Miracle-dz/UniFAR-FTUs huggingface dataset:
Study on the Prognosis Effect of Traditional Chinese Medicine Treatment in DR Patients Based on the Perspective of Network Pharmacology

Diabetes damages the eye in many ways, but the most common eye complication is retinopathy. Of the 246 million people with diabetes worldwide, about 30% will be at risk of developing diabetic retinopathy. In addition to impairing vision, the presence of diabetic retinopathy also means an increased risk of life-threatening systemic vascular complications. To prevent the occurrence and development of diabetic retinopathy, the research and development of new drugs for diabetic retinopathy is the primary task. Because of its characteristics of holistic view and dialectical view, traditional Chinese medicine has a good effect in the treatment of complex diseases. However, due to the characteristics of complex components, numerous targets, and synergistic effects that are important, and its compound prescriptions, the modernization of traditional Chinese medicine has been hindered. The rise of network pharmacology in recent years provides a good opportunity for the development of traditional Chinese medicine. Network pharmacology aims to explore the relationship between drugs and diseases from a holistic perspective, discover drug targets, and guide the development of new drugs. In terms of methodology, network pharmacology has the characteristics of integrity and systematicness, which just coincides with the principle of consultation in traditional Chinese medicine. In this paper, from the perspective of the application of traditional Chinese medicine, TCMSP software was used to retrieve the active ingredients in traditional Chinese medicine, and the corresponding targets of the active ingredients were obtained. We then performed GO annotation analysis and KEGG pathway analysis on the targets using DAVID software. We further used Cytoscape software to build an active ingredient-target-pathway network model. Through network pharmacology research, it has been shown that Fufang Xueshuantong may treat diabetic retinopathy through multiple pathways such as intravascular growth factor signaling pathway, mitogen-activated protein kinase signaling pathway, and Toll sample receptor signaling pathway, reflecting the multicomponent traditional Chinese medicine compound and multitarget and multichannel characteristics. The research in this paper provides a theoretical basis for the pharmacological mechanism of traditional Chinese medicine in the treatment of diabetic retinopathy.
Urinary Aromatic Amino Acid Metabolites Associated With Postoperative Emergence Agitation in Paediatric Patients After General Anaesthesia: Urine Metabolomics Study

Background: Emergence agitation (EA) is very common in paediatric patients during recovery from general anaesthesia, but underlying mechanisms remain unknown. This prospective study was designed to profile preoperative urine metabolites and identify potential biomarkers that can predict the occurrence of EA. Methods: A total of 224 patients were screened for recruitment; of those, preoperative morning urine samples from 33 paediatric patients with EA and 33 non-EA gender- and age-matched patients after being given sevoflurane general anaesthesia were analysed by ultra-high-performance liquid chromatography (UHPLC) coupled with a Q Exactive Plus mass spectrometer. Univariate analysis and orthogonal projection to latent structures squares-discriminant analysis (OPLS-DA) were used to analyse these metabolites. The least absolute shrinkage and selection operator (LASSO) regression was used to identify predictive variables. The predictive model was evaluated through the receiver operating characteristic (ROC) analysis and then further assessed with 10-fold cross-validation. Results: Seventy-seven patients completed the study, of which 33 (42.9%) patients developed EA. EA and non-EA patients had many differences in preoperative urine metabolic profiling. Sixteen metabolites including nine aromatic amino acid metabolites, acylcarnitines, pyridoxamine, porphobilinogen, 7-methylxanthine, and 5′-methylthioadenosine were found associated with an increased risk of EA, and they all exhibited higher levels in the EA group than in the non-EA group. The main metabolic pathways involved in these metabolic changes included phenylalanine, tyrosine and tryptophan metabolisms. Among these potential biomarkers, L-tyrosine had the best predictive value with an odds ratio (OR) (95% CI) of 5.27 (2.20–12.63) and the AUC value of 0.81 (0.70–0.91) and was robust with internal 10-fold cross-validation. Conclusion: Urinary aromatic amino acid metabolites are closely associated with EA in paediatric patients, and further validation with larger cohorts and mechanistic studies is needed. Clinical Trial Registration: clinicaltrials.gov, identifier NCT04807998
A meta-analysis to examine whether nitrification inhibitors work through selectively inhibiting ammonia-oxidizing bacteria

