Miracle-dz/UniFAR-FTUs huggingface dataset:
Stimuli-responsive platinum and ruthenium complexes for lung cancer therapy

Lung cancer is the most common cause of cancer-related deaths worldwide. More efficient treatments are desperately needed. For decades, the success of platinum-based anticancer drugs has promoted the exploration of metal-based agents. Four ruthenium-based complexes have also entered clinical trials as candidates of anticancer metallodrugs. However, systemic toxicity, severe side effects and drug-resistance impeded their applications and efficacy. Stimuli-responsiveness of Pt- and Ru-based complexes provide a great chance to weaken the side effects and strengthen the clinical efficacy in drug design. This review provides an overview on the stimuli-responsive Pt- and Ru-based metallic anticancer drugs for lung cancer. They are categorized as endo-stimuli-responsive, exo-stimuli-responsive, and dual-stimuli-responsive prodrugs based on the nature of stimuli. We describe various representative examples of structure, response mechanism, and potential medical applications in lung cancer. In the end, we discuss the future opportunities and challenges in this field.
ANALISA PENGARUH WORK-FAMILY CONFLICT TERHADAP TINGKAT STRES KERJA DAN KINERJA KARYAWAN WANITA DI HOTEL BINTANG 4 DAN 5 DI SURABAYA

Abstrak - Penelitian ini dilakukan untuk mengetahui apakah work family conflict berpengaruh terhadap stres kerja dan kinerja karyawan wanita yang bekerja di hotel bintang 4 dan 5 di Surabaya. Penulis memilih hotel bintang 4 dan 5 karena karyawan memiliki beban kerja yang relatif sama. Penelitian ini merupakan penelitian kuantitatif. Teknik analisa yang diunakan dalam penelitian ini adalah partial least square (PLS). hasil dari penelitian ini menyebutkan bahwa work family conflict mempunyai pengaruh positif signifikan terhadap stress kerja sedangkan work family conflict memiliki pengaruh negatif signifikan terhadap kinerja karyawan dan stress kerja berpengaruh negatif signifikan terhadap kinerja. Sehingga dapat disimpulkan bahwa work family conflict yang tinngi akan mempengaruhi stres kerja dan kinerja karyawan, dan stres kerja mempengaruhi kinerja karyawan wanita di hotel bintang 4 dan 5 di Surabaya. Kata Kunci: Work Family Conflict , Stres Kerja, Kinerja Karyawan Abstrak - The aim of this research is to analyzed the influence of work family conflict on work stress and job performance woman employee at 4 and 5 star hotel in Surabaya. Researcher choose 4 and 5 star hotel as a object because the employee has the same work load. This thesis is a conclusive research. The statistical analysis technique used is Partial Least Square (PLS). The result showed that work family conflict has an influence on job stress is positive significant. Moreover work family conflict has an influence on job performance was negative significant and Job stress has an influence on job performance was negative significant. However, work family conflict has an influence to job stress and job performance and also job stress has an influence to job performance woman employee at 4 and 5 star hotel in Surabaya. Keywords: Work Family Conflict, Work Stress, Job Perfomance
A Book Recommendation System for Cloud Computing: A Survey

Data mining is the approach to extract knowledge from raw data facts. Cloud computing is the emerging technique used to share resources and information among nodes. Recommender systems have made significant utility in daily routing life. Online shopping and Social networking sites are playing crucial role in routine life. Over 3.5 billion people uses internet for various purpose. Online shopping retail sales are predicted to grow steadily in upcoming years. Book recommendation is one of the major requirements of e-commerce portals for ease of reading and referencing purpose. This feature can help to increase shopping value with minimum shopping time. Logical recommendation not only helps to customer for purchasing but also increases total sales value. This research paper has attempted to explore the importance of book recommendation and existing solutions. It also investigates the existing solutions and scope of improvement to enhance the performance.
Estimage: A mobile application in agriculture for image to object count estimation

