Miracle-dz/UniFAR-FTUs huggingface dataset:
Dietary Mannan Oligosaccharides Modulate Gut Inflammatory Response and Improve Duodenal Villi Height in Post-Weaning Piglets Improving Feed Efficiency

Simple Summary Postweaning is a stressful period for piglets, accompanied by several modifications of the gastrointestinal tract, which can impair both animal health and performance. Nowadays, some classes of feed additives are under evaluation to benefit health status and promote growth in farm animals, modulating the development of the gastrointestinal tract and the residing microflora, and ameliorating the immune response during stressful situations. In the present study, we investigated the efficacy of mannan oligosaccharides (MOS) to support gut health and improve growth performance. Our results suggest that MOS can exert beneficial effects on gut health, improving duodenal morphology and modulating the expression of inflammation-related genes, which are accompanied by improved feed efficiency. Abstract The aim of this study was to evaluate the effects of mannan oligosaccharides (MOS) on gut health and performance in post-weaning piglets. In total, 40 piglets were divided into two experimental groups and fed a basal diet with (TRT) or without (CON) 0.2% mannan oligosaccharides for 35 days. Growth performance was determined weekly and faecal microbial composition on days 0, 14 and 35. On day 36, histometrical evaluations were performed on duodenal, jejunal, ileal, and colon samples. mRNA gene expression of inflammation-related genes was evaluated in samples of ileal Peyer’s patches (IPP). MOS administration improved feed efficiency in the last two weeks of the trial (p < 0.05), and a decreased clostridia content was found in faeces at day 14 (p = 0.05). TRT piglets showed increased duodenal villi height (p < 0.05), and reduced mRNA levels of Tumour Necrosis Factor α (p < 0.05) and Toll-Like Receptor 4 (p < 0.01) in IPP. Our results suggest beneficial effects of MOS supplementation on gut morphology and the expression of inflammation-related genes in post-weaning piglets, accompanied by increased feed efficiency.
Effect of Operative Time on Short-Term Adverse Events After Isolated Anterior Cruciate Ligament Reconstruction

Background: A longer operative time has been previously recognized as a risk factor for short-term complications after various orthopaedic procedures; however, it has yet to be investigated as an independent risk factor for postoperative complications after anterior cruciate ligament (ACL) reconstruction. Purpose: To identify whether a longer operative time in ACL reconstruction is an independent risk factor for the development of postoperative complications, hospital readmissions, or an extended length of stay within 30 days of the index procedure. Study Design: Descriptive epidemiology study. Methods: Patients undergoing ACL reconstruction between 2005 and 2016 were identified using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database. Cases with concomitant procedures were excluded from the analysis. We evaluated the association between operative time and preoperative variables such as patient age, sex, body mass index, comorbidities, and procedure. Correlations between adverse events and operative time, while controlling for the above preoperative variables, were calculated using multivariate Poisson regression with robust error variance. Results: A total of 14,159 procedures were included in this investigation. The mean patient age was 32.6 ± 10.8 years, the mean body mass index was 27.7 ± 6.5 kg/m2, and the mean operative time was 89.7 ± 28.6 minutes. Patients who were between the ages of 18 and 30 years (mean operative time, 95.1 ± 27.8 minutes; relative risk [RR], 17.7; P < .001), male (mean operative time, 91.9 ± 28.3 minutes; RR, 4.7; P < .001), and nondiabetic (mean operative time, 89.8 ± 28.6 minutes; RR, 7.1; P = .011) were associated with a longer operative duration. The overall complication rate was 1.1%. After adjusting for demographic characteristics and procedures, 15-minute incremental increases in operative duration were associated with an increased risk of deep vein thrombosis (RR, 1.12; P = .042), surgical site infections (RR, 1.21; P = .001), and sepsis (RR, 1.66; P < .001) as well as increased readmission rates (RR, 1.23; P = .001) and an extended length of stay (RR, 1.18; P = .008). Conclusion: While the overall adverse risk rate after ACL reconstruction remains low, marginal increases in operative time are associated with an increased risk of adverse events such as deep vein thrombosis, surgical site infections, sepsis, an extended length of stay, and readmissions. Thus, the operating physician and surgical staff should make all efforts to coordinate and prepare for each case to maximize surgical efficiency.
Impact of Information Technology Various Use on Students Digital Reading Achievement

