Miracle-dz/UniFAR-FTUs huggingface dataset:
The Sense of Style: The Thinking Person's Guide to Writing in the 21st Century

Steven Pinker, the bestselling author of The Language Instinct, deploys his gift for explaining big ideas in The Sense of Style - an entertaining writing guide for the 21st century. What is the secret of good prose? Does writing well even matter in an age of instant communication? Should we care? In this funny, thoughtful book about the modern art of writing, Steven Pinker shows us why we all need a sense of style. More than ever before, the currency of our social and cultural lives is the written word, from Twitter and texting to blogs, e-readers and old-fashioned books. But most style guides fail to prepare people for the challenges of writing in the 21st century, portraying it as a minefield of grievous errors rather than a form of pleasurable mastery. They fail to deal with an inescapable fact about language: it changes over time, adapted by millions of writers and speakers to their needs. Confusing changes in the world with moral decline, every generation believes the kids today are degrading society and taking language with it. A guide for the new millennium, writes Steven Pinker, has to be different. Drawing on the latest research in linguistics and cognitive science, Steven Pinker replaces the recycled dogma of previous style guides with reason and evidence. This thinking person's guide to good writing shows why style still matters: in communicating effectively, in enhancing the spread of ideas, in earning a reader's trust and, not least, in adding beauty to the world. Eye-opening, mind-expanding and cheerful, The Sense of Style shows that good style is part of what it means to be human. An award-winning cognitive scientist, Steven Pinker is also Chair of the Usage Panel of the American Heritage Dictionary and the lauded author of bestsellers such as The Language Instinct, Words and Rules, The Better Angels of Our Nature and The Stuff of Thought. He is Johnstone Family Professor in the Department of Psychology at Harvard and lives in Boston & Truro, MA.
The Future of Sludge and Biosolids Research

A bout two months ago, I was searching for a reviewer for a manuscript focused on sludge management. To find an appropriate reviewer, I used the Association of Environmental Engineering and Science Professors Membership Directory for faculty listed under the category, Sludge Handing and Disposal. I found that the number of faculty listed under this category is not only one of the smaller ones, but many of the listed faculty are now retired. By this measure, the actual number of active faculty who list sludge management as one of their principal research areas is quite small, less than Nanotechnology and Geological Sciences. This lack of interest by environmental engineering faculty is not reflected by engineering firms and utilities. Sludge management remains a problem for utilities and is also one of the most costly aspects of wastewater treatment. Further, sludge biosolids disposal is one of the areas of wastewater treatment that raises public concern. From the consultant’s standpoint, there is a large demand for engineers knowledgeable in sludge and biosolids handling and disposal. The interest in biosolids is also reflected by the large attendance at the annual WEF Residuals and Biosolids Conferences. In fact, the Residuals and Biosolids Conferences are the best attended of any of the WEF specialty conferences. Nevertheless, few academics attend this conference. The decline in academic interest comes at a time when new innovative technologies to deal with sludge management are being proposed and implemented and where concerns about the contaminants in sludges are increasing among managers, legislators, and the public. Some of the important research topics and issues that I see are the following:
Etude de la conversion de spin nucléaire du méthane en matrices d'Argon et de Krypton

Les molecules possedant des atomes identiques en positions interchangeables existent sous differentes formes appelees " configurations de spