Miracle-dz/UniFAR-FTUs huggingface dataset:
Baicalin provides protection against fluoxetine-induced hepatotoxicity by modulation of oxidative stress and inflammation

BACKGROUND Fluoxetine is one of the most widely prescribed anti-depressant drugs belonging to the category of selective serotonin reuptake inhibitors. Long-term fluoxetine treatment results in hepatotoxicity. Baicalin, a natural compound obtained from the Chinese herb Scutellaria baicalensis is known to have antioxidant, hepatoprotective and anti-inflammatory effects. However, the beneficial effects of baicalin against fluoxetine-induced hepatic damage have not previously been reported. AIM To evaluate the protective action of baicalin in fluoxetine-induced liver toxicity and inflammation. METHODS Male albino Wistar rats were divided into seven groups. Group 1 was the normal control. Oral fluoxetine was administered at 10 mg/kg body weight to groups 2, 3, 4 and 5. In addition, groups 3 and 4 were also co-administered oral baicalin (50 mg/kg and 100 mg/kg, respectively) while group 5 received silymarin (100 mg/kg), a standard hepatoprotective compound for comparison. Groups 6 and 7 were used as a positive control for baicalin (100 mg/kg) and silymarin (100 mg/kg), respectively. All treatments were carried out for 28 d. After sacrifice of the rats, biomarkers of oxidative stress [superoxide dismutase (SOD), catalase (CAT), reduced glutathione (GSH), glutathione-S-transferase (GST), advanced oxidation protein products (AOPP), malondialdehyde (MDA)], and liver injury [alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), total protein, albumin, bilirubin] were studied in serum and tissue using standard protocols and diagnostic kits. Inflammatory markers [tumor necrosis factor (TNF-α), interleukin (IL)-6, IL-10 and interferon (IFN)-γ] in serum were evaluated using ELISA-based kits. The effect of baicalin on liver was also analyzed by histopathological examination of tissue sections. RESULTS Fluoxetine-treated rats showed elevated levels of the serum liver function markers (total bilirubin, ALT, AST, and ALP) and inflammatory markers (TNF-α, IL-6, IL-10 and IFN-γ), with a decline in total protein and albumin levels. Biochemical markers of oxidative stress such as SOD, CAT, GST, GSH, MDA and AOPP in the liver tissue homogenate were also altered indicating a surge in reactive oxygen species leading to oxidative damage. Histological examination of liver tissue also showed degeneration of hepatocytes. Concurrent administration of baicalin (50 and 100 mg/kg) restored the biomarkers of oxidative stress, inflammation and hepatic damage in serum as well as in liver tissues to near normal levels. CONCLUSION These findings suggested that long-term treatment with fluoxetine leads to oxidative stress via the formation of free radicals that consequently cause inflammation and liver damage. Concurrent treatment with baicalin alleviated fluoxetine-induced hepatotoxicity and liver injury by regulating oxidative stress and inflammation.
Surface Acoustic Wave Devices for Mobil and Wireless Communications

From the Publisher: Written for readers with or without surface acoustic wave (SAW) experience, this book covers a wide range of SAW filter- and device-design techniques as well as applications to mobile and wireless circuitry. It provides numerous references and worked examples on SAW devices to highlight various design aspects, and contains illustrations from many leading electronic companies around the world. The first half of the book covers the principles of SAW devices. The second half focuses on applications to the mobile/wireless field, including SAW devices for antenna duplexers, RF and IF filters for cellular cordless phones, front-end filters for wireless transceivers, fixed and tunable oscillators, filters for on-board satellite communications, as well as coding and convolvers for indoor/outdoor spread-spectrum communications. Surface Acoustic Wave Devices for Mobile and Wireless Communications serves as an excellent sourcebook for engineers and designers with some SAW background, or for technical staff with no prior knowledge of SAW devices who need to know how this technology can help their products. It can be used as a textbook for senior and graduate students engaged in the study of signal processing techniques and systems for mobile communications.
Retracted Article: Fitting into technical organizations? Exploring the role of gender in construction and engineering management in Greece

While there is growing interest in professional identity construction, little is known about how marginalization may influence the development of professional identity of minority professionals, such as women engineers holding middle and upper management positions in construction management. Professional identity is defined as one’s professional self-concept based on attributes, beliefs, values, motives and experiences. The development of professional identity under conditions of marginalization presents an interesting puzzle. Professional roles are defined as prestigious and provide the role holder with autonomy and, often, a degree of privilege. However, marginalized professionals are often accorded little prestige and/or privilege because their identities are perceived as inferior. Thus, the purpose of the study is to build and enrich theory around the development of professional identity under conditions of marginalized gender identity. To accomplish this goal, the study of narratives by 33 prominent Greek women civil engineers with careers in construction management explores what it means to be both women and engineers holding high management positions in their organizations. The analysis of the findings revealed a redefinition rather than an adaptation process as a central task for the professional identity construction of women managers in engineering which involved three redefinition tasks: redefining occupational rhetorics, disadvantage, and the self.
Trends in Health Care Access/Experiences: Differential Gains across Sexuality and Sex Intersections before and after Marriage Equality

