Miracle-dz/UniFAR-FTUs huggingface dataset:
Pinpointing Cancer Sub-Type Specific Metabolic Tasks Facilitates Identification of Anti-cancer Targets

Metabolic reprogramming is one of the hallmarks of tumorigenesis. Understanding the metabolic changes in cancer cells may provide attractive therapeutic targets and new strategies for cancer therapy. The metabolic states are not the same in different cancer types or subtypes, even within the same sample of solid tumors. In order to understand the heterogeneity of cancer cells, we used the Pareto tasks inference method to analyze the metabolic tasks of different cancers, including breast cancer, lung cancer, digestive organ cancer, digestive tract cancer, and reproductive cancer. We found that cancer subtypes haves different propensities toward metabolic tasks, and the biological significance of these metabolic tasks also varies greatly. Normal cells treat metabolic tasks uniformly, while different cancer cells focus on different pathways. We then integrated the metabolic tasks into the multi-objective genome-scale metabolic network model, which shows higher accuracy in the in silico prediction of cell states after gene knockout than the conventional biomass maximization model. The predicted potential single drug targets could potentially turn into biomarkers or drug design targets. We further implemented the multi-objective genome-scale metabolic network model to predict synthetic lethal target pairs of the Basal and Luminal B subtypes of breast cancer. By analyzing the predicted synthetic lethal targets, we found that mitochondrial enzymes are potential targets for drug combinations. Our study quantitatively analyzes the metabolic tasks of cancer and establishes cancer type-specific metabolic models, which opens a new window for the development of specific anti-cancer drugs and provides promising treatment plans for specific cancer subtypes.
Influence of Outlet Boundary Conditions on Cerebrovascular Aneurysm Hemodynamics

Influence of Outlet Boundary Conditions on Cerebrovascular Aneurysm Hemodynamics by Daniel R. Adrianzen Alvarez Department of Biomedical Engineering Duke University Date:_______________________ Approved: ___________________________ George A. Truskey, Supervisor ___________________________ L. Fernando Gonzalez ___________________________ Amanda Randles ___________________________ David F. Katz An abstract of a thesis submitted in partial fulfillment of the requirements for the degree of Master of Science, in the Department of Biomedical Engineering in the Graduate School of Duke University 2016 Copyright by Daniel R. Adrianzen Alvarez 2016
Machine Learning Based Real-Time Diagnosis of Mental Stress Using Photoplethysmography

Mental stress is a natural response to life activities. However, acute and prolonged stress may cause psychological and heart diseases. Heart rate variability (HRV) is considered an indicator of mental stress and physical fitness. The standard way of obtaining HRV is using electrocardiography (ECG) as the time interval between two consecutive R-peaks. ECG signal is collected by attaching electrodes on different locations of the body, which need a proper clinical setup and is costly as well; therefore, it is not feasible to monitor stress with ECG. Photoplethysmography (PPG) is considered an alternative for mental stress detection using pulse rate variability (PRV), the time interval between two successive peaks of PPG. This study aims to diagnose daily life stress using low-cost portable PPG devices instead of lab trials and expensive devices. Data is collected from 27 subjects both in rest and in stressed conditions in daily life routine. Thirty-six time domain, frequency domain, and non-linear features are extracted from PRV. Multiple machine learning classifiers are used to classify these features. Recursive feature elimination, student t-test and genetic algorithm are used to select these features. An accuracy of 72% is achieved using stratified leave out cross-validation using K-Nearest Neighbor, and it increased up to 81% using a genetic algorithm. Once the model is trained with the best features selected with the genetic algorithm, we used the trained weights for the real-time prediction of mental stress. The results show that using a low-cost device; stress can be diagnosed in real life. The proposed method enable the regular monitoring of stress in short time that help to control the occurrence of psychological and cardiovascular diseases.
A Simulation Study on the Estimation of the Effect in the Hypothetical Scenario of No Use of Symptomatic Treatment in Trials for Disease-Modifying Agents for Alzheimer’s Disease