Nitrification inhibitor (NI) is often claimed to be efficient in mitigating nitrogen (N) losses from agricultural production systems by slowing down nitrification. Increasing evidence suggests that ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) have the genetic potential to produce nitrous oxide (N2O) and perform the first step of nitrification, but their contribution to N2O and nitrification remains unclear. Furthermore, both AOA and AOB are probably targets for NIs, but a quantitative synthesis is lacking to identify the “indicator microbe” as the best predictor of NI efficiency under different environmental conditions. In this present study, a meta-analysis to assess the response characteristics of AOB and AOA to NI application was conducted and the relationship between NI efficiency and the AOA and AOB amoA genes response under different conditions was evaluated. The dataset consisted of 48 papers (214 observations). This study showed that NIs on average reduced 58.1% of N2O emissions and increased 71.4% of soil NH4+ concentrations, respectively. When 3, 4-dimethylpyrazole phosphate (DMPP) was applied with both organic and inorganic fertilizers in alkaline medium soils, it had higher efficacy of decreasing N2O emissions than in acidic soils. The abundance of AOB amoA genes was dramatically reduced by about 50% with NI application in most soil types. Decrease in N2O emissions with NI addition was significantly correlated with AOB changes (R2 = 0.135, n = 110, P < 0.01) rather than changes in AOA, and there was an obvious correlation between the changes in NH4+ concentration and AOB amoA gene abundance after NI application (R2 = 0.037, n = 136, P = 0.014). The results indicated the principal role of AOB in nitrification, furthermore, AOB would be the best predictor of NI efficiency.
Kalman Filtering Method for Real-Time Queue Length Estimation in a Connected Vehicle Environment

Queue length estimation is of great importance for measuring traffic signal performance and optimizing traffic signal timing plans. With the development of connected vehicle (CV) technology, using mobile CV data instead of fixed detector data to estimate queue length has become an important research topic. This study focuses on real-time queue length estimation for an isolated intersection with CV data. A Kalman filtering method is proposed to estimate the queue length in real time using traffic signal timing and real-time traffic flow parameters (i.e., saturated flow rate, traffic volume, and penetration rate), which are estimated using CV trajectories data. A simulation intersection was built and calibrated using field data to evaluate the performance of the proposed method and the benchmark method. Results show that when the CV penetration rate is at 30%, the average values of mean absolute errors, mean absolute percentage errors, and root mean square errors are just 1.6 vehicles, 20.9%, and 2.5 vehicles, respectively. The performance of the proposed model is also better than the benchmark method when the penetration rate of CVs is higher than 20%, which proves the validity of the proposed method. Furthermore, sensitivity analysis indicates that the proposed method requires a high penetration rate of at least 30%.
A Unit Root Test for Micro Panels with Serially Correlated Errors

This paper proposes a unit root test for short panels with serially correlated errors. The proposed test is based on the instrumental variables (IV) and the generalized method of moments (GMM) estimators. An advantage of the new test over other tests is that it allows for an ARMA type serial correlation. Monte Carlo simulation shows that the new test has good finite sample properties. Several methods to estimate the lag orders of ARMA structure are briefly discussed.
The emergence of e-learning and online-based training during the COVID-19 crisis: an exploratory investigation from Bangladesh