Information and communication technology (ICT) has changed almost every aspect of our lives and work. A substantial amount of money is spent on technology by schools, families and policymakers with the hope of improving educational outcomes. When every child has access to the Internet, parents and teachers can use computers to develop their children's learning ability. However, unrestricted use of computers can also have a negative impact on children's development. In particular, every new use of computer technology brings new potential benefits in customization and flexibility, as well as potential pitfalls that may hinder education. Based on the 2012 Pisa test data of Israeli students, this paper discusses and analyzes the reading literacy of Israeli students from the perspective of educational informatization, focusing on the impact of various use and use time of computers on students' digital reading achievement.
Predictive Biomarkers and Patient Outcome in Platinum-Resistant (PLD-Treated) Ovarian Cancer

Identification of predictive biomarkers for ovarian cancer (OC) treatment, particularly in the platinum-resistant/refractory setting, is highly relevant for clinical management. E-cadherin, vimentin, and osteopontin (OPN) are proteins associated with tumor microenvironment (TME) remodelling that play key roles in cancer. This study aimed to evaluate the association between the staining patterns of these proteins with survival outcomes in a series of OC patients, namely in patients with platinum-resistant/refractory disease. Low E-cadherin expression and high vimentin expression in all patient groups (as well as for E-cadherin in the platinum-resistant arm) were significantly associated with longer overall survival (OS). Low cytoplasmic OPN expression (and cytoplasmic and membrane OPN in the platinum-resistant arm) were significantly associated with longer OS. In patients that responded to treatment (pegylated liposomal doxorubicin (PLD) or other), low cytoplasmic OPN expression was also associated with longer progression-free survival (PFS). In the other hand, high nuclear OPN-c expression in patients that respond to treatment was associated with longer OS and longer PFS. Longer PFS was also associated with high expression of both nuclear and cytoplasm OPN-c, in platinum-resistant patients and in those that responded to PLD. Our study indicates that the expression of E-cadherin, vimentin, and OPN may have prognostic implications. Nuclear OPN-c and cytoplasm OPN expression are putative predictive markers in platinum-resistant (PLD treated) ovarian cancer patients.
Earlier diagnosis of lung cancer in a randomised trial of an autoantibody blood test followed by imaging

The EarlyCDT-Lung test is a high-specificity blood-based autoantibody biomarker that could contribute to predicting lung cancer risk. We report on the results of a phase IV biomarker evaluation of whether using the EarlyCDT-Lung test and any subsequent computed tomography (CT) scanning to identify those at high risk of lung cancer reduces the incidence of patients with stage III/IV/unspecified lung cancer at diagnosis compared with the standard clinical practice at the time the study began. The Early Diagnosis of Lung Cancer Scotland (ECLS) trial was a randomised controlled trial of 12 208 participants at risk of developing lung cancer in Scotland in the UK. The intervention arm received the EarlyCDT-Lung test and, if test-positive, low-dose CT scanning 6-monthly for up to 2 years. EarlyCDT-Lung test-negative and control arm participants received standard clinical care. Outcomes were assessed at 2 years post-randomisation using validated data on cancer occurrence, cancer staging, mortality and comorbidities. At 2 years, 127 lung cancers were detected in the study population (1.0%). In the intervention arm, 33 out of 56 (58.9%) lung cancers were diagnosed at stage III/IV compared with 52 out of 71 (73.2%) in the control arm. The hazard ratio for stage III/IV presentation was 0.64 (95% CI 0.41–0.99). There were nonsignificant differences in lung cancer and all-cause mortality after 2 years. ECLS compared EarlyCDT-Lung plus CT screening to standard clinical care (symptomatic presentation) and was not designed to assess the incremental contribution of the EarlyCDT-Lung test. The observation of a stage shift towards earlier-stage lung cancer diagnosis merits further investigations to evaluate whether the EarlyCDT-Lung test adds anything to the emerging standard of low-dose CT. A positive EarlyCDT-Lung test, followed by CT, significantly reduced the numbers of late-stage cancers: performance of the blood test should be assessed further in a screening study where all eligible participants in the intervention arm have a CT scan https://bit.ly/32maUrB
Influences over Italian nurses’ job satisfaction and willingness to recommend their workplace