Background: Sexual minority adults experience several health care access inequities compared to their heterosexual peers; such inequities may be affected by LGBTQ+ legislation, such as the 2015 national marriage equality ruling. Methods: Using population-based data (n = 28,463) from the Association of American Medical Colleges biannual Consumer Survey of Health Care Access, we calculated trend ratios (TR) for indicators of health care access (e.g., insurance coverage, delaying or forgoing care due to cost) and satisfaction (e.g., general satisfaction, being mistreated due to sexual orientation) from 2013 to 2018 across sexuality and sex. We also tested for changes in trends related to the 2015 marriage equality ruling using interrupted time series trend interactions (TRInt). Results: The largest increases in access were observed in gay men (TR = 2.42, 95% CI 1.28, 4.57). Bisexual men had decreases in access over this period (TR = 0.47, 95% CI 0.22, 0.99). Only gay men had a significant increase in the health care access trend after U.S. national marriage equality (TRInt = 5.59, 95% CI 2.00, 9.18), while other sexual minority groups did not. Conclusions: We found that trends in health care access and satisfaction varied significantly across sexualities and sex. Our findings highlight important disparities in how federal marriage equality has benefited sexual minority groups.
Comorbidity Scores and Machine Learning Methods Can Improve Risk Assessment in Radical Cystectomy for Bladder Cancer

BACKGROUND: Pre-operative risk assessment in radical cystectomy (RC) is an ongoing challenge especially in elderly patients. OBJECTIVE: To evaluate the ability of comorbidity indices and their combination with clinical parameters in machine learning models to predict mortality and morbidity after RC. METHODS: In 392 patients who underwent open RC, complication and mortality rates were reported. The predictive values of the age-adjusted Charlson Comorbidity index (aCCI), the Elixhauser Index (EI), the Physical Status Classification System (ASA) and Gagne’s combined comorbidity Index (GCI) were evaluated using regression analyses. Various machine learning models (Gaussian naïve bayes, logistic regression, neural net, decision tree, random forest) were additionally investigated. RESULTS: The aCCI, ASA and GCI showed significant results for the prediction of complications (χ 2 = 8.8, p < 0.01, χ 2 = 15.7, p < 0.01 and χ 2 = 4.6, p = 0.03) and mortality (χ 2 = 21.1, p < 0.01, χ 2 = 25.8, p < 0.01 and χ 2 = 2.4, p = 0.04) after RC while the EI showed no significant prediction. However, areas under receiver characteristic curves (AUROCs) revealed good performance only for the prediction of mortality by the aCCI and ASA (0.81 and 0.78, CGI 0.63) while the prediction of complications was poor (aCCI 0.6, ASA 0.63, CGI 0.58). The combination of ASA, age, body mass index and sex in machine learning models showed a better prediction. Gaussian naïve bayes (0.79) and logistic regression (0.76) showed the best performance using a hold-out test set. CONCLUSIONS: The ASA and aCCI show good prediction of mortality after RC but fail predicting complications accurately. Here, the combination of comorbidity indices and clinical parameters in machine learning models seems promising.
Smart Grid Redefined

The Smart Grid is the biggest thing to hit the electric utility industry over the last 40 years. Was the grid dumb before and is now on its way to becoming smarter? Yes, and no. If you ask four people “what is a Smart Grid? ” – You will get five answers. Defining it is very important and this study attempts to do just that. The study starts by defining what the Smart Grid can and should deliver and uses it to define the Smart Grid. The author also presents a construct identifying various components of Smart Grid followed by their descriptions. Understanding these components is important because as technology progresses, one or more of them may replace. The paper ends with a description of two prominent Smart Grid implementations, one in US and one in Europe followed by what the future holds for this area and the challenges that it may pose. The Smart Grid is not just a technology play but a journey that must be followed with changes in people, processes driving business transformation [1]. If these are considered in totality, then the implementation will be successful. If not, the benefits will be lower than expected.
Interaction Analysis through "Collaboration and Cooperation" of the 4C Model

