Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence of Asthma Characteristics in COPD Patients in a Dutch Well-Established Asthma/COPD Service for Primary Care

Purpose Primary care COPD guidelines indicate that COPD patients with asthma characteristics should be treated as having asthma. This study aims to describe the prevalence of asthma characteristics in patients with a pulmonologist-confirmed working diagnosis of COPD or ACO. Patients and Methods This retrospective cross-sectional study used real-life data (collected between 2007 and 2017) from a Dutch asthma/COPD-service, a structured web-based system in which pulmonologists support general practitioners in their diagnosis of patients with suspicion of obstructive lung disease. The prevalence of asthma characteristics (history of asthma, atopy, symptoms, and reversibility) and blood eosinophil (Eos) counts were assessed in patients with a working diagnosis of COPD or ACO. Results Of the 14,141 patients, ≥40 years in the dataset, 4475 (31.6%) were diagnosed with asthma, 3532 (25.0%) with COPD, and 1276 (9.0%) with ACO. Asthma characteristics were present in 65.6% (n=1956) of the COPD and 90.9% (n=1059) of the ACO patients. Eos counts of ≥ 300 cells per μL were found in 35.7% (n=924) of the COPD patients and 35.3% (n=341) of the ACO patients. Conclusion In this group of COPD and ACO patients remotely diagnosed by pulmonologists, a substantial proportion would be considered to have asthma characteristics according to the guidelines. This may explain the high number of inhaled corticosteroid (ICS) prescriptions found in primary care COPD patients. Prospective studies are necessary to identify patients who may or may not benefit from ICS containing treatment. Hence, personalized care in primary care can be optimized.
Screening for diabetic retinopathy.

In this issue, Malone et al. (1) use their analysis of the retinal photographs taken in the Diabetes Control and Complications Trial (DCCT) to try to challenge the well-established dictum that it is not useful to perform early screening (<5 years duration) for diabetic retinopathy in juvenile-onset type 1 diabetes. I share their enthusiasm for preventing vision loss; however, in my judgment, the data do not support their challenge, but rather strongly support the current recommendation. Screening examinations or any tests performed in medicine should only be done when the results have a reasonable probability of altering the treatment, when the risk-to-benefit ratio of undergoing the test is favorable for the individual patient, and when the cost-to-benefit ratio is competitive with other uses of health care dollars. Early screening for diabetic retinopathy in juvenile-onset type 1 diabetes fails on all three counts. First, consider that not one of the 1,613 patients screened for the DCCT at <5 years duration of diabetes had …
A Filter Based Improved Decision Tree Sentiment Classification Model for RealTime Amazon Product Review Data

: E-Commerce product features and reviews are considered to be the essential factors in real-time e-commerce sites for product recommendation systems. Due to inaccuracy decision patterns, in most cases e-commerce user fails to predict the products based on the user ratings and review comments. Traditional sentiment classification models are independent of data filtering, transformation and sentiment score computing techniques which require high computing memory, time and mostly leading to false-positive rate. To overcome these issues, a novel sentiment score-based product recommendation model is proposed on the real-time product data. In this model, a new product ranking score, filtering, and hybrid decision tree classifiers are implemented. Initially, real-time amazon product review data is captured using Document Object Model (DOM) parser. The features from the review comments are extracted using lexicon Feature Dictionary (FD) and AFINN, Normalized Product Review Score (NPRS) are generated to compute the class label for product review sentiment prediction. Ranked Principal Component Analysis (RPCA) is used as a feature selection measure to overcome the problem of data sparsity. Random Tree, Hoeffding Tree, Adaboost + Random Tree, the three variants of decision tree classifiers are used for product sentiment classification. The proposed filter-based improved decision tree sentiment classification model for real-time amazon product review data recommends the product based on the user query by prediction using a new novel normalized product review sentiment score and ranked feature selection measure. The proposed product recommendation, the decision-making system maximizes sentiment classification accuracy. Experimental results are compared against the traditional decision-making classification models in terms of correctly classified instances, error rate, and PRC, F-measure, kappa statistics. The proposed model experimental results show high efficiency
Observations of Hail–Wind Ratios from Convective Storm Reports across the Continental United States

