Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating science teachers' understanding and teaching of complex systems

This study investigates science teachers' understanding and teaching of complex systems. The field of complex systems is the study of how parts of a system give rise to its collective behaviors. Since the 1990s, scientific and educational agencies have advocated the importance of complex systems in science education. Despite this call for instructional emphasis in complex systems, recent studies have shown that students continue to have poor understanding of these systems. Current efforts in addressing this problem have focused on promoting student learning of complex systems. There are also a few studies that examine this problem from a teacher perspective. While these endeavors have yielded various successes and discoveries, the findings concerning teachers' complexity understanding and instructional practices are not conclusive. This is because most studies are small-scale, involve selective teachers, or investigate singular aspects of complex systems understanding. In short, we have yet to gain a thorough insight of the extent science teachers understand and teach complex systems. This research addresses the gaps directly by looking at science teachers' understanding and teaching of complex systems. It examines what they know and teach about complex systems, how their instructional practices may be influenced by their understanding and why the ideas may be difficult to comprehend and teach. This research was conducted with 90 11th and 12th grades science teachers across six Singapore schools. A mixed methods design was used. The findings revealed that while science teachers might appreciate the complex nature of systems, their understanding was not comprehensive: few teachers had prior knowledge of this domain; and certain complex systems ideas appeared better understood than others. It was also found that complex systems ideas were conveyed in science lessons but the extent the ideas were taught was uneven. These ideas were conveyed more often in biology than in chemistry and physics, and certain ideas were more explicitly taught. Teachers with better complex systems understanding were also better able to convey these ideas in their lessons. Several reasons impeding teachers' understanding and teaching of complex systems were also revealed. Implications for research and professional development for science teachers are discussed. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Education First Advisor Susan A. Yoon This dissertation is available at ScholarlyCommons: http://repository.upenn. edu/edissertations/1057
Accumulation of lipid peroxidation‐derived DNA lesions in iron‐overloaded thalassemic mouse livers: Comparison with levels in the lymphocytes of thalassemia patients

In thalassemia patients, iron overload can stimulate lipid peroxidation (LPO), thereby generating miscoding DNA adducts. Adducted DNA was measured in the lymphocytes of β‐Thal/Hb E patients and healthy controls and in the organs of thalassemic mice. εdA, εdC and M1dG residues were quantified by 32P‐postlabeling‐TLC/HPLC. M1dG levels in lymphocyte DNA from patients were 4 times as high as in controls, while the increase in εdA and εdC was not significant. Adducted DNA accumulated in the liver of thalassemic mice having >2.7 mg Fe/g tissue dry weight; DNA adducts and iron were highly correlated. εdA was not specifically generated in certain mouse liver cell types as revealed by immunohistochemical staining. We found elevated LPO‐induced DNA damage in the liver of thalassemic mouse and in lymphocytes, implicating that massive DNA damage occurs in the liver of thalassemia patients. We conclude that promutagenic LPO‐derived DNA lesions are involved in the onset of hepatocellular carcinoma in these patients. © 2009 UICC
Share Price Formation, Market Exuberance and Accounting Design

This paper develops a theoretical analysis of share market price formation driven by accounting and market structures. Interacting heterogeneous investors are assumed to discover and process fundamental information disclosed by accounting system of share-issuing entity. Information set available to share market investors for decision-making comprises then market-driven and firm-specific (non-market) information. From one side, accounting system provides collective signal of fundamental information; from another side, price system provides collective signal of market-driven information over time. Both jointly drive the formation of aggregate share market prices through limited knowledge, hazard, and social interaction. Numerical simulations are provided under alternative accounting regimes (namely, historical cost and fair value accounting regimes), to derive implications and recommendations for the concept and occurrence of speculative bubbles and herd behavior; the cyclical effects of accounting regime on share market price dynamics; and the "value relevance" of accounting information and its role in the formation of share market prices over time.This numerical statistical analysis contributes to shed light on financial stability, market exuberance, accruals accounting anomalies and fundamental analysis.
Manufacturing Plant Closure Selections within Firms

Abstract This research focuses on the influence of location on the decision to close a manufacturing facility. Case studies of closures in the Cincinnati region, 1980–88, reveal that most closures are little affected directly by location, with corporate difficulties and plant characteristics being more significant. Approximately two-thirds of the closures were forced on the firm by severely inadequate profits. Analyses of selective closures within multiplant firms show that the most vulnerable are inappropriately sized and less technologically sophisticated plants. Regional variables such as taxes, business climate, and declines in local market demand or access to supplies are not often important. Relative location within the firm or within the metropolitan area also are not significant. The one regional exception is labor; plants deemed to be in areas of poorer labor relations and/or higher labor costs are more likely to be selected for closure. The appropriate locational model for plant closure is not t.
European Integration and Democratic Consolidation: Spain, Poland and Turkey in Comparative Perspective

The study explored when, under what conditions, and to what extent did European integration, particularly the European Union’s requirement for democratic conditionality, contribute to democratic consolidation in Spain, Poland, and Turkey? On the basis of a four-part definition, the dissertation examined the democratizing impact of European integration process on each of the following four components of consolidation: (i) holding of fair, free and competitive elections, (ii) protection of fundamental rights, including human and minority rights, (iii) high prospects of regime survival and civilian control of the military, and (iv) legitimacy, elite consensus, and stateness. To assess the relative significance of EU’s democratizing leverage, the thesis also examined domestic and non-EU international dynamics of democratic consolidation in the three countries.By employing two qualitative methods (case study and process-tracing), the study focused on three specific time frames: 1977-1986 for Spain, 1994-2004 for Poland, and 1999-present for Turkey. In addition to official documents, newspapers, and secondary sources, face-to-face interviews made with politicians, academics, experts, bureaucrats, and journalists in the three countries were utilized.The thesis generated several conclusions. First of all, the EU’s democratizing impact is not uniform across different components of democratic consolidation. Moreover, the EU’s democratizing leverage in Spain, Poland, and Turkey involved variations over time for three major reasons: (i) the changing nature of EU’s democratic conditionality over time (ii) varying levels of the EU’s credible commitment to the candidate country’s prospect for membership, and (iii) domestic dynamics in the candidate countries. Furthermore, the European integration process favors democratic consolidation but its magnitude is shaped by the candidate country’s prospect for EU membership and domestic factors in the candidate country. Finally, the study involves a major policy implication for the European Union: unless the EU provides a clear prospect for membership, its democratizing leverage will be limited in the candidate countries.
Speech emotion recognition with deep learning

This paper describes a method for Speech Emotion Recognition (SER) using Deep Neural Network (DNN) architecture with convolutional, pooling and fully connected layers. We used 3 class subset (angry, neutral, sad) of German Corpus (Berlin Database of Emotional Speech) containing 271 labeled recordings with total length of 783 seconds. Raw audio data were standardized so every audio file has zero mean and unit variance. Every file was split into 20 millisecond segments without overlap. We used Voice Activity Detection (VAD) algorithm to eliminate silent segments and divided all data into TRAIN (80%) VALIDATION (10%) and TESTING (10%) sets. DNN is optimized using Stochastic Gradient Descent. As input we used raw data without and feature selection. Our trained model achieved overall test accuracy of 96.97% on whole-file classification.
Novel knowledge-based mean force potential at atomic level.