PurposeThe extreme measures that have been taken by governments across the globe to minimize the spread of COVID-19 have had significant impacts on almost all the public sectors, especially on the economy and education. This study aims to address the approaches and prospective of online-based training and e-learning for employee learning and development during this COVID-19 crisis.Design/methodology/approachWith an emphasis on the qualitative approach and considering the complex COVID-19 emergency, required data were collected from in-depth interviews to interpret the experiences of the respondents.FindingsThe findings suggested that the digital learning ecosystem offered flexibility of time, place and pace, which provided essential convenience during the COVID-19 crisis. From the human resource (HR) perspective, the e-learning culture has enabled the organizations to quickly adopt the new normal, secure sustainable continuity of organizational development and ensure decent work and growth within and across organizations. The adoption of e-learning and flexible working conditions following the setback has enabled the organizations to quickly cope up with the new normal, causing a significant paradigm shift in the organizational culture and corporate sector of Bangladesh.Research limitations/implicationsThe study will assist the HR of any organization to contemplate e-learning systems as effective alternative training methods. Also, the study will be suggestive to traverse new dimensions and skillsets for the pedagogues.Originality/valueThis study offers new evidential scenarios regarding the emergence of effective e-learning initiatives and online-based learning programs for developing the workforce to be efficient and productive even in distressful and inconvenient COVID-19 situations.
Impact of Current Waveforms on Battery Behaviour

Impact of Current Waveforms on Battery Behaviour Thuwaragan Sritharan Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2012 With increasing emphasis on renewable energy sources and efficient energy use, energy storage devices, and in particular electrochemical storage devices, are becoming more prevalent. In order to interface batteries to systems, converters are used to maintain the desired voltage, current or power. In this thesis, we explore the response of the battery to commonly seen current waveforms to understand the impact of the converter on the battery. An electrochemical model of the electrode-electrolyte is studied to first understand its operating principles and then to pinpoint the causes of the observed battery response. A circuit was built to test the response of the battery to current waveforms. Experiments consisting of constant current, triangular and sinusoidal currents of varying frequency and ripple currents, and pulsed currents were conducted. Using electrochemical principles, an explanation of the results is presented along with the impact of the experimental results on converter design specifications.
Simulations beyond the building, identifying climate adaptation scale jumping potentials to district and city level. Research by design for the city of Monterotondo (Italy)

With the increasing relevance of positive energy districts and complexity embedded in multiple buildings retrofitting strategies, the opportunities and demand for modelling and simulation tools have increased. This paper presents a workflow for dynamic simulation of energy demand for cooling and heating for the industrial district of Monterotondo, located in the outskirt of Rome (Italy). This dynamic framework was supported by Rhino’s 3-D modelling tools, and by the visual programming tool Grasshopper. Temperature, energy and UTCI were subsequently investigated, and different building and open space retrofitting strategies were compared, highlighting expected scaling up potential for the entire district.
Correlation of Breast Density Grade on Mammogram With Diagnosed Breast Cancer: A Retrospective Cross-Sectional Study

Objective The objective of this study is to determine any association between mammographic density (MD) and breast cancer in Pakistani population. The study will also investigate relationship between mammographic breast density, clinical characteristics, and molecular tumor markers of the disease. Methods A retrospective review of data was carried out from January 2020 to December 2020 with stage 0-3 patients with histologically proven breast cancer included in the study. Mammograms were reviewed and density grade was recorded in accordance with "Breast Imaging Reporting and Data System (BIRADS)" guidelines. Patient age, tumor, and receptor characteristics were studied and their association with mammographic density was investigated by using chi-square test. P-value ≤0.05 was considered statistically significant. Results A total of 361 patients were included with a mean age of 46 years. The frequencies of BIRAD categories were as follows: category A: 8.9%, category B: 43.2%, category C: 33.5%, and category D: 14.4%. Cumulative frequency of categories B and C was 76.7%. There is a statistically significant p-value ≤0.05 association observed between age, estrogen receptors (ER) status, and T-stage versus MD. Also, majority of our patients were in T-stage category 2 or 3, which can easily be picked on mammogram. Conclusion Most of the breast cancer patients in our population had a mammographic density of B or C, indicating that breast cancer is more common in dense breasts. Strong significant association of mammographic density with age, ER status, and tumor stage was found in our population. Future studies need to address and confirm MD and its association with subtypes and aggressiveness of breast cancer.
Underwriter ratings and risk-taking of IPO firms: evidence from China

