Miracle-dz/UniFAR-FTUs huggingface dataset:
Nitric Oxide Synthase Inhibition Induces Renal Medullary Hypoxia in Conscious Rats

Background Renal hypoxia, implicated as crucial factor in onset and progression of chronic kidney disease, may be attributed to reduced nitric oxide because nitric oxide dilates vasculature and inhibits mitochondrial oxygen consumption. We hypothesized that chronic nitric oxide synthase inhibition would induce renal hypoxia. Methods and Results Oxygen‐sensitive electrodes, attached to telemeters, were implanted in either renal cortex (n=6) or medulla (n=7) in rats. After recovery and stabilization, baseline oxygenation (pO 2) was recorded for 1 week. To inhibit nitric oxide synthase, N‐ω‐nitro‐l‐arginine (L‐NNA; 40 mg/kg/day) was administered via drinking water for 2 weeks. A separate group (n=8), instrumented with blood pressure telemeters, followed the same protocol. L‐NNA rapidly induced hypertension (165±6 versus 108±3 mm Hg; P<0.001) and proteinuria (79±12 versus 17±2 mg/day; P<0.001). Cortical pO 2, after initially dipping, returned to baseline and then increased. Medullary pO 2 decreased progressively (up to −19±6% versus baseline; P<0.05). After 14 days of L‐NNA, amplitude of diurnal medullary pO 2 was decreased (3.7 [2.2–5.3] versus 7.9 [7.5–8.4]; P<0.01), whereas amplitudes of blood pressure and cortical pO 2 were unaltered. Terminal glomerular filtration rate (1374±74 versus 2098±122 μL/min), renal blood flow (5014±336 versus 9966±905 μL/min), and sodium reabsorption efficiency (13.0±0.8 versus 22.8±1.7 μmol/μmol) decreased (all P<0.001). Conclusions For the first time, we show temporal development of renal cortical and medullary oxygenation during chronic nitric oxide synthase inhibition in unrestrained conscious rats. Whereas cortical pO 2 shows transient changes, medullary pO 2 decreased progressively. Chronic L‐NNA leads to decreased renal perfusion and sodium reabsorption efficiency, resulting in progressive medullary hypoxia, suggesting that juxtamedullary nephrons are potentially vulnerable to prolonged nitric oxide depletion.
A tutorial on the synthesis and validation of a closed-loop wind farm controller using a steady-state surrogate model

In wind farms, wake interaction leads to losses in power capture and accelerated structural degradation when compared to freestanding turbines. One method to reduce wake losses is by misaligning the rotor with the incoming flow using its yaw actuator, thereby laterally deflecting the wake away from downstream turbines. However, this demands an accurate and computationally tractable model of the wind farm dynamics. This problem calls for a closed-loop solution. This tutorial paper fills the scientific gap by demonstrating the full closed-loop controller synthesis cycle using a steady-state surrogate model. Furthermore, a novel, computationally efficient and modular communication interface is presented that enables researchers to straight-forwardly test their control algorithms in large-eddy simulations. High-fidelity simulations of a 9-turbine farm show a power production increase of up to 11% using the proposed closed-loop controller compared to traditional, greedy wind farm operation.
Interference Comparison between OFDM & FH-OFDM Systems

Orthogonal Frequency Division Multiplexing (OFDM) is a common modulation technique that is being used in many of modern wireless communications and standards due to its excellent spectral efficiency and immunity to multipath interference in fading channel. In this paper, a Frequency Hopping Orthogonal Frequency Division Multiplexing (FH-OFDM) system is proposed to enhance the performance of conventional OFDM systems in multiuser interference. Based on simulation results, the Bit Error Rate (BER) performance of the proposed FH-OFDM system is shown to be superior to that of the conventional OFDM system under conditions of multiuser interference and Additive White Gaussian Noise (AWGN) channel.
A Journey From Simple to Complex Alignment on Real-World Ontologies