Background Nurses’ perception towards job satisfaction and willingness to recommend their workplace are relevant to a number of areas including the quality of nursing care delivery. Hence, an increasing number of scholars seek to understand the factors that influence these two concepts. Yet, inclusiveness and openness to innovation are under-investigated. Purpose The paper focuses on the relative importance that factors like propensity towards innovation, working conditions and inclusion have on nurses’ job satisfaction and their willingness to recommend their workplace. Methods A large sample of nurses was extracted from the organizational climate survey carried out in all healthcare authorities of nine Italian Regions through the years 2016–2018. Descriptive and multilevel regressions were carried out to investigate the factors that influence nurses’ job satisfaction and their willingness to recommend the hospital in which they work in, analysing both overall and in specific age classes. Results When recommending a workplace, nurses tend to recommend units showing higher propensity to innovate (OR 2.83), while the most important factor related to job satisfaction is the encouragement after a failure (OR 2.23). Inclusiveness is a key factor for both job satisfaction and willingness to recommend, whilst innovation prone organizations appear to be the most attractive for nurses. The levers mix is slightly different among the age classes. Findings identify the levers to be used in order to attract nurse workforce and increase nurses’ job satisfaction. These levers are partially different for young and senior nurses.
Systematic Mapping Study 2012-2017: Quality and Effectiveness Measurement in MOOC

Massive Open Online Courses (MOOCs) concentrate an important number of students and are set up as an alternative for acquiring knowledge and continuing education. The objective of this article is to analyze how the quality and effectiveness of the MOOCs were measured in empirical studies between 2012 and 2017. For which a systematic mapping study of articles was performed by using databases of Scopus and Web of Science. These articles were analyzed according to the: (1) context of the publication, (2) type of developing institutions and distribution platforms of the MOOC, and (3) characteristics of the empirical studies. It was identified that 54% of the developing institutions were universities and that 31% of the platforms that distributed the MOOC are of Coursera. These articles were also analyzed by type of study, the more frequently used indicators to measure the effectiveness, and the more frequently used focus points (approaches) to measure quality. The results of this study are useful because it allows having a general view of the most frequently utilized methodologies to measure quality and effectiveness in MOOCs.
The Impact of Korean Medicine Treatment on the Incidence of Parkinson’s Disease in Patients with Inflammatory Bowel Disease: A Nationwide Population-Based Cohort Study in South Korea

We aimed to investigate the association between Korean medicine (KM) treatment and the risk of Parkinson’s Disease (PD) in patients with inflammatory bowel disease (IBD) in South Korea. This study analyzed data from the National Health Insurance Service-Senior cohort in South Korea. The 1816 IBD patients enrolled in the analysis comprised 411 who received only conventional treatment (monotherapy group) and 1405 who received both conventional and KM treatments (integrative therapy group). The risk of PD in patients with IBD was significantly lower in the integrative therapy group than in the monotherapy group after adjusting for confounding variables (adjusted hazard ratio (HR), 0.56; 95% confidence interval (CI) = 0.34–0.92). In the mild Charlson Comorbidity Index (CCI) group, the risk of PD in patients with IBD in the integrative therapy group was 0.39 times lower (adjusted HR, 95% CI = 0.20–0.77) than that in the monotherapy group. However, there was no significant difference in the risk of PD in patients with IBD between the integrative therapy and monotherapy groups among individuals with severe CCI (adjusted HR, 0.90; 95% CI = 0.41−1.96). IBD patients are at a decreased risk of PD when they receive integrative therapy. KM treatment may prevent PD in IBD patients.
Safety-Guaranteed, Accelerated Learning in MDPs with Local Side Information *