A major problem in the agricultural field is accurately estimating the yield of produce. Typically, farmers must wait to measure their crops after harvest using manual mechanical equipment. There is value in having better methods of yield estimation based on data that can be captured with inexpensive technology in the field, such as a smartphone. We develop a smartphone application for the Android platform with access to a cloud-based machine learning (ML) service that can estimate the amount of crop on a bush or tree from an image. The development of an image-to-object-count estimation system called Estimage is presented. The Estimage system consists of an Android client application for user interaction, a PHP server application for request handling, an Octave program for image normalization, and an open-source ML software package called ilastik that applies a predictive model to an image. The functionality of the mobile client application is tested and the system satisfies all of the functional requirements and most of the non-functional requirements. The system is tested on the images of coins on a table, logs stacked in a pile, and blueberries on the bush. We show that the system is capable of accurately estimating the count of objects in the images that have objects of the same (size, colour, and shape) as that used to train the model. The system is good at distinguishing object pixels from the image background pixels provided the background is consistent with that used to train the model.
CFD Simulation On The Pressure Distribution For An Isolated Single-Story House With Extension: Grid Sensitivity Analysis

Damage due to wind-related disasters is increasing due to global climate change. Many studies have been conducted to study the wind effect surrounding low-rise building using wind tunnel tests or numerical simulations. The use of numerical simulation is relatively cheap but requires very good command in handling the software, acquiring the correct input parameters and obtaining the optimum grid or mesh. However, before a study can be conducted, a grid sensitivity test must be conducted to get a suitable cell number for the final to ensure an accurate result with lesser computing time. This study demonstrates the numerical procedures for conducting a grid sensitivity analysis using five models with different grid schemes. The pressure coefficients (CP) were observed along the wall and roof profile and compared between the models. The results showed that medium grid scheme can be used and able to produce high accuracy results compared to finer grid scheme as the difference in terms of the CP values was found to be insignificant.
Global urbanization and food production in direct competition for land: Leverage places to mitigate impacts on SDG2 and on the Earth System

Global urbanization and food production are in direct competition for land. This paper carries out a critical review of how displacing crop production from urban and peri-urban land to other areas – because of issues related to soil quality – will demand a substantially larger proportion of the Earth’s terrestrial land surface than the surface area lost to urban encroachment. Such relationships may trigger further distancing effects and unfair social-ecological teleconnections. It risks also setting in motion amplifying effects within the Earth System. In combination, such multiple stressors set the scene for food riots in cities of the Global South. Our review identifies viable leverage points on which to act in order to navigate urban expansion away from fertile croplands. We first elaborate on the political complexities in declaring urban and peri-urban lands with fertile soils as one global commons. We find that the combination of an advisory global policy aligned with regional policies enabling robust common properties rights for bottom-up actors and movements in urban and peri-urban agriculture (UPA) as multi-level leverage places to intervene. To substantiate the ability of aligning global advisory policy with regional planning, we review both past and contemporary examples where empowering local social-ecological UPA practices and circular economies have had a stimulating effect on urban resilience and helped preserve, restore, and maintain urban lands with healthy soils.
Predicting Deterioration of Patients in the Intensive Care Unit

University of Tampere Faculty of Natural Sciences Master Degree Programme in Computational Big Data Analytics HATEM BOUABANA: Predicting Deterioration of Patients in the Intensive Care Unit. M.Sc. Thesis, 64 pages April 2018 The massive influx of data in healthcare encouraged the building of data-driven machine learning models in order to improve medical diagnosis and assess patients health status. Thus, gaining knowledge and actionable insights from this complex, heterogeneous, poorly annotated and generally unstructured data remains a key challenge in transforming healthcare. In this thesis, we focus on consecutive events in patients Electronic Health Records (EHR) data to predict organ failure in the ICU. We first investigate the ability of both logistic regression and random forest classifiers to achieve this task. Then, we compare these methods along with convolutional neural networks (CNN) for prediction of multiple organ failures: cardiovascular and pulmonary. Our predictions are done using a restricted set of parameters to enable “real-time” usage in the ICU. Predictions are made three hours in the future to support clinically actionable planning while having a 90 minutes window of parameters history. Our results suggest that the CNN has substantial additional predictive value for cardiovascular and pulmonary organ failures among critically ill patients.
Towards understanding antibiotic use and producer performance under the Canadian Quality Milk Program