Ontology alignment has been an active research topic for over a decade. Over that time, many developers have focused on creating alignment systems and methods to find simple 1-to-1 equivalence matches between two ontologies. However, very few alignment systems focus on finding complex correspondences. There are several reasons for this limitation. First, there are no widely accepted alignment benchmarks that contain such complex relationships. Second, the traditional evaluation metrics like precision, recall, and f-measure are not accurate enough to evaluate the performance of a complex alignment system. And third, the approaches most commonly used to find simple equivalences do not handle the increased computational complexity of finding complex equivalences well. Therefore, it becomes a big challenge for many developers to create and evaluate the systems. In this paper, in order to advance the development of ontology matching, we seek to address the problem by first developing potential complex alignment benchmarks from realworld ontologies. In addition, we utilize traditional automated alignment systems to suggest complex correspondences, and finally plan to achieve our ultimate goal of creating and evaluating our own complex alignment system based on logical RDF data compression.
Concurrent wasting and stunting among under‐five children in Niakhar, Senegal

Abstract The study describes the patterns of concurrent wasting and stunting (WaSt) among children age 6–59 months living in the 1980s in Niakhar, a rural area of Senegal under demographic surveillance. Wasting and stunting were defined by z scores lower than −2 in weight for height and height for age. Both conditions were found to be highly prevalent, wasting more so before age 30 months, stunting more so after age 30 months. As a result, concurrent WaSt peaked around age 18 months and its prevalence (6.2%) was primarily the product of the two conditions, with an interaction term of 1.57 (p < 10−6). The interaction was due to the correlation between both conditions (more stunting if wasted, more wasting if stunted). Before age 30 months, boys were more likely to be concurrently wasted and stunted than girls (RR = 1.61), but the sex difference disappeared after 30 months of age. The excess susceptibility of younger boys could not be explained by muscle mass or fat mass measured by arm or muscle circumference, triceps, or subscapular skinfold. Concurrent WaSt was a strong risk factor for child mortality, and its effect was the product of the independent effect of each component, with no significant interaction.
Leveraging Gaussian Process and Voting-Empowered Many-Objective Evaluation for Fault Identification

Using piezoelectric impedance/admittance sensing for structural health monitoring is promising, owing to the simplicity in circuitry design as well as the high-frequency interrogation capability. The actual identification of fault location and severity using impedance/admittance measurements, nevertheless, remains to be an extremely challenging task. A first-principle based structural model using finite element discretization requires high dimensionality to characterize the high-frequency response. As such, direct inversion using the sensitivity matrix usually yields an under-determined problem. Alternatively, the identification problem may be cast into an optimization framework in which fault parameters are identified through repeated forward finite element analysis which however is oftentimes computationally prohibitive. This paper presents an efficient data-assisted optimization approach for fault identification without using finite element model iteratively. We formulate a many-objective optimization problem to identify fault parameters, where response surfaces of impedance measurements are constructed through Gaussian process-based calibration. To balance between solution diversity and convergence, an -dominance enabled many-objective simulated annealing algorithm is established. As multiple solutions are expected, a voting score calculation procedure is developed to further identify those solutions that yield better implications regarding structural health condition. The effectiveness of the proposed approach is demonstrated by systematic numerical and experimental case studies.
On preserving non-discrimination when combining expert advice

We study the interplay between sequential decision making and avoiding discrimination against protected groups, when examples arrive online and do not follow distributional assumptions. We consider the most basic extension of classical online learning: "Given a class of predictors that are individually non-discriminatory with respect to a particular metric, how can we combine them to perform as well as the best predictor, while preserving non-discrimination? " Surprisingly we show that this task is unachievable for the prevalent notion of "equalized odds" that requires equal false negative rates and equal false positive rates across groups. On the positive side, for another notion of non-discrimination, "equalized error rates", we show that running separate instances of the classical multiplicative weights algorithm for each group achieves this guarantee. Interestingly, even for this notion, we show that algorithms with stronger performance guarantees than multiplicative weights cannot preserve non-discrimination.
Ultra-Wideband Based Pose Estimation for Small Unmanned Aerial Vehicles