The objective of this study is to provide guidance on when hail and/or wind is climatologically most likely (temporally and spatially) based on the ratio of severe hail reports to severe wind reports, which can be used by National Weather Forecast (NWS) forecasters when issuing severe convective warnings. Accordingly, a climatology of reported hail-to-wind ratios (i.e., number of hail reports divided by the number of wind reports) for observed severe convective storms was derived using U.S. storm reports from 1955 to 2017. Owing to several temporal changes in reporting and warning procedures, the 1996–2017 period was chosen for spatiotemporal analyses, yielding 265 691 hail and 294 449 wind reports. The most notable changes in hail–wind ratios occurred around 1996 as the NWS modernized and deployed new radars (leading to more hail reports relative to wind) and in 2010 when the severe hail criterion increased nationwide (leading to more wind reports relative to hail). One key finding is that hail–wind ratios are maximized (i.e., relatively more hail than wind) during the late morning through midafternoon and in the spring (March–May), with geographical maxima over the central United States and complex/elevated terrain. Otherwise, minimum ratios occur overnight, during the late summer (July–August) as well as November–December, and over the eastern United States. While the results reflect reporting biases (e.g., fewer wind than hail reports in low-population areas but more wind reports where mesonets are available), meteorological factors such as convective mode and cool spring versus warm summer environments also appear associated with the hail–wind ratio climatology.
In-Situ Fatigue Prediction of Direct Laser Deposition Parts Based on Thermal Profile

Additive manufacturing (AM) is a novel fabrication technique which enables production of very complex designs that are not feasible through conventional manufacturing techniques. However, one major barrier against broader adoption of additive manufacturing processes is concerned with the quality of the final products, which can be measured as presence of internal defects, such as pores and cracks, affecting the mechanical properties of the fabricated parts. In this paper, a data-driven methodology is proposed to predict the size and location of porosities based on in-situ process signatures, i.e. thermal history. Size as well as location of pores highly affect the resulted fatigue life where near-surface and large pores, compared to inner or small pores, significantly reduces the fatigue life. Therefore, building a model to predict the porosity size and location will pave the way toward building an in-situ prediction model for fatigue life which would drastically influence the additive manufacturing community. The proposed model consists of two phases: in Phase I, a model is established to predict the occurrence and location of small and large pores based on the thermal history; and subsequently, a fatigue model is trained in Phase II to predict the fatigue life based on porosity features predicted from Phase I. The model proposed in Phase I is validated using a thin wall fabricated by a direct laser deposition process and the Phase II model is validated based on fatigue life simulations. Both models provide promising results that can be further studied for functional outcomes.
Resident Attitudes Toward Timber Rattlesnakes (Crotalus horridus)

Abstract Timber rattlesnakes (Crotalus horridus) are endangered throughout the northeastern United States where multiple factors contribute to population declines. Challenges exist to managing rattlesnake populations because there is little information about human dimensions of this species or other small predators that are venomous or perceived as hazardous. Our objective was to evaluate relationships between resident attitudes and behavioral intentions toward timber rattlesnakes. A mail survey (n = 593) was used to collect data from residents who live near a rattlesnake population in central Connecticut. Two variables defined resident attitudes toward rattlesnakes: coexistence with the species and perceived threats from the species. Rattlesnake-related factors and situational factors appeared to contribute more heavily to behavioral intentions toward rattlesnakes than general wildlife value orientations. Attitudes predicted behavioral intentions toward rattlesnakes. Results will help wildlife managers incorporate human factors into appropriate management and public outreach strategies.
Lung cancer screening: are we ready now?

Lung cancer is main oncologic cause of death worldwide, because diagnosis is usually reached with symptomatic advanced stage disease. Reduction of lung cancer mortality could be reached especially by primary prevention because cigarette smoke is exceptionally associated with increased risk of lung cancer. Primary prevention would also grant reduction of other pulmonary (chronic obstructive pulmonary disease) and extra-pulmonary diseases (cardiovascular events, colonic cancer). Secondary prevention by early diagnosis of lung cancer is another option, apparently easier to propose to high-risk subjects, but much more expensive than primary prevention. Screening by annual low-dose computed tomography (LDCT) is currently implemented in the United States, following evidence of significant reduction in mortality from lung cancer and overall mortality. European countries have not reported efficacy of annual LDCT, currently there are results from an Italian pooled analysis that reports indeed a trend for mortality reduction, yet not significant. Pre-test selection of highrisk population, interval length of LDCT rounds, and definition of positive finding are the main topics of discussion to achieve better harm/benefit ratio from LDCT screening. Comprehensive and simple risk model for selection of subjects with relatively high risk of lung cancer is paramount for optimization of LDCT screening, furthermore subjective risk prediction by biological sampling is under investigation. Biennial and annual screening rounds might have equal performance in lung cancer detection, notably with reduction of LDCT performed. Volumetric quantification of nodules at baseline and volume doubling time for assessment of progression increase the accuracy of the test, thus reducing the number of false positive and the risk of surgery for benign disease. Nevertheless, smoking cessation is the most effective strategy for reduction of mortality, hence smoking cessation program must be integrated in case of implementation of national lung cancer screening program.
Investigating the Perception of Public Sector Higher Education Institution Faculty Members about the Influences of Psychological Contract on Organizational Commitment