TOWARDS UNDERSTANDING ANTIBIOTIC USE AND PRODUCER PERFORMANCE UNDER THE CANADIAN QUALITY MILK PROGRAM Mary Ellen Alexandrea Watters Advisor: University of Guelph, 2019 Dr. David F. Kelton Canadian dairy producers have taken a proactive approach to addressing food safety through the Canadian Quality Milk (CQM) program; now known as the Food Safety module of proAction. This thesis investigated the CQM program, antibiotic use, and CQM antibiotic record quality in Ontario. A survey was used to understand the experiences of CQM Advisors (n= 99) who administered a voluntary training program available to Ontario dairy producers prior to their first CQM audit. In general, Advisors reported a positive experience and felt training was beneficial to producers. The Ontario CQM database (n=4,001 herds) was analyzed to evaluate producer performance at first and second audit. Participation in the voluntary training program was high; 88.9% of Ontario dairy producers participated. Success at first validation visit was also high (79.6%). Training was associated with greater odds of producer success at first validation visit. There appeared to be a cohort effect based on audit year as well as variability due to auditor variation. This indicates a need for future research to understand these impacts. A cross-sectional approach was used to survey Ontario producers’ (n= 101)
The Effect of Medicaid Expansion on Healthcare Coverage, Labor Market Activity, and Government Assistance Among Those with Disabilities

In 2010, The Affordable Care Act (ACA) was passed in the United States (U.S.). The ACA overhauled the U.S. healthcare system and expanded Medicaid coverage to those with income below 138% of the federal poverty line. However, in 2012 the Supreme Court decided that Medicaid expansion should be voluntary. In 2014 24 states expanded Medicaid creating the opportunity for a natural experiment. This study exploits this natural experiment to evaluate the effect of Medicaid expansion on labor market activity, health insurance coverage, and public assistance receipt among those with disabilities. By employing a difference-in-difference regression model and using the repeated cross-sectional nature of data collected through the American Community Survey, I found that Medicaid expansion has no independent significant effects on labor market activity but is associated with increased health insurance coverage and decreased public assistance for those with disabilities.
ANÁLISE RELACIONAL ENTRE O DESEMPENHO AMBIENTAL, SOCIAL E ECONÔMICO: ESTUDO DAS CORPORAÇÕES COM SELO ISE DA BM&FBOVESPA