This paper proposes a 3-D local pose estimation system for a small Unmanned Aerial Vehicle (UAV) with a weight limit of 200 g and a very small footprint of 10 cm<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> 10 cm. The system is realized by fusing 3-D position estimations from an Ultra-Wide Band (UWB) transceiver network with Inertial Measurement Unit (IMU) sensor data and data from a barometric pressure sensor. The 3-D position from the UWB network is estimated using Multi-Dimensional Scaling (MDS) and range measurements between the transceivers. The range measurements are obtained using Double-Sided Two-Way Ranging (DS-TWR), thus eliminating the need for an additional clock synchronization mechanism. The sensor fusion is accomplished using a loosely coupled Extended Kalman Filter (EKF) architecture. Extensive evaluation of the proposed system shows that a position accuracy with a Root-Mean-Square Error (RMSE) of <inline-formula> <tex-math notation="LaTeX">$0.20\,cm$ </tex-math></inline-formula> can be obtained. The orientation angle can be estimated with an RMSE of 1.93°.
Student Academic Performance Prediction by using Decision Tree Algorithm

This work explores student’s academic performance using decision tree algorithm having parameters like Student’s Academic Information and Students Activity. We collected records of 22 students from Spring 2017 semester, studying in undergraduate level from Oman’s private Higher Education Institution. Proposed work utilizes Electronic Commerce Technologies module since it is a core module offered in every computing specialization. Furthermore, WEKA data mining tool is used to evaluate the decision tree algorithm for discovery of student’s performance along with Moodle access time. Simulation results demonstrate that Random Forest Tree algorithm showed better accuracy than comparative decision tree algorithms. Hence, shows good agreement for the training set provided. Therefore, the proposed work aid in improving student’s grades in the module. Helping stakeholders to analyze and evaluate the module delivery and results. Early detection and solution can be made both at the institutional level and module level.
Downregulation of miR-145-5p in cancer cells and their derived exosomes may contribute to the development of ovarian cancer by targeting CT

The present study aimed to identify shared microRNAs (miRNAs) in ovarian cancer (OC) cells and their exosomes using microarray data (accession number GSE103708) available from the Gene Expression Omnibus database, including exosomal samples from 13 OC cell lines and 3 normal ovarian surface epithelial cell lines, and their original cell samples. Differentially expressed miRNAs (DE-miRNAs) were identified using the Linear Models for Microarray data method, and mRNA targets of DE-miRNAs were predicted using the miRWalk2 database. The potential functions of target genes were analyzed using Database for Annotation, Visualization and Integrated Discovery and intersected with known OC-associated pathways downloaded from the Comparative Toxicogenomics Database. The associations between crucial miRNAs and target genes, and their clinical associations, were validated using data from The Cancer Genome Atlas. As a result, 16 upregulated and 6 downregulated DE-miRNAs were shared in OC cell lines and their exosomes compared with normal controls. The target genes of 11 common DE-miRNAs were predicted. Among these DE-miRNAs, a low expression of homosapiens (hsa)-miR-145-5p was significantly correlated with a poor prognosis and higher stages. Although 91 target genes were predicted for hsa-miR-145-5p, only 4 genes [connective tissue growth factor (CTGF), myotubularin-related protein 14, protein phosphatase 3 catalytic subunit alpha and suppressor of cytokine signaling 7] were suggested as risk factors for prognosis. The subsequent Pearson’s correlation analysis validated a significant negative correlation between hsa-miR-145-5p and CTGF (r=−0.1126, P=0.02188). According to the results of the functional analysis, CTGF is involved in the Hippo signaling pathway (hsa04390). In conclusion, decreased expression of hsa-miR-145 in OC and OC-derived exosomes may be a crucial biomarker for the diagnosis and treatment of OC.
Ancestral diterpene cyclases show increased thermostability and substrate acceptance