The core aim of this research study is to investigate the consequences of psychological contract on organizational commitment. The context of the study is higher educational Institution International Islamic University Islamabad. Data is collected from 90 faculty members of International Islamic University Islamabad through questionnaire by using the convenience sampling approach. The alpha index is using minimum (0.60) to measure the item reliability. Regression analysis indicates that psychological contract is positively and significantly associated with affective commitment (0.55), continuance commitment (0.74), and the normative commitment (0.69). From the findings, it is concluded that psychological contract is very important for organizational commitment. Higher degree of psychological contract has a result of more organizational commitment. This paper recommended that higher educational institutes should focus on developing a positive and healthy psychological contract with employees. Failure to do so may result in unhealthy psychological contract and can produce negative employee related outcomes.
Effect of Smoking on Appetite, Concentration and Stress Level

Objective- Smokers often report that cigarette relieve feeling of stress, improve mood and concentration and can decrease their appetite level. To identify weather a cigarette is a mood altering and appetite suppressant we study the effect of smoking on concentration, stress and appetite level among smokers. Design- We examined if there is a relation between smoking and other variables (age, gender and working hours per week). Several data collected in the form of surveys from smokers and non-smokers and then analyzed using a software program SPSS. Main outcome- Results according to smoker's majority shows that cigarette decrease their stress level and it has been shown that it’s the most affected parameters compared to concentration and appetite level that are affected also by smoking. Results- The results of this study show that smoking is related to age and it is affected by the number of working hours. Participants aged between 14 and 35 years, that include students, unemployed and hard-workers smoke the most and have the highest number of cigarettes per week. Conclusion- Based on our study, smoking has an effect on appetite, concentration and stress that is correlated with working hours.
A Novel Low Output Offset Voltage Charge Amplifier for Piezoelectric Sensors

The charge amplifier is an important building block in various electronic circuits. In this paper a new charge amplifier for piezoelectric sensors is introduced. The advantages of the new proposed charge amplifier becomes obvious in the quasi-static applications. In some quasi-static applications the traditional charge amplifiers uses an extremely large feedback resistor (in the range of $\text{G}\Omega $ ) whereas the proposed charge amplifier no longer requires such extremely large resistors. Moreover the proposed circuit reduces the output offset voltage significantly in comparison with conventional charge amplifier. The proposed circuit can be also implemented by using general purpose JFET operational amplifiers instead of using electrometer operational amplifiers therefore the cost of implementation will be reduced significantly in comparison with conventional charge amplifier. The proposed charge amplifier was assembled by using general purpose JFET Op-Amp to capture and amplify the output voltage of the piezoelectric vibration sensor Minisense100. In this experiment the low-cutoff frequency and the gain of the proposed charge amplifier were set equal to 0.2Hz and 20.5 dB respectively. The output offset voltage of the circuit was measured equal to 210 $\mu \text{V}$ . The measurement of very small vibration (±0.015g) showed a relative error equal to 2.1% with respect to the value which is obtained by using vibration meter as reference.
INTEREST RATES AND LOAN PERFORMANCE OF DEPOSIT MONEY BANKS IN NIGERIA

There has been much speculation about the seemingly high lending rates as evident of perceived inequity on the part of bankers by their customers in reaction to huge overhang of unpaid loans in the books of Deposit Money Banks (DMBs). Data for the study was collected from the financial statements of the three banks under study (UBA, FBN and GTB), as well as the CBN’s statistical database for macroeconomic variables analysed using Microsoft Excel’s regression function to perform a descriptive, correlation and regression analysis and examine the relationship between interest rates and loan repayment. This study established that there is a significant relationship between the interest rate and loan repayment, measured by credit quality using the non-performing loan ratio. This indicates that an increase in the interest rate will likely cause a corresponding increase or decrease in the credit quality. It further showed that any slight change in the lending rate would increase non-performing loan. KEY WORDS: Prime lending rate (PLR); Monetary Policy Rate (MPR); Non-performing Loan (NPL), and loan loss provision.
Effect of basicity on dephosphorization of hot metal with a low basicity slag at 1653 K