Este estudo objetiva analisar a relação entre os investimentos ambientais, sociais e econômicos das corporações cadastradas no Índice de Sustentabilidade Empresarial (ISE) da BMFBovespa de 2016. A metodologia é quantitativa, descritiva e o procedimento técnico é a pesquisa documental. A análise dos dados ocorreu mediante testes estatísticos, sendo a correlação de Pearson, Teste t de student, Teste de Levene e pelo coeficiente de variação. Os resultados apontam que o desempenho ambiental mais eficiente é das corporações dos setores de combustível, alimentício e de extração de recursos naturais; ao analisar a dimensão social, destacam-se os setores de transportes e de energia elétrica; e, na dimensão econômica, destacam-se as organizações dos serviços financeiros. A análise de variância com base no Teste Levene F (1,296) = 0,263 e t de Student (0,246) = 0,807 revelam um p 0,05, neste sentido, sugerem que não há diferença entre a média do desempenho ambiental e social. Além disso, o teste Pearson revela que não há correlações significativas do desempenho ambiental e social em relação ao desempenho econômico. Conclui-se que a geração de lucro ou prejuízo das corporações da carteira ISE da BMFBovespa de 2016 não influencia no montante de investimento realizado no âmbito ambiental e social.Palavras-Chave: Índice de Sustentabilidade Empresarial. Correlação de Pearson. Teste t de Student. RELATIONAL ANALYSIS BETWEEN ENVIRONMENTAL, SOCIAL AND ECONOMIC PERFORMANCE: STUDY OF CORPORATIONS WITH ISE OF BM FBOVESPAAbstract: This study aims to analyze the relationship between environmental, social and economic investments of corporations registered in the BMFBovespa Corporate Sustainability Index (CSI) of 2016. The methodology is quantitative, descriptive and the technical procedure is documentary research. Data analysis was performed using statistical tests, Pearson correlation, Student t test, Levene test and coefficient of variation. The results indicate that the most efficient environmental performance is of the corporations of the fuel, food and natural resources extraction sectors; when analyzing the social dimension, the sectors of transport and electric energy stand out; and, in the economic dimension, the financial services organizations stand out. The analysis of variance based on the Levene F test (1.296) = 0.263 and Student t (0.246) = 0.807 revealed a p 0.05, in this sense, suggest that there is no difference between the average environmental and social performance. In addition, the Pearson test reveals that there are no significant correlations of environmental and social performance in relation to economic performance. It´s concluded that the generation of profit or loss of the corporations of the BMFBovespa CSI portfolio of 2016 does not influence the amount of investment made in the environmental and social scope.Keywords: Corporate Sustainability Index. Pearson correlation. Test t of Student.
Important Elements for Inflation Targeting for Emerging Economies

This is the fifth chapter of a forthcoming monograph entitled "On Implementing Full-Fledged Inflation-Targeting Regimes: Saying What You Do and Doing What You Say. " It examines whether certain conditions have to be met before emerging economies can adopt an inflation-targeting regime and provides some empirical evidence on the matter. The issues analyzed are the priority of inflation targeting over other goals, the absence of fiscal dominance, central bank independence, the degree of control over the policy interest rate, a sound methodology for forecasting, and the soundness of financial institutions and markets, and resilience to changes in exchange rates and interest rates.
Property Rights, Place-Based Policies, and Economic Development

This paper examines the effect of property rights on economic development within local labor markets, including how property rights change the equilibrium response to place-based policies. It does so in the context of federally recognized American Indian reservations, where a fraction of the land is held in trust by the US federal government and associated with restrictions on transactions. I find that incomplete property rights on reservations are responsible for lower wages and higher levels of unemployment. The direction of these findings is robust to an instrumental variables approach to dealing with the endogeneity of property rights. Next I shed light on the extent to which place-based policies can improve economic outcomes on reservations. I use a spatial equilibrium framework to study the incidence of casino adoption, a place-based policy unique to reservations. The key insight from the model is that incomplete property rights impose frictions in the housing market that lower the migration response to casino adoption, improving the likelihood that the local population benefits. Consistent with the model's predictions, I find that casino adoption raises average wages and that the wage effect is greater on reservations with more land in trust. My estimates suggest that wage increases correspond to welfare improvements. This paper provides insights into how place-based policies and property rights jointly shape economic outcomes through changes in the labor market, the housing market, and the mobility of workers.
A Unified Approach to Collaborative Filtering via Linear Models and Beyond