ABSTRACT Unlike the existing literature, which focuses on the underwriter reputation, this paper examines the effect of underwriters on the risks of IPO (initial public offering) firms from the perspective of the ability to control risks. Using the underwriter rating by CSRC (China Securities Regulatory Commission), we find that the underwriter rating provides incremental information over the underwriter reputation and mainly reflects the ability of the underwriter to control risks. Consistent with this hypothesis, we document a negative relationship between the underwriter rating and the earnings volatility of firms after an IPO. Our results remain qualitatively similar after a series of robustness tests. Additional analysis suggests that an underwriter with a higher ability to control risks, proxied by the risk index of the underwriter, can significantly lower firms’ risks. Moreover, we find that a highly rated underwriter can reduce stock return volatility, discretionary accruals, the potential for a decline in earnings, and penalties by the CSRC. This study enriches the literature on how underwriter plays an essential role in IPOs from the ability to control risks.
ENHANCING ENGAGEMENT AND INCLUSIVITY THROUGH ACTIVITIES CO-DESIGNED WITH UNDERGRADUATES - A CASE OF INDUCTION WEEK FOR BUSINESS MANAGEMENT

In relation to induction there have been valuable innovations in the wider university, also nationally and internationally, but there has been insufficient human resource both to research these and then adapt to a specific context. The current study is to enhance induction week for business management with special focuses on student engagement and inclusion. The study adapts existing viable solutions as well as proposes new answers geared to equity, accessibility and exclusivity. One of the main aims of the study is to draw directly on the interest and experiences of students, explicitly as co-creators for induction, redesigning structure and activities. Consultations with student representatives and the Student Union are also conducted. By involving students in the process (Bovill et al [1] ), opportunities and challenges arise from the co-design approach, and these are addressed here.
The Impact of Lean Manufacturing Practices on Sustainability Performance: A Natural Resource-Based View

Drawing upon a Natural Resource-Based View (NRBV), this paper aims to propose a quantitative model that could be used to investigate whether Lean Manufacturing (LM) practices/tools can improve the three aspects of corporate sustainability performance (economic, environmental, and social). This paper is based on a theoretical study to develop a new model by reviewing the literature and proposing new ideas according to the Natural Resource-Based View (NRBV). Reviewing the literature showed that there is a significant association between LM practices/tools implementation and the improvement on three aspects of corporate sustainability performance (economic, environmental, and social). This paper provides insights to manufacturing managers about the ability of LM practices to reduce cost of operations and maximize the value provided to customers. Further, it highlighted the importance of LM practices implementation to manage organizations’ activities responsibly in terms of their environmental, social, and economic effects. By proposing such a quantitative model according to a NRBV, this study contributes to a broader understanding of how LM practices affect three pillars of sustainability.
Formation mechanism of binary complex based on β-lactoglobulin and propylene glycol alginate with different molecular weights: Structural characterization and delivery of curcumin