Collaboration and cooperation are two of the factors with the greatest impact on achieving quality software. The importance of analyzing these two dimensions in the course of a software development process becomes imperative to, not only ensure the quality of the current software, but also to improve the development processes itself. By believing on these assumptions the 4C model emerged. The 4C model was adapted from the 3C collaboration model in order to analyze and propose improvements to the software development process. The 4C model is based on the following dimensions: Communication, Coordination, Collaboration and Cooperation. In this paper we describe the dimensions "Collaboration and Cooperation" and its applicability in the analysis of the Hybrid User Centered Development Methodology (HUCDM) that formed the basis for the development of the educational resource Courseware Sere - The Human Being and Natural Resources. The analysis has mainly based on posts inserted on forums available at Moodle (which served as a groupware tool). The results achieved reinforce the importance of developing educational resources using collaborative and cooperative work based on multidisciplinary teams.
On time and meaningful partisanship: Stability, strength, and sway of attachment to new parties

New parties pose a challenge to the claim that time is an essential element in the construction of partisanship. By definition, new parties have not been around for much time, so the opportunities for the construction of meaningful attachments could be considered limited. In this paper, we test this expectation, unpacking the dynamics and implications of the attachment to new parties. Using panel data collected in Spain during a period of profound party system change, we estimate the extent to which partisanship with new parties is stable and strong, works as a heuristic for preference formation, and predicts vote choice. Our data suggest that attachments to new parties can be as meaningful as those that citizens have with old parties. These findings seem particularly relevant in a context where new parties are on the rise.
Prevalence and Factors Associated with Risky Sexual Behaviors among Patients with Severe Mental Illness in Uganda: A Descriptive Cross Sectional Study

Background: Persons living with severe mental illness (SMI) which includes schizophrenia, bipolar affective disorder and recurrent major depressive disorder are predisposed to risky sexual behavior (RSB). There is a paucity of data on this problem in sub-Saharan Africa and where research has been undertaken, only a limited range of risk factors have been considered and most of it was undertaken before antiretroviral therapy was universally available, hence the need for this study. The objective of this study was to determine the prevalence and factors associated with risky sexual behavior among individuals with SMI attending care in central and south western Uganda. Methods: A cross sectional study was conducted among 393 persons with SMI attending two psychiatric out-patient facilities in Uganda. Psychiatric disorder was confirmed using MINI International Neuropsychiatric Interview version 7.2. RSB was defined as engaging in at least one of four risky sexual behaviours that have been associated with HIV infection in the Ugandan psychosocial environment in the last three months using an 8 item RSB questionnaire used for assessment of RSB. Prevalence of RSB and associated logistic Results: The of RSB The physical abuse) current psychosocial challenges (mental health stigma) and psychiatric illness factors (history of a past manic episode, current psychotic episode, severity of depressive symptoms and severity of manic symptoms). Conclusions: One quarter of clinic attending respondents with severe mental illness in Uganda practice risky sexual behaviour. Factors associated with risky sexual behaviour fall under the domains of past and present trauma, current psychosocial challenges and psychiatric illness factors. This calls for a multi-sectoral approach that includes community awareness about the nature of SMI and the rights of persons with SMI and measures to improve Psychiatric symptom management.
Speed recovery strategy for the inertia response control of DFIGs: extended state observer based approach

The inertia response control (IRC) of doubly-fed induction generators is capable of providing the power system with controlled inertia by releasing mechanical power to or absorbing electrical power from the system when the system frequency experiences sudden changes. However, it will result in deviation of the rotor speed from the optimal working point and unexpectedly reduce the captured wind power. To restore the rotor speed as quickly after an IRC action as possible, in this study, the authors derive a novel rotor speed recovery strategy based on the extended state observer (ESO) technique. They first develop two ESOs to accurately estimate the captured wind power by the wind turbine and the system unbalance power, respectively. They then synthesise the rotor speed recovery strategy based on such estimates, including the optimal recovery timing and the control modes as well as the associated switching logics. Detailed simulations carried on PSCAD/EMTDC show that the authors’ controller outperforms the traditional proportional–integral controller in the aspects of dynamical performance, the robustness to varying working conditions and the capability to prevent the system frequency from a second drop.
Automatic method for quantification of pericardial fat on non-enhanced cardiac CT

Poster: "ECR 2013 / C-0190 / Automatic method for quantification of pericardial fat on non-enhanced cardiac CT" by: "R. Shahzad1, D. Bos1, C. Metz1, H. Kirisli1, A. van der Lugt1, L. J. van Vliet2, W. J. Niessen1, T. van Walsum1; 1Rotterdam/NL, 2Delft/NL"
Bespoke particle shapes in granular matter