Abstract In studying a potential disease-modifying treatment for Alzheimer’s Disease, the use of currently available symptomatic medicines—being proportional to the disease progression—can mask the disease-modifying effect. A solution in line with the Estimand framework is to adopt a hypothetical strategy for the intercurrent event “initiation of symptomatic treatment”. However, there is no consensus on reliable estimators for estimands adopting this strategy. To evaluate the performance of several candidate estimators, we have (i) designed clinically realistic data-generating mechanisms based on causal Directed Acyclic Graphs; (ii) selected potentially adequate estimators, amongst other, g-estimation methods usually employed to estimate “controlled direct effect” in mediation analysis; (iii) simulated 10,000 trials for six plausible scenarios and compared the performance of the estimators. The results of our simulations demonstrate that ignoring the intercurrent event introduces a bias compared to the true value of the target estimand. In contrast, g-estimation methods are unbiased, retain nominal power, and control the Type-I error rate at the intended level. Our results can be extrapolated, from a qualitative (absence or presence of bias) but not quantitative point of view (magnitude of the bias), to clinical scenarios with a similar underlying causal structure.
Financial Literacy in Micro-Scale Enterprises Operating in Forest Products Sector

Enterprises are one of the main components of the economic system and they are indispensable for maintaining the sustainability of economic activities. The majority of these enterprises are small and medium-sized enterprises (SMEs). Sustainability of SMEs depends on their good financial management. Inadequate financial literacy causes SMEs’ owners to make inaccurate financial decisions. The forest products sector is mostly composed of micro-scale enterprises in which financial problems are common. Therefore, this study aims to reveal the financial literacy status of the owners of micro-scale and wood-processing enterprises. For this purpose, 78 enterprises were selected as study population. Data were collected by applying a structured questionnaire to 43 of these companies by the face-to-face interview method. The structured questionnaire consisted of multiple-choice and open-ended questions and statements prepared on the Five Likert scales. Data were analysed by using the Independent-Sample T-Test, Mann-Whitney U-Test and correlation test. The reliability coefficient of the data was found to be 0.791. Of the enterprises, 58 % produced in the furniture sub-sector and 42 % in the wood products sub-sector. This study provides evidence that there was no statistically significant difference between the knowledge means of economics and financial behaviour of the furniture and wood products sectors. However, the enterprise owners’ knowledge of financial analysis positively affected their financial literacy and financial behaviour.
A Nationwide Questionnaire Survey on Awake Craniotomy in Japan

The number of awake craniotomies is increasing because of its beneficial features. However, not enough information is available regarding the current status of awake craniotomy in Japan. To evaluate the current status of awake craniotomy in institutes, a nationwide questionnaire survey was conducted. From June to August 2019, we conducted a questionnaire survey on awake craniotomy in the neurosurgery department of 45 institutes that perform awake craniotomies in Japan. Responses were obtained from 39 institutes (response rate, 86.7%). The main methods of awake craniotomy were almost the same in all institutes. Twenty-six institutes (66.7%) had fewer than 10 awake craniotomies (low-volume institutes) per year, and 13 high-volume institutes (33.3%) performed more than 10 awake craniotomies annually. Some institutes experienced a relatively high frequency of adverse events. In 11 institutes (28.2%), the frequency of intraoperative seizures was more than 10%. An intraoperative seizure frequency of 1%-9%, 10%-29%, and over 30% was identified in 12 (92%), 0 (0%), and 1 (8%) of the high-volume institutes, which was significantly less than in 16 (62%), 10 (38%), and 0 (0%) of the low-volume institutes (p = 0.0059). The routine usage of preoperative antiepileptic drugs was not different between them, but the old type was used more often in the low-volume institutes (p = 0.0022). Taken together, the annual number of awake craniotomies was less than 10 in over two-thirds of the institutes. Fewer intraoperative seizures were reported in the high-volume institutes, which tend not to preoperatively use the old type of antiepileptic drugs.
Innovative technique for identification of prestressing tendons layout in post-tensioned bridges using a probe with MEMS accelerometer