In environments with uncertain dynamics, synthesis of optimal control policies mandates exploration. The applicability of classical learning algorithms to real-world problems is often limited by the number of time steps required for learning the environment model. Given some local side information about the differences in transition probabilities of the states, potentially obtained from the agent’s onboard sensors, we generalize the idea of indirect sampling for accelerated learning to propose an algorithm that balances between exploration and exploitation. We formalize this idea by introducing the notion of the value of information in the context of a Markov decision process with unknown transition probabilities, as a measure of the expected improvement in the agent’s current estimate of transition probabilities by taking a particular action. By exploiting available local side information and maximizing the estimated value of learned information at each time step, we accelerate the learning process and subsequent synthesis of the optimal control policy. Further, we define the notion of agent safety, a vital consideration for physical systems, in the context of our problem. Under certain assumptions, we provide guarantees on the safety of an agent exploring with our algorithm that exploits local side information. We illustrate agent safety and the improvement in learning speed using numerical experiments in the setting of a Mars rover, with data from onboard sensors acting as the local side information.
A Distributed Stochastic Task Offloading Methodology for IoT on e-Health

With the rapid development of Internet of Things (IoT) on e-Health, the role of Mobile Edge Computing (MEC) has been increasingly effective in providing high-performance, lowlatency computing services. In this work, we consider the problem of task offloading and computing resource allocation in dynamic environment, wherein heterogeneous IoT devices or e-Health applications with diverse requirements in latency and energy constraint. Taking into account the different traffic characteristics and spatio-temporally varying distributed environment, we formulate the offloading problem as a dynamic game and a Stackelberg Equilibrium (SE) based distributed online offloading manner is proposed. And then, to allocate computing resource on demand, a dynamic quote price mechanism is designed by invoking Lyapunov optimization. Furthermore, to improve processing efficiency and reduce unnecessary communication overhead, a “first-rank” servers selection criteria is proposed by balancing revenue and latency. Finally, the effectiveness and rationality of the algorithm are verified by experimental simulation.
Photodegradation-induced changes in dissolved organic matter in acidic waters

Photodegradation of dissolved organic matter (DOM) from stream waters was investigated using dissolved organic carbon (DOC) analysis, ultraviolet-visible absorbance, three-dimensional excitational emission matrix fluorescence, and high-performance size exclusion chromatography. The effects of altering pH and various iron concentrations on DOM characteristics during irradiation were examined. DOC concentration, absorbance, and fluorescence all decreased with increasing irradiation. These decreases were accompanied by a decrease in absorbance spectral slope and average molecular size and a blue-shift in fluorescence maximum; decreasing pH enhanced these changes. The photooxidation rate constants were wavelength dependent. For the ratio of the photooxidation rate constant at pH 4 to that at pH 8 under ultraviolet irradiation, there were two maxima at wavelengths of approximately 280 and 320 nm, respectively, indicating that aromatic fractions were most pH photosensitive. The isolated humic acid (HA) and fulv.
Microbiology and Biochemistry of Cheese and Fermented Milk

Rennets: Their Role In Milk Coagulation And Cheese Ripening. Classification and Identification of Bacteria Important in the Manufacture of Cheese Microbiology and Technology of Fermented Milks. Flavor and Texture in Soft Cheese. Flavor and Texture in Cheese. Cheese and Milk Flavor Chemistry. Enzymology of Dairy Lactic Acid Bacteria. Sensory Evaluation of Dairy Flavors. References. Index.
A seventy‐two‐year record of diminishing deep‐water oxygen in the St. Lawrence estuary: The northwest Atlantic connection

