need to widen our knowledge base about care homes and the inclusion of people living and working in care homes in research studies. This paper presents qualitative findings from a study exploring the facilitators and barriers to research participation in care homes. Semi-structured interviews were conducted with residents (n = 12), staff (n = 15), relatives (n = 6) and researchers (n = 8) across three care homes in Scotland between 2014 and 2015. The findings suggest that the key barriers and facilitators to research participation are best captured by three themes: relationships, knowledge about research, and structural challenges. The way these themes are navigated within the care home is expected to shape the willingness and ability of care homes to engage in research. Positive relationships, accessible information about research, and adequate time and space are all likely to increase research presence within care homes. Conversely, poor relationships, alienating research communication, and limited time and space are all likely to result in care homes being unable or unwilling to participate. Overall, this paper demonstrates that care homes face several barriers to research participation, and efforts to improve relationships, raise awareness of the research process and provide flexible solutions for structural challenges are needed. Future research needs to be mindful of these challenges in order to facilitate research relating to COVID-19 and more generally in gerontology and dementia.
3D Printed Scaffold Based on Type I Collagen/PLGA_TGF-β1 Nanoparticles Mimicking the Growth Factor Footprint of Human Bone Tissue

In bone regenerative strategies, the controlled release of growth factors is one of the main aspects for successful tissue regeneration. Recent trends in the drug delivery field increased the interest in the development of biodegradable systems able to protect and transport active agents. In the present study, we designed degradable poly(lactic-co-glycolic)acid (PLGA) nanocarriers suitable for the release of Transforming Growth Factor-beta 1 (TGF-β1), a key molecule in the management of bone cells behaviour. Spherical TGF-β1-containing PLGA (PLGA_TGF-β1) nanoparticles (ca.250 nm) exhibiting high encapsulation efficiency (ca.64%) were successfully synthesized. The TGF-β1 nanocarriers were subsequently combined with type I collagen for the fabrication of nanostructured 3D printed scaffolds able to mimic the TGF-β1 presence in the human bone extracellular matrix (ECM). The homogeneous hybrid formulation underwent a comprehensive rheological characterisation in view of 3D printing. The 3D printed collagen-based scaffolds (10 mm × 10 mm × 1 mm) successfully mimicked the TGF-β1 presence in human bone ECM as assessed by immunohistochemical TGF-β1 staining, covering ca.3. 4% of the whole scaffold area. Moreover, the collagenous matrix was able to reduce the initial burst release observed in the first 24 h from about 38% for the PLGA_TGF-β1 alone to 14.5%, proving that the nanocarriers incorporation into collagen allows achieving sustained release kinetics.
Analysis of the Culvert Foundation Settlement under Different Construction Methods in High Salinity Regions

In this paper, a key treatment technology of the culvert foundation is presented, which is on the high salt saturated fine sand in a new China local railway from XieTieshan to North Hobsonis. In the procedure，for the two kinds of culvert foundation treatment technology(gravel pile foundation and rubble replacement), the settlement laws of culvert under China-load are explored by comparing with the field observation data and numerical analysis conclusion. The results show that in saline soil area, using rubble fill to reinforce groundwork is a appropriate treatment technology for culvert foundation.
LDBPR: Latest Database of Protein Research

With the vast and rapid growth of protein research data, a large number of databases are produced to annotate proteins. How to use these databases is becoming a crucial part of modern biology. Database research is usually the first step in the analysis of a new protein. The combined utilization of multiple databases could help researchers to understand the evolution, structure, and function of proteins. Therefore, a well comprehensive and large-scale resource integrated with most of databases is urgently desirable for systematic and precise studies of proteins. Here we designed a platform LDBPR with a collection of 564 latest scientific protein databases. It fully covered physical, chemical, and biological information of Protein sequence, structure, and model, domain, function, and protein‐ protein interactions. Furthermore, The LDBPR can be explored by three ways: (i) single database can be browsed by typing the name in the given search bar; (ii) all protein categories can be browsed by clicking on the name of the category; (iii) the image icon, could give all categorized protein databases on single click. Moreover, the programming languages including PHP, HTML, CSS, and MySQL were used to construct LDBPR for the protein scientific community that can be freely searched by clicking http://www.habdsk. org/ldbpr.php and will be updated timely.
The Effects of Providing Advance Notice and Stress-Coping Traits on Physiological Stress of Patients during Dental Treatment

Patients tend to feel stress in association with dental treatment due to uneasiness and fear. We investigated the effects of providing advance notice and stress-coping traits on the physiological stress of patients during dental treatment. Sixty non-dental professionals (male, n = 26; female, n = 34; mean age, 49.9 years) were recruited for this study and informed consent was obtained. Subjects were given simulated dental treatment including three stimuli, air, percussion and running of an air turbine, with or without advance notice of the stimulation during dental treatment. Real-time sympathetic nerve activity (SN) and parasympathetic nerve activity (PN) during the treatment were measured using a biological information monitor. The stress-coping traits of each subject were examined using the Lazarus-Type Stress Coping Inventory (SCI). Correlations between the nerve-activity and scores of eight stress-coping strategies of SCI and the presence/absence of advance notice were analyzed. Age, types of stimuli and order of stimuli significantly affected SN, while age, types of stimuli, and the pattern of stimulation significantly affected PN. The interaction of the stress-coping trait and presence/absence of advance notice significantly affected PN. Providing advance notice may have different effects on physiological stress depending on how the patient copes with stress.