Bacterial diterpene cyclases are receiving increasing attention in biocatalysis and synthetic biology for the sustainable generation of complex multicyclic building blocks. Herein, we explore the potential of ancestral sequence reconstruction (ASR) to generate remodeled cyclases with enhanced stability, activity, and promiscuity. Putative ancestors of spiroviolene synthase, a bacterial class I diterpene cyclase, display an increased yield of soluble protein of up to fourfold upon expression in the model organism Escherichia coli. Two of the resurrected enzymes, with an estimated age of approximately 1.7 million years, display an upward shift in thermostability of 7–13 °C. Ancestral spiroviolene synthases catalyze cyclization of the natural C20‐substrate geranylgeranyl diphosphate (GGPP) and also accept C15 farnesyl diphosphate (FPP), which is not converted by the extant enzyme. In contrast, the consensus sequence generated from the corresponding multiple sequence alignment was found to be inactive toward both substrates. Mutation of a nonconserved position within the aspartate‐rich motif of the reconstructed ancestral cyclases was associated with modest effects on activity and relative substrate specificity (i.e., kcat/KM for GGPP over kcat/KM for FPP). Kinetic analyses performed at different temperatures reveal a loss of substrate saturation, when going from the ancestor with highest thermostability to the modern enzyme. The kinetics data also illustrate how an increase in temperature optimum of biocatalysis is reflected in altered entropy and enthalpy of activation. Our findings further highlight the potential and limitations of applying ASR to biosynthetic machineries in secondary metabolism.
[Meta-analysis on safety of application of enhanced recovery after surgery to laparoscopic bariatric surgery].

OBJECTIVE To systematically review the safety of application of enhanced recovery after surgery(ERAS) to laparoscopic bariatric surgery. METHODS The randomized controlled trials (RCTs) or case-controlled trials concerning application of ERAS principles in bariatric surgery were collected by searching several national and international online databases, including PubMed, Cochrane Library, CNKI, EMBASE and Wanfang databases. Data collection was completed in October 2016. The ERAS protocol covered three phases (preoperative, intraoperative, and postoperative), including preoperative counseling, reduced fasting, early ambulation, early oral feeding, etc. The endpoints included at least one of the following parameters: length of stay (LOS), operation time, readmission rate within 30 days, morbidity of postoperative complication (major/minor), and reoperation rate within 30 days. The quality of enrolled literatures was evaluated according to Cochrane Handbook and Newcastle-Ottawa Scale. RevMan 5.2 software was applied to perform meta analysis. The weighted mean difference (WMD) was used to combine the statistics for the measurement data, and the ratio and its 95% confidence interval were used to combine the statistics for the counting data. Subgroup analysis was conducted based on the quality of the enrolled literatures for the results of high heterogeneity. RESULTS A total of 7 studies, including 1 randomized controlled trail and 6 case-control studies, with 3264 patients were enrolled. Among the 3264 patients, 2051 received ERAS management (ERAS group) and 1213 received traditional perioperative management (control group). Meta analysis showed that compared with control group, ERAS group had shorter operative time (WMD=-17.56, 95%CI: -29.50 to -5.62, P=0.00), shorter length of hospital stay (WMD=-1.11, 95%CI: -1.31 to -0.92,P=0.00). There were no statistically significant differences between the two groups in the morbidity of postoperative major complication(OR=1.21, 95%CI:0.87 to 1.69, P=0.26) or minor complication (OR=1.25, 95%CI:0.99 to 1.58, P=0.06), re-admission rate within 30 days (OR=1.07, 95%CI: 0.81 to 1.43, P=0.63) and re-operation rate within 30 days(OR=1.33, 95%CI: 0.84 to 2.11, P=0.23). CONCLUSION Application of ERAS protocols to bariatric surgery is safe and feasible, which can also reduce length of hospital stay and operative time, and accelerate recovery.
Monkey-MIMMS: Towards Automated Cellular Resolution Large- Scale Two-Photon Microscopy In The Awake Macaque Monkey

The size and curvature of the macaque brain present challenges for two photon laser scanning microscopy (2P-LSM). General access to the cortex requires 5-axis positioning over a range of motion wider than existing designs offer. In addition, movement artifacts due to physiological pulsations and bodily movement present particular challenges. We present a microscope and implant platform that allows for repeatable, motorized positioning and stable imaging at any point on the dorsal convexity of macaque cortex. While testing the system to image neurons expressing fluorescent proteins in an awake macaque, motion artifacts were limited to several microns.
Manufacturing Productivity and Real Consumption Wages