Abstract Post-tensioned concrete bridges are currently often constructed engineering structures. In this type of bridges it is crucial that geometrical layout of prestressing system complies with the design requirements. Unfortunately, major errors still occur during assembly of tendon routes. This has often negative effects. In a local aspect, it may cause a local damage, such as spalling of concrete cover. In a global aspect, prestressing may produce distribution of forces in the bridge structure different from the expected. That is why numerous methods have been developed to control the accuracy of executed tendon routs. Some of them, e.g. geodetic measurements with levelers, require direct access to tendon sheaths. Other methods, which can be used after casting of concrete (mainly NDT methods) have a series of resolution, efficiency and accessibility limitations. Hence, the paper presents a proposal of an alternative method for control of tendons routing using a special probe with Micro Electro-Mechanical Systems capacitive accelerometer. The paper presents a concept of tests performed with the probe, evaluation of the probe application in the view of a random process and finally assessment of the results obtained with the use of the constructed measurement system in trial laboratory conditions.
Weather Conditions Influence on Lavandin Essential Oil and Hydrolate Quality

Lavandula sp. essential oil and hydrolate are commercially valuable in various industry branches with the potential for wide-ranging applications. This study aimed to evaluate the quality of these products obtained from L. x intermedia cv. ‘Budrovka’ for the first time cultivated on Fruška Gora Mt. (Serbia) during three successive seasons (2019, 2020, and 2021). Essential oil extraction was obtained by steam distillation, and the composition and influence of weather conditions were also assessed, using flowering tops. The obtained essential oils and hydrolates were analysed by gas chromatography with a flame ionization detector (GC-FID) and gas chromatography coupled to mass spectrometry (GC-MS). A linear regression model was developed to predict L. x intermedia cv. ‘Budrovka’ essential oil volatile compound content and hydrolate composition during three years, according to temperature and precipitation data, and the appropriate regression coefficients were calculated, while the correlation analysis was employed to analyse the correlations in hydrolate and essential oil compounds. To completely describe the structure of the research data that would present a better insight into the similarities and differences among the diverse L. x intermedia cv. ‘Budrovka’ samples, the PCA was used. The most dominant in L. intermedia cv. ‘Budrovka’ essential oil and hydrolate were oxygenated monoterpenes: linalool, 1,8-cineole, borneol, linalyl acetate, and terpinene-4-ol. It is established that the temperature was positively correlated with all essential oil and hydrolate compounds. The precipitations were positively correlated with the main compounds (linalool, 1,8-cineole, and borneol), while the other compounds’ content negatively correlated to precipitation. The results indicated that Fruška Gora Mt. has suitable agro-ecological requirements for cultivating Lavandula sp. and providing satisfactory essential oil and hydrolate.
The ethanol extract of Caragana sinica ameliorated skin lesions in mice with contact dermatitis