This research aims to investigate the influence of the slag basicity from 1.40 to 1.83 on dephosphorization of the hot metal with a CaO–FeO–SiO2–MgO–Al2O3 molten slag at the low temperature of 1653 K. The results indicated that the dephosphorization ratio was increased with the increase of basicity. Even at the low basicities of 1.73 and 1.83, the dephosphorization ratios can be as high as 77.3 and 80.7%, respectively. With the increase of basicity, the contents of P2O5 and total iron in the slag were increased, whereas the content of MnO was decreased. The distribution ratio of phosphorus was expressed as . The values calculated by the present method are well consistent with the measurement values. Besides, the dark grey phase B and the light grey phase D could be considered as the phosphorus-rich phases containing C2S solid particles.
Banking Efficiency Determinants in India: A Two-stage Analysis

This study aims at measuring the technical efficiency of banks in India and examining its determinants. Efficiency is said to be achieved if a bank is able to maximise its output subject to limited inputs. To obtain technical efficiency score, input-oriented Malmquist Data Envelopment Analysis is applied on two outputs and three input variables, based on a VRS (variable returns to scale) assumption. Three foreign banks—namely, A B Bank Ltd, Bank of Ceylon, and Citibank N A—and two Indian banks—namely, HDFC Bank and State Bank of India—are found to be most efficient during the study period. The efficiency scores when subsequently used as the dependent variable along with independent variables—bank size, capitalisation, liquidity risk, returns on assets, interest rate, credit risk, market concentration and gross domestic product (GDP)—in a panel regression analysis found the fixed effect model to be more appropriate in explaining the determinants. The results reveal that liquidity risk, returns on assets, credit risk, market concentration and GDP have a significant effect on the technical efficiency, while banks size, interest rate and level of capitalisation are found to be insignificant variables. JEL Classification: G21, C13, C60
Transcriptional addiction in mixed lineage leukemia: new avenues for target therapies

Abstract Mixed lineage leukemia (MLL) is an aggressive and refractory blood cancer that predominantly occurs in pediatric patients and is often associated with poor prognosis and dismal outcomes. Thus far, no effective target therapy for the treatment of MLL leukemia is available. MLL leukemia is caused by the rearrangement of MLL genes at 11q23, which generates various MLL chimeric proteins that promote leukemogenesis through transcriptional misregulation of MLL target genes. Biochemical studies on MLL chimeras have identified that the most common partners exist in the superelongation complex (SEC) and DOT1L complex, which activate or sustain MLL target gene expression through processive transcription elongation. The results of these studies indicate a transcription-related mechanism for MLL leukemogenesis and maintenance. In this study, we first review the history of MLL leukemia and its related clinical features. Then, we discuss the biological functions of MLL and MLL chimeras, significant cooperating events, and transcriptional addiction mechanisms in MLL leukemia with an emphasis on potential and rational therapy development. Collectively, we believe that targeting the transcriptional addiction mediated by SEC and the DOT1L complex will provide new avenues for target therapies in MLL leukemia and serve as a novel paradigm for targeting transcriptional addiction in other cancers.
MOCCAA - MObile Cloud Computing AdaptAble

The primary objective of Mobile Cloud Computing (MCC) is the support of resourceconstrained mobile devices by means of Cloud or nearby computing resources. In general, this is achieved by outsourcing or offloading computational intensive tasks of mobile applications. This allows, for instance, to virtually extend the processing power of mobile devices and, indirectly, to save battery life. In case remote resources are not available or the communication link is broken, still a local execution is possible. The challenges and issues that arise in such a scenario are manifold. The essential ones, which are also addressed in this thesis, can be summarized with the following four questions. Which part of a mobile application should be offloaded to the Cloud to accelerate, for example, its execution or to relieve the mobile device with respect to the battery consumption? Therefore, those parts of an application have to be identified that have a high resource need, but whose offloading would only lead to a small communication overhead. The decision where to run which part of the application has to take into account the current latencies to the remote resources and the dynamics of their availability and usage. This requires a Resource Management System that is able to discover matching remote resources fast and efficiently without delaying the offloading procedure too much. Subsequently, we have to determine when or under which conditions which parts shall be offloaded. This decision-making requires a monitoring on client side and a prediction about the future resource consumption of the given application parts. The final question addresses the procedure of offloading itself and the applied communication protocol. It can be summarized with how to offload. In the last few years, several approaches for MCC have been developed and examined in the research community. Most of them deal with one or two of the aforementioned aspects, but do not consider the positive and negative effects for the other dimensions. The key point of this thesis is that a comprehensive solution for MCC must handle all core questions listed above in an integrated fashion. With our framework MOCCAA we did not only strive for just another partitioning and offloading technique that is additionally equipped with a standard Resource Management System and further modules. Instead, the single modules of MOCCAA shall cooperate and interact with each other in such a way that all dimensions can benefit and are improved a little bit further.