• Users may freely distribute the URL that is used to identify this publication. • Users may download and/or print one copy of the publication from the University of Birmingham research portal for the purpose of private study or non-commercial research. • User may use extracts from the document in line with the concept of ‘fair dealing’ under the Copyright, Designs and Patents Act 1988 (? ) • Users may not further distribute the material nor use it for the purposes of commercial gain.
Educational Games to Enhance Museum Visits for Schools

Museums usually look for new educational tools to enhance their exhibition. The Oteiza’s museum in Navarre (Spain) especially gives importance to the dissemination of Jorge Oteiza’s work to children at schools. Consequently, a didactics section was created with the objective of developing activities and relationship with schools. Jorge Oteiza represents one of the most important artists in the Spanish modern art and his sculptures stem from his proper philosophical concepts such as negative aesthetics via addition and subtraction, or activation of space and time. Such notions make the learning process at school complex. Thus, this study proposes a framework that aims to enhance the visit to the museum through a series of mini-games that shed light on these abstract concepts. Representative sculptures were selected and the corresponding activities were designed and developed in collaboration with the didactics section of the museum following a Co-Design approach. Then, the framework was tested by pupils from primary and secondary schools and students from educational practice. Therefore this paper provides a guideline to design educational games in collaboration with a museum, shows that mini educational games help students in learning artistic concepts and that motion-based touchless interfaces are not really adapted for classroom use.
Hitting the Wall—Sensing and Signaling Pathways Involved in Plant Cell Wall Remodeling in Response to Abiotic Stress

Plant cells are surrounded by highly dynamic cell walls that play important roles regulating aspects of plant development. Recent advances in visualization and measurement of cell wall properties have enabled accumulation of new data about wall architecture and biomechanics. This has resulted in greater understanding of the dynamics of cell wall deposition and remodeling. The cell wall is the first line of defense against different adverse abiotic and biotic environmental influences. Different abiotic stress conditions such as salinity, drought, and frost trigger production of Reactive Oxygen Species (ROS) which act as important signaling molecules in stress activated cellular responses. Detection of ROS by still-elusive receptors triggers numerous signaling events that result in production of different protective compounds or even cell death, but most notably in stress-induced cell wall remodeling. This is mediated by different plant hormones, of which the most studied are jasmonic acid and brassinosteroids. In this review we highlight key factors involved in sensing, signal transduction, and response(s) to abiotic stress and how these mechanisms are related to cell wall-associated stress acclimatization. ROS, plant hormones, cell wall remodeling enzymes and different wall mechanosensors act coordinately during abiotic stress, resulting in abiotic stress wall acclimatization, enabling plants to survive adverse environmental conditions.
Analysis of Students’ Ratings of Teaching Quality to Understand the Role of Gender and Socio-Economic Diversity in Higher Education

Contribution: This paper contributes to the literature by confirming the existence, in gender and socio-economic diversified higher educational environments, of differential evaluation ratings given by students to their teachers. Background: Women and low socio-economic classes have historically been under-represented, both as students and teachers. Various policies and measures are being put in place internationally to raise their standing, equity, and success as they progress in their careers. To be effective, the after effects of these policies must be investigated and understood. Research Questions: This paper addressed the question of whether gender and socio-economic differences, in both teachers and students, affect students’ opinion of their teachers in higher education, across a number of disciplines. Methodology: The research analyzed the differentials in students’ ratings of their teachers in five disciplines in the field of education. Data was drawn from student responses to the surveys conducted in a large Indian university at the end of each course unit. The survey questions elicit their perceptions of teaching quality in the disciplines of civil engineering, electrical engineering, computer science engineering, mathematics, humanities and social sciences. This paper analyzes 112 919 and 16 354 complete sets of student ratings, to study the gender and socio-economic diversity based effects respectively. Statistical multivariate and univariate general linear models were used to derive the relevant results and graphs. Findings: The study reveals the existence of socio-economic status bias, gender-typical behavior, gender-atypical behavior, and same-gender and cross-gender biases; these resulted in differential ratings in the disciplines examined.