Oxygen concentrations in the bottom waters of the Lower St. Lawrence estuary (LSLE) decreased from 125 µmol L™1 (37.7% saturation) in the 1930s to an average of 65 µmol L™1 (20.7% saturation) for the 1984‐2003 period. A concurrent 1.65°C warming of the bottom water from the 1930s to the 1980s suggests that changes in the relative proportions of cold, fresh, oxygen‐rich Labrador Current Water (LCW) and warm, salty, oxygen‐poor North Atlantic Central Water (NACW) in the water mass entering the Laurentian Channel probably played a role in the oxygen depletion. We estimate that about one half to two thirds of the oxygen loss in the bottom waters of the LSLE can be attributed to a decreased proportion of LCW. This leaves between one third and one half of the oxygen decrease to be explained by causes other than changes in water mass composition. An increase in the along‐channel oxygen gradient from Cabot Strait to the LSLE over the past decades, combined with data from sediment cores, suggests that increased sediment oxygen demand may be partly responsible for the remainder of the oxygen decline. In July 2003, approximately 1,300 km2 of seafloor in the LSLE was bathed in hypoxic water (<62.5 µmol L−1).
Passive Fault-tolerant Estimation under Strategic Adversarial Bias

This paper is concerned with the problem of fault-tolerant estimation in cyber-physical systems. In cyber-physical systems, such as critical infrastructures, networked embedded sensors are widely used for monitoring and can be exploited by an adversary to deceive the control center by modifying measured values. The deception is modeled as a bias; i.e., there is a misalignment between the objective functions of the control center and the adversarial sensor. Different from previous studies, a Stackelberg equilibrium of a cheap talk setup is adapted to the attacker-defender game setting for the first time. That is, the defender (control center), as a receiver, is the leader, and the attacker (adversarial sensor), as a transmitter, is the follower. The equilibrium strategies and the associated costs are characterized for uniformly distributed variables and quadratic objective functions, and an analysis on the uniqueness of the equilibrium is provided. It is shown that the attacker and defender costs at the equilibrium are increasing with the bias and decreasing with the number of quantization levels. Our results surprisingly show that, under certain conditions, the attacker prefers a public bias rather than a private one.
How Well Do Teachers Predict Students’ Actions in Solving an Ill-Defined Problem in STEM Education: A Solution Using Sequential Pattern Mining

Predicting students’ line of actions helps educators give adequate guidance to students, but this remains a challenge in science, technology, engineering, and mathematics (STEM) education. Given this, there is a scarcity of related research that will help improve teachers’ prediction capabilities on students’ line of actions when tackling ill-defined problems (IDPs), as well as how emerging data mining techniques could contribute to such prediction. The present study aims to fill the gap by measuring the quality of teachers’ predictions (labeled expert prediction), where 43 elementary teachers predict students’ step-by-step actions when solving an IDP through the light path task (LPT), and then comparing its quality with that of machine prediction, executed via sequential pattern mining techniques. Data on students’ lines of action were collected from 501 5th- and 6th-grade students, aged 11–12. The results showed the significantly lower accuracy of expert prediction compared to machine prediction, which highlights the advantages of using data mining in predicting students’ actions and shows its possible application as a recommendation system to provide adaptive guidance in future STEM education.
A Deep Physical Model for Solar Irradiance Forecasting with Fisheye Images

We present a new deep learning approach for short-term solar irradiance forecasting based on fisheye images. Our architecture, based on recent works on video prediction with partial differential equations, extracts spatio-temporal features modelling cloud motion to accurately anticipate future solar irradiance. Our method obtains state-of-the-art results on video prediction and 5min-ahead irradiance forecasting against strong recent baselines, highlighting the benefits of incorporating physical knowledge in deep models for real-world physical process forecasting.
Memory Efficient Exact and Approximate Functional Dependency Extraction with ParSIT

In the last decade, Big Data has been presenting more and more challenges to various fields of computer science that center around data processing. Functional dependency extraction, the process of finding rules and relationships between attributes of datasets, is one such application. In this paper, a new dependency extraction method is presented for finding both exact and approximate functional dependencies, that is also memory efficient for large datasets. The proposed method is a parallelized improvement of Sequential Indexing Tables. It is evaluated through benchmark datasets and analysis is given about its time and spatial complexity.