The complexation of protein and polysaccharide has shown considerable potential for the encapsulation of functional food components. In this work, propylene glycol alginate (PGA) molecules with different molecular weights (100, 500, and 2,000 kDa) were prepared through H2O2 oxidation, which were further combined with β-lactoglobulin nanoparticles (β-lgNPs) to form PGA-β-lgNPs complexes for the delivery of curcumin (Cur). Results showed that the depolymerization of PGA molecule was resulted from the breakage of glycosidic bonds in the main chain, and the depolymerization rate of PGA molecule depended on the reaction time, temperature, solution pH and H2O2 concentration. As the increasing molecular weight of PGA, the particle size, zeta-potential and turbidity of the complexes were obviously increased. The formation of PGA/β-lgNPs complexes was mainly driven by non-covalent interaction, including electrostatic gravitational interaction, hydrogen bonding and hydrophobic effect. Interestingly, the difference in the molecular weight of PGA also led to significantly differences in the micro-morphology of the complexes, as PGA with a high molecular weight (2,000 kDa) generated the formation of a “fruit-tree” shaped structure, whereas PGA with relatively low molecular weight (100 and 500 kDa) led to spherical particles with a “core-shell” structure. In addition, the incorporation of PGA molecules into β-lgNPs dispersion also contributed to the improvement in the encapsulation efficiency of Cur as well as physicochemical stability of β-lgNPs, and PGA with a higher molecular weight was confirmed with a better effect. Findings in the current work may help to further understand the effect of molecular weight of polysaccharide on the physical and structural properties as well as effectiveness as delivery systems of polysaccharide-protein complexes, providing for the possibility for the design and development of more efficient carriers for bioactive compounds in food system.
Generalized Decoupled Control Synthesis for Invertible Nonlinear Systems

Sufficient conditions for decoupling-control synthesis using state-variable feedback and precompensation are presented for a class of invertible nonlinear systems which does not satisfy the decoupling conditions available in the literature. For a certain class of systems which are invertible for restricted control inputs, a characterisation of external command input space is presented for which the closed-loop system is decoupled. An example of decoupling of a noninvertible nonlinear system with restricted control is presented.
A Hierarchical Compliance-Based Contextual Policy Search for Robotic Manipulation Tasks With Multiple Objectives

Contextual policy search methods have demonstrated the potential to acquire robotic skill generalization on trajectory-shaping-based tasks. However, it is still challenging for robotic contact-rich manipulation tasks because contact force regulation, reference trajectory adaptation, and task generalization must be fulfilled simultaneously. To this end, a hierarchical compliance-based contextual policy search (HC-CPS) approach is proposed to learn the robotic compliant skills for force, motion, and task adaptation. Specifically, the parameterized impedance-conditioned action space is proposed for reinforcement learning lower-level policy to obtain the compliance for reference motion regulation and contact force control, while a linear Gaussian contextual policy is formulated as the higher-level policy to optimize the context-conditioned impedance parameters for task generalization; therefore, a family of contact-rich manipulation tasks with multiple objectives is achieved. Moreover, data efficiency is further improved by two aspects: first, a variation encoder-decoder model is proposed to estimate the underlying constraints of impedance parameters over the actions, leading to the mitigated extrapolation error for lower-level policy off-policy learning; second, a composite forward model is proposed to generate artificial trajectories and reduce the reward bias for higher-level contextual policy learning. The HC-CPS approach is validated by three simulated manipulation tasks and the real-world dual peg-in-hole assembly tasks with two kinds of objectives, and the results demonstrate the effectiveness of HC-CPS.
Robust Controller for Community Microgrids for Stability Improvement in Islanded Mode

Many utilities are developing microgrids to improve power reliability and grid resiliency for customers. One critical challenge in microgrid design is maintaining system stability with changing operating conditions in the microgrid. The technical and contractual constraints of accessibility and controllability to customer-owned resources limit available control options. This paper details a single-phase community microgrid model and illustrates the stability challenges. It further proposes adopting an optimal controller using predictive current control (PCC) and robust control mu-synthesis to improve microgrid stability in islanded operating mode. Incorporating the mu-synthesis in the controller design assures the microgrid's robust stability. The proposed method facilitates the incorporation of main uncertainties in the microgrid: change in resources, uncertainties in their modeling, and load variation. The proposed method overcomes the constraints and does not impact the customer's resources normal operation. Furthermore, the controller has a simple structure and is easy to implement. The simulation results validate that the designed controller can maintain the system stability and achieve optimal performance against various changes in the microgrid. This paper presents a practical solution to the challenges utilities are facing in microgrid development.