Background: Caragana sinica (Buc'hoz) Rehd, which belongs to the legume family, is used to treat a variety of diseases such as gout, high blood pressure, neuralgia, arthritis, and eczema. Morden studies reveal that C. sinica has anti-tumor, anti-viral, anti-hypertensive, immune-stimulatory, immune-suppressive and anti-inflammatory activities. Aims: This study aims to confirm its therapeutic efficacy on contact dermatitis (CD) induced by harmful chemical. Materials and Methods: The dried roots of C. sinica were extracted using 70% ethanol, then the extract was condensed and lyophilized (ethanol extract of C. sinica, [EECS]). We investigated the effects of EECS on skin lesion severities, erythema and melanin indices, skin weights and thicknesses, histopathological changes and cytokine levels in mice with CD induced by 1-fluoro-2,4-dinitrofluorobenzene. In addition, the effects on changes in body weight and spleen body weight ratios were also investigated. Results: EECS relieved skin lesions such as roughness, abrasions, scabs, erythema, and petechia, inhibited thickening of dorsal skin and lowered erythema and melanin indexes in the CD mice. Besides, EECS reduced epidermal hyperplasia and immune cell infiltration into inflamed tissues and reduced levels of Tumor necrosis factor-α, interferon-γ, interleukin-6, and monocyte chemotactic protein-1 (MCP-1) in inflamed tissues. Finally, body weight gains and spleen/weight ratios of CD mice were unaffected by EECS, unlike dexamethasone treatment. Conclusion: These results suggest that C. sinica has potential use as a therapeutic agent for CD and the therapeutic mechanism is different from that of corticosteroids.
ISMJ International SportMed Journal Physical and technical activity of soccer players in the French First League - with special reference to their playing position

Background: The aim of this study was to analyze the physical and technical activities of elite soccer players from the French First League, according to their playing positions. Methods: During the 2005-2006 season, 3540 professional soccer players’ activities were recorded and analysed during competitive matches played by means of a semi-automatic video system (Amisco ©). Physical and technical variables were analyzed according to their specific playing positions. The players were classified into 6 positional roles: central defenders (CD), full-backs (FB), central defensive midfielders (CDM), wide midfielders (WM), central attacking midfielders (CAM), and forwards (FW). Match performance variables analysed included: (a) physical activity: total distance covered, distances covered at high-intensities both with and without possession of the ball; (b) technical actions: heading and ground duels, passing, time in possession and ball touches. Results: The total distances covered ranged from 10425.9m to 12029.5m, with especially 235.4m to 290.4m in sprinting. In the offensive phase, FW covered ~4 times greater total distances in sprinting than CD and FB (p <0.001). The technical analysis showed that the players had the possession of the ball between 55.5sec and 74.2sec per match played and they had no more than 2.2 ball touches per individual possession. More specifically, midfielders (CDM, WM and CAM) performed successful passes ranging from 75% to 78%, whereas lower values were found for the FW (71%) and CD (63%) respectively. Conclusions: Soccer at the elite level requires that the players have a high aerobic capacity and that they are able to perform many high-intensity actions, especially the capacity for repeated sprints. Although these main findings showed the characteristics of French elite soccer, the players have to be skilful with their few ball possessions. In conclusion, elite soccer is characterized by the ability of the players to repeat high-intensity actions, but almost to be able to lose a small part of their ball possessions and to realize quickly the technical actions during the matches played.
Preparing Early Childhood Teachers for Managing Emergencies

The COVID-19 pandemic has revealed the reality of life in all aspects of human endeavors. The education sector was not spared-the school system was uprooted and procedures had to be made quickly for the safety of students and faculty. As a result, educators struggled with keeping students engaged academically during online learning and the stress of a health crisis on society. Preparing Early Childhood Teachers for Managing Emergencies explores international and cross-cultural perspectives on teacher effectiveness in handling education and learning in emergency periods as well as preparedness for post-COVID-19 experiences. This book identifies, shares, and explores the predominant theoretical and conceptual understandings of teacher preparedness toward emergencies and the aftermath. Covering topics such as first aid measures, teacher effectiveness, and technology usage, this book is an essential resource for global K-12 educators, pre-service teachers, K-12 administrators, policymakers, researchers, and academicians. © 2022 by IGI Global. All rights reserved.
Study on Structural Evolution of Synthetic Graphite Derived from Lignite Prepared by High Temperature–High Pressure Method