Recommending a personalised list of items to users is a core task for many online services such as Amazon, Netflix, and Youtube. Recommender systems are the algorithms that facilitate such personalised recommendation. Collaborative filtering (CF), the most popular class of recommendation algorithm, exploits the wisdom of the crowd by predicting users’ preferences not only from her past actions but also from the preferences of other like-minded users. In general, it is desirable to have a CF framework that is (1) applicable to wide range of recommendation scenarios, (2) learning-based, (3) amenable to convex optimisation, and (4) scalable. However, all existing CF methods, such as neighbourhood and matrix factorisation, lack one or more of these desiderata. In this dissertation, we investigate linear models, an under-appreciated but promising area for recommendations that addresses all the above desiderata. We formulate a unified framework based on linear models that yields CF algorithms for four prevalent scenarios. First, we investigate Social CF, which involves leveraging users’ signals from online social networks. We propose social affinity filtering (SAF), that exploits fine-grained user interactions and activities in a social network. Second, we investigate Cold-Start CF, which refers to the scenario when we do not have any historical data about a user or an item. We formulate a large-scale linear model that leverages users social information. Third, we investigate One-Class CF, which concerns suggesting relevant items to users from the data that consists of only positive preferences such as item purchase.Noting the superior performance of linear models, we propose LRec, a user-focused linear CF model, and extend it to large-scale datasets via dimensionality reduction. Finally, we investigate Explicit Feedback CF, which concerns predicting user’s actual preferences such as rating, or like/dislikes. We identify CF as an auto-encoding problem and propose AUTOREC, a generalized neural network architecture for CF. We demonstrate state-of-the-art performance of the proposed models through extensive experimentation on real world datasets. In a nutshell, this dissertation elucidates the power of linear models for various CF tasks and paves the way for further research on applying deep learning models to CF.
A convex model approach for structure non-probabilistic reliability analysis

In this article, a novel approach, that is, convex model method of set theory, is proposed to investigate the non-probabilistic reliability of bridge crane. Considering the metal structure system of the bridge crane, the finite element method is applied to obtain the stress response of the structure dangerous point. Then, the sample of stress response of the structure danger point and uncertain parameters are obtained. Finally, based on support vector machines, the structure implicit regression function of the system is replaced by explicit expression that calculates the non-probabilistic reliability of the structure. Results show that this approach is useful and efficient to solve the problem of non-probabilistic reliability in the metal structure.
Influence of Military Commander’s Leadership Style towards Subordinate’s Morale

Leadership is regarded as one of the strategic matters in the development and management of morale. In military, leader control both interpersonal and material rewards and punishment that often shape subordinate’s behaviour and influence subordinate’s performance, morale, motivation and attitude. The objective of the study was to empirically investigate the direct effect of Military Commander’s transformational and transactional leadership styles towards their subordinate’s morale. This study seeks to determine whether the two different leadership styles have direct effects on the subordinate’s morale. This study employed quantitative methods for data collection. The respondents of this study are infantry soldiers from Border Regiment consisting of officers and other ranks. The research instruments consisted of structured questionnaires using MLQ (Multifactor Leadership Questionnaire) developed by Bass and Avolio (2004), along with items of morale. The result of this study is expected to provide insight into the importance of the application of concepts of morale for subordinates, transformational and transactional leadership styles that exist within a unit.
An interactive ocean surface albedo scheme: formulation and evaluation intwo atmospheric models

Ocean surface represents roughly 70 % of the Earth surface, playing a large role in the partitioning of the energy flow within the climate system. The ocean surface albedo (OSA) is an important parameter in this partitioning because it governs the amount of energy penetrating into the ocean or reflected towards space. The old OSA schemes in the ARPEGE and LMDZ models only resolve the latitudinal dependence in an ad hoc way without an accurate representation of the solar zenith angle dependence. Here, we propose a new interactive OSA scheme suited for Earth system models, which gather contributions for relevant OSA processes published in the literature over the last decades. This scheme resolves spectrally the various contributions of the surface for direct and diffuse solar radiation. The implementation of this scheme in two Earth system models leads to substantial improvements in simulated OSA. At the local scale, models using the interactive OSA scheme better replicate the day-to-day distribution of OSA derived from ground-based observations in contrast to old schemes. At global scale, the improved representation of OSA for diffuse radiation reduces model biases by up to 80 % over the tropical oceans, reducing annual-mean model-data error in surface upwelling shortwave radiation by up to 7 W m −2 over this domain. The spatial correlation coefficient between modelled and observed OSA at monthly resolution has been increased from 0.1 to 0.8. Despite its complexity, this interactive OSA scheme is computationally efficient to enable precise OSA calculation without penalizing the model elapsed time.