We present a new approach at the atomic level for the development of knowledge-based mean force potentials (MFPs) that can be used in fold recognition, ab initio structure prediction, comparative modelling and molecular recognition. Our method is based on atom-type definitions, raising the total frequency of the pairwise distributions and leading to very accurate and specific distance-dependent energy functions. Forty different heavy atom types were defined depending on their bond connectivity, chemical nature and location level (side-chain or backbone). Using this approach it has been possible to obtain average frequencies of pairwise contacts about 15 times higher than the ones obtained using the classic way of one heavy atom definition for each amino acid (i.e. alpha-carbon, beta-carbon, virtual centroid or virtual beta-carbon co-ordinates). In this paper we use this approach to develop a MFP that can be used in fold recognition and we compare it with a classic MFP at the amino acid level compiled from the alpha-carbon distances between the different amino acid pairs. Both potentials involve all the pairwise contacts extracted from a non-redundant folds database of 180 protein chains with a sequence identity threshold of 25%. The pairwise energy functions of the MFP at the atomic level have a deep and very well defined minimum for each pairwise interaction, in contrast to the same curves obtained from the MFP developed at the amino acid level, which generally have multiple minima with similar depth. Our results also show that this MFP is able to produce very similar energy profiles for couples of proteins that share a very low sequence identity but are closely related at the structural level. When these profiles are plotted considering the structure-structure alignment, they are mostly superimposed, showing a correlation with the structure-structure similarity. In the same test, the MFP at the amino acid level fails to produce similar profiles. We suggest that using this MFP at the atomic level in the last stages of fold recognition or threading, when some candidates are available, can improve the sequence-structure alignments and, therefore, the final models. We also discuss the possibility of using this approach in the development of new MFPs to be used in ab initio structure prediction, comparative modelling and molecular recognition procedures.
Monitoring training with heart rate-variability: how much compliance is needed for valid assessment?

PURPOSE To establish the minimum number of days that heart-rate-variability (HRV, ie, the natural logarithm of square root of the mean sum of the squared differences between R-R intervals, Ln rMSSD) data should be averaged to achieve correspondingly equivalent results as data averaged over a 1-wk period. METHODS Standardized changes in Ln rMSSD between different phases of training (normal training, functional overreaching (FOR), overall training, and taper) and the correlation coefficients of percentage changes in performance vs changes in Ln rMSSD were compared when averaging Ln rMSSD from 1 to 7 d, randomly selected within the week. RESULTS Standardized Ln rMSSD changes (90% confidence limits, CL) from baseline to overload (FOR) were 0.20 ± 0.28, 0.33 ± 0.26, 0.49 ± 0.33, 0.48 ± 0.28, 0.47 ± 0.26, 0.45 ± 0.26, and 0.43 ± 0.29 on days 1 to 7, respectively. Correlations (90% CL) over the same time sequence and training phase were -. 02 ± . 23, -. 07 ± . 23, -. 17 ± . 22, -. 25 ± . 22, -. 26 ± . 22, -. 28 ± . 21, and -. 25 ± . 22 on days 1 to 7. There were almost perfect quadratic relationships between standardized changes/r values vs the number of days Ln rMSSD was averaged (r2 = .92 and .97, respectively) in trained triathletes during FOR. This indicates a plateau in the increase in standardized changes/r values' magnitude after 3 and 4 d, respectively, in trained triathletes. CONCLUSION Practitioners using HRV to monitor training adaptation should use a minimum of 3 (randomly selected) valid data points per week.
Laparoscopic live donor left lateral sectionectomy is safe and feasible for pediatric living donor liver transplantation.

BACKGROUND/AIMS Compared to the open method of left lateral sectionectomy, the laparoscopic method has demonstrated shorter hospital stay with less bleeding and complications and is becoming the gold standard procedure. We report our experience with 15 Iaparoscopic left lateral sectionectomies performed during PLDLTs from May 2008. METHODOLOGY From May 2008 to April 2010, there were 15 cases where laparoscopic left lateral sectionectomy was performed for donor hepatectomy. All cases were performed by a sin-gle surgeon. RESULTS The mean size of the actual graft was 248.8±52.8mL (range 150-350). The mean operation time was 331.3+63.1 minutes (range 220-480),the mean blood loss was 410.0+71.2mL (range 250-500) and the mean warm ischemic time was 5.8+1.6 minutes (range 4-10). The mean time to oral intake was 2.0±0.3 days (range 1-3) and the mean hospital stay was 7.1+0.8 days (range 6-10). There were no complications or deaths among donors postoperative-ly. CONCLUSIONS We believe it is a safe and reproducible procedure and an especially useful procedure for young mother donors who desire small wounds and rapid recovery.
Comparison of preservation values between Internet and interview survey modes: the case of Dokdo, South Korea