Among granular matter, one type of particle has special properties. Upon being assembled in disordered configurations, these particles interlock, hook, almost braid, and – surprisingly, considering their relatively low packing fractions – show exceptional shear strength.Such is the case of non-convex particles. They have been used in the shapes of tetrapods, ‘L’, ‘Z’, stars, and many others, to protect coasts or build self-standing structures requiring no binders or external supports. Although these structures are often designed without a comprehensive mechanical characterization, they have already demonstrated great potential as highly resistant construction materials. Nevertheless, it is natural to attempt to find the most appropriate non-convex shapes for any given application. Can a particle shape be tuned to obtain a desired mechanical behavior? Although this question cannot be answered yet, current technological, simulation, and experimental developments strongly suggest that it can be resolved in the next decade. A clear understanding of the relationships between particle shapes, mechanical response, and packing properties will be key to providing insights into the behavior of these materials. Such work should stand on 1) robust and general shape descriptors that encode the complexity of non-convex shapes (i.e., the number of arms, the symmetries, and asymmetries of the bodies, the presence of holes, etc.), 2) the analysis of the response of assemblies under different loading conditions, and 3) the disposition and reliability of non-convex shapes to ensure durability. The manufacturing process and an efficient use of resources are additional elements that could further help to optimize particle shape. In the quest of designing bespoke non-convex particles, this paper consolidates the challenges that remain unresolved. It also outlines some routes to explore based on the latest developments in technology and research.
Decision tree: basic theory, algorithm formulation and implementation

Machine learning is a subfield of artificial intelligence that teaches a machine how to learn. It has drawn research interest in many research areas, including computer science, engineering technology, and statistics. It also has growing impacts on our daily life. Our life is gradually being affected by algorithms regardless of realizing it or not. For example, the history of your Internet research is shared with companies. When I searched for “football kits” on google, it suggested 10 or 20 most related links; after I clicked on one of the links, the Internet then recorded this as a piece of data; the computer would learn from it to provide improved suggestions next time. Decision trees are one of the most important machine learning models. It uses a tree-like model of decisions and consequences to help classify experiment sets of data. This article summarises the algorithm of decision trees by investigating its basic theories, algorithms, and implementations.
Comparative evaluation of compressive strength of three different core build up materials on fiber reinforced composite post after 24 hours and 1 week- an in vitro UTM study

Background: A core build-up is a restoration placed in a badly broken down tooth to restore the coronal portion of the tooth. This facilitates subsequent restoration of the broken down tooth by means of extra-coronal restoration. Compressive strength of core materials is thought to be important because core usually replaces the large bulk of the tooth structure and must resist multidirectional forces. In this study compressive strength of three different core materials was investigated on Fiber Reinforced Composite post at different time intervals. Objective: The purpose of the study undertaken was to determine the compressive strength of self-cured, photo cured and dual cured core build up materials on Fiber Reinforced Composite post after 24 hours and 1 week. Methodology: Cylindrical specimens measuring 6mm in height and 4mm in diameter were prepared using a machined plexiglass mold and core build up was done around the fiber post. Ten specimens were prepared in each group (n=30); Group A: Restorative Glass lonomer Cement-GC Gold, Japan; Group B: Light-cured composite-Magma NT, Prevest Denpro, USA and Group C: Dual-cure core-build up composite resin-Para Core, Coltene whaledent, USA, which were further subdivided into five specimens per group according to the time intervals of 24 hours and 1 week. Compressive strength was determined using a universal testing machine. The maximum load applied to fracture the specimens was recorded and compressive strength calculated in MPA. The data obtained was analyzed using parametric one way ANOVA test and Bonferroni post-hoc procedure. Results: The mean compressive strength was significantly higher ( p <0.05) in Para Core group as compared to GC Gold and Magma NT. The differences in compressive strength observed were statistically significant. Conclusion: Within the limitations of this study, Para Core had higher strength compared to the other two core build-up materials; GC Gold and Magma NT and the strength of each material increased after 1 week.
The Impact of Training on Beef Cattle Farmers’ Installation of Biogas Digesters

Anaerobic digestion is one of the leading ways to manage livestock manure for energy production and move towards the target of carbon neutrality in the agricultural sector. Based on field survey data from China, a binary probit model and the propensity score matching method are employed to empirically examine the impact of agricultural training on livestock farmers’ installation of biogas digesters to manage livestock manure. The survey results show that beef cattle farmers in our study area are reluctant to install biogas digesters and the actual installation ratio of farmers is much lower than that that is willing to install. On the contrary, the beef cattle farmers are enthusiastic to participate in training (e.g., policy-oriented, technology-oriented, and field-based) related to sustainable farming practices. Regression results suggest that training can effectively promote the installation of biogas digesters, and with the increase of training intensity, the probability to install biogas digesters increases. We further find three other factors that affect farmers’ installation of biogas digesters: the education level of a farmer, which is one of the most important factors positively affecting the installation of biogas digesters; longer farming experience of a farmer, which can significantly promote biogas digester installation; and the farther away a farm is from town/urban centers, which means the more likely it is that the farmer will install biogas digesters. Policy implications are discussed.