Abundant and cheap lignite is regarded as inferior fuel due to its disadvantages such as low heat and high moisture. In order to realize the high value and clean, non-fuel utilization of lignite, we used lignite as precursor to prepare high-quality synthetic graphite through graphitization treatment using the high temperature–high pressure (HTHP) method, and afterwards characterized the samples by XRD, Raman, FTIR, SEM-EDS, and HRTEM, and systematically analyzed the effect of P-T conditions on the structure evolution of lignite. Our results demonstrated that temperature dominates the graphitization of lignite, and high pressure accelerates the graphitization process of lignite. Under HTHP treatment, the aromatic layer of lignite accelerates directional rearrangement; the ordered domain increases rapidly, and the ductility and stacking degree of the carbon sheets of the lignite sample are greatly enhanced. Compared with the traditional high-temperature graphitization method, the HTHP method greatly reduces the graphitization temperature and shortens the graphitization time. Remarkably, the as-prepared graphite with a graphitization degree of 91.87% superior to graphite fabricated by the conventional high-temperature processing were rapidly prepared from lignite at 6 GPa and 1300 °C in 20 min. This study demonstrates that the HTHP method is a feasible and effective method to realize the green, efficient, and high value utilization of lignite.
Influence of choline-based ionic liquids as neoteric green solvents on aqueous solubility of lamotrigine and piroxicam drugs

Background: The low aqueous solubility of three important drugs (betamethasone (BETA), meloxicam (MEL) and piroxicam (PIR)) have been increased by use of deep eutectic solvents (DESs) based choline chloride/urea (ChCl/U), choline chloride/ethylene glycol (ChCl/EG) and choline chloride/glycerol (ChCl/G) as new class of solvents at T = (298.15 to 313.15) K. Methods: DESs were prepared by combination of the ChCl/EG, U and G with the molar ratios: 1:2. The solubility of drugs in the aqueous DESs solutions was measured at different temperatures with shake flask method. Results: The solubility of the investigated drugs increased with increasing the weight fraction of DESs. The solubility data were correlated by e-NRTL and Wilson models. Also, the thermodynamic functions, Gibbs energy, enthalpy, and entropy of dissolution were calculated. Conclusion: At the same composition of co-solvents and temperature, the BETA, PIR and MEL solubility was highest in (ChCl/U + water), (ChCl/U + water) and (ChCl/EG + water) respectively. The calculated solubility based on these models was in good agreement with the experimental values. In addition, the results show that, the main contribution for drugs solubility in the aqueous DES solutions is the enthalpy.
Data report: terrigenous grain-size distributions at Sites 1263 and 1267: testing the applicability of Leg 208 sediments for eolian analysis.

To date, the only Southern Hemisphere eolian grain-size record constructed for the early Paleogene comes from Deep Sea Drilling Project Site 215. Ten early Paleogene sediment samples from Site 215 were collected and processed to show that the existing eolian grain-size record at this site can be reproduced. Five samples each from Ocean Drilling Program Sites 1263 and 1267 were similarly examined to test the possibility of generating new Southern Hemisphere eolian grain-size records for the early Paleogene. Our results indicate that an eolian grain-size signal can be constructed at Walvis Ridge, although the record will be complicated by hemipelagic terrigenous inputs. Further, we assert that a record generated at a site located on the deep flanks of Walvis Ridge is particularly susceptible to hemipelagic influence.
Re-Identification of Giant Sunfish using Keypoint Matching

We present the first work where re-identification ofthe Giant Sunfish (Mola alexandrini) is automated using computer vision and deep learning. We propose a pipeline that scores an mAP of 60.34% on a full rank of the novel TinyMola dataset which includes 31 IDs and 91 images. The method requires no domain-adaptation or training which makes it especially suited for low-budget or volunteer-based projects, like Match My Mola, as part of a human-in-the-loop model. The pipeline includes segmentation, keypoint detection and description, keypoint matching, and ranking. The choice of feature descriptor has the largest impact on the performance and we show that the deep learning based SuperPoint descriptor greatly outperforms handcrafted descriptors like SIFT and RootSIFT independent of the segmentation level and matching method. Combining SuperPoint and the graph neural network based SuperGlue matching method produces the best results.