With the increase in employment of Internet surveys, there is a need to address how this survey mode affects inferences. Internet and interview modes are compared in estimating the preservation value of Dokdo, South Korea. Estimates of willingness to pay in the Internet survey are smaller than those in the interview survey. This may be attributable to the interview respondents being conscious of the presence of the interviewers, given the social importance of Dokdo to Koreans. Internet surveys may be effective in reducing overestimation of the willingness to pay in situations where potential social desirability is present.
Cumulative Energy and Global Warming Impact from the Production of Biomass for Biobased Products

The cumulative energy and global warming impacts associated with producing corn, soybeans, alfalfa, and switchgrass and transporting these crops to a central crop processing facility (called a “biorefinery”) are estimated. The agricultural inputs for each crop are collected from seven states in the United States: Illinois, Indiana, Iowa, Michigan, Minnesota, Ohio, and Wisconsin. The cumulative energy requirement for producing and transporting these crops is 1.99 to 2.66 megajoules/kilo‐gram (MJ/kg) for corn, 1.98 to 2.04 MJ/kg for soybeans, 1.24 MJ/kg for alfalfa, and 0.97 to 1.34 MJ/kg for switchgrass. The global warming impact associated with producing biomass is 246 to 286 grams (g) CO2 equivalent/kg for corn, 159 to 163gCO2 equivalent/kg for soybeans, 89 g CO2 equivalent/ kg for alfalfa, and 124 to 147 g CO2 equivalent/kg for switch‐grass. The detailed agricultural data are used to assess previous controversies over the energy balance of bioethanol and, in light of the ongoing debates on this topic, provide a needed foundation for future life‐cycle assessments.
The practice of corporate social responsibility by Malaysian developers

Purpose – The purpose of this research is to assess the implementation of sustainable practice by Malaysian property developers, particularly on social and environmental perspectives.Design/methodology/approach – This is a qualitative research where content analysis is used to analyse leading property companies’ websites, annual reports, corporate responsibility and sustainability reports, and carbon disclosure reports.Findings – Findings from this research indicate that the majority of the developers have their corporate social responsibility (CSR) initiatives in place and there are variations in their approaches and reporting process. Of all, philanthropic activities are the mostly widely reported followed by human resource initiatives. Even though the majority of property companies reported their environmental practices, only the top few developers had their projects certified by sustainability rating agencies.Research limitations/implications – As this project was restricted to the top ten Malaysian d.
Proteomic patterns of preinvasive bronchial lesions.

PURPOSE A proteomics approach is warranted to further elucidate the molecular steps involved in lung tumor development. We asked whether we could classify preinvasive lesions of airway epithelium according to their proteomic profile. EXPERIMENTAL DESIGN We obtained matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiles from 10-microm sections of fresh-frozen tissue samples: 25 normal lung, 29 normal bronchial epithelium, and 20 preinvasive and 36 invasive lung tumor tissue samples from 53 patients. Proteomic profiles were calibrated, binned, and normalized before analysis. We performed class comparison, class prediction, and supervised hierarchic cluster analysis. We tested a set of discriminatory features obtained in a previously published dataset to classify this independent set of normal, preinvasive, and invasive lung tissues. RESULTS We found a specific proteomic profile that allows an overall predictive accuracy of over 90% of normal, preinvasive, and invasive lung tissues. The proteomic profiles of these tissues were distinct from each other within a disease continuum. We trained our prediction model in a previously published dataset and tested it in a new blinded test set to reach an overall 74% accuracy in classifying tumors from normal tissues. CONCLUSIONS We found specific patterns of protein expression of the airway epithelium that accurately classify bronchial and alveolar tissue with normal histology from preinvasive bronchial lesions and from invasive lung cancer. Although further study is needed to validate this approach and to identify biomarkers of tumor development, this is a first step toward a new proteomic characterization of the human model of lung cancer tumorigenesis.
Cost-effective DAC/ADC-induced impacts on DSP-enabled flexible ROADM free from O-E-O conversion and optical filter

Utilizing Hilbert-pair-based digital filtering, intensity modulation and passive optical coupling, DSP-enabled optical filter- and O-E-O conversion-free ROADMs have been reported to offer excellent flexibility, colorlessness, gridlessness, contentionlessness, adaptability and transparency to physical-layer network characteristics. In this paper, DAC/ADC-induced impacts on ROADM performances are, for the first time, extensively explored in various IMDD-based optical network nodes. Numerical results indicate that for optical and electrical filters-free network nodes, ROADM has excellent performance robustness against the DAC characteristic variations, however high-resolution ADCs are required to improve the ROADM drop performances. While when equipping the network nodes with electrical baseband filters, ROADM drop operation performance robustness against the DAC/ADC characteristic variations is considerably improved and the low-cost ADCs with much lower resolutions and sampling speeds are also tolerable to be used in demodulating the dropped signals.
Withania somnifera shows a protective effect in monocrotaline-induced pulmonary hypertension

Abstract Context: Withania somnifera (Linn.) Dunal (Solanaceae), a clinically used herbal drug in Ayurveda, shows potent antioxidant, anti-inflammatory, pro-apoptotic, and cardioprotective effects. However, the efficacy of W. somnifera in pulmonary hypertension (PH), a cardiopulmonary disorder, remains unexplored. Objective: The present study investigates the effect of W. somnifera root powder on monocrotaline (MCT)-induced PH in rats. Materials and methods: In preventive studies, W. somnifera root powder (50 and 100 mg/kg/d, p.o.) was administered from day 1 following single administration of MCT (60 mg/kg, s.c.) in Sprague–Dawley (SD) rats. After 35 d, right ventricular pressure (RVP) was measured in anesthetized rats. Various physical markers of right ventricular hypertrophy (RVH) were measured in isolated hearts. Markers of endothelial function, inflammation, and oxidative stress were estimated in lung homogenate. Vasoreactivity of pulmonary arteries was also studied. In therapeutic treatment, W. somnifera (50 and 100 mg/kg/d, p.o.) was administered from day 21 to 35 post-MCT administration. Results: Preventive treatment with 50 and 100 mg/kg W. somnifera significantly reduced the RVP (32.18 ± 1.273 mm Hg and 29.98 ± 1.119 mm Hg, respectively, versus 42.96 ± 1.789 mm Hg of MCT) and all markers of RVH in MCT-challenged rats. There was an improvement in inflammation, oxidative stress and endothelial dysfunction, and attenuation of proliferative marker and apoptotic resistance in lungs. Therapeutic treatment with W. somnifera (100 mg/kg) also reduced RVP and RVH. Discussion: This study demonstrated that W. somnifera significantly protected against MCT-induced PH due to its antioxidant, anti-inflammatory, pro-apoptotic, and cardioprotective properties.
A Markov random field model-based approach to image interpretation

A Markov random field (MRF) model-based approach to automated image interpretation is described and demonstrated as a region-based scheme. In this approach, an image is first segmented into a collection of disjoint regions which form the nodes of an adjacency graph. Image interpretation is then achieved through assigning object labels, or interpretations, to the segmented regions, or nodes, using domain knowledge, extracted feature measurements, and spatial relationships between the various regions. The interpretation labels are modeled as a MRF on the corresponding adjacency graph, and the image interpretation problem are formulated as a maximum a posteriori estimation rule. Simulated annealing is used to find the best realization, or optimal interpretation. Through the MRF model, this approach also provides a systematic method for organizing and representing domain knowledge through the clique functions of the probability density function underlying MRF. Results of image interpretation experiments performed on synthetic and real-world images using this approach are described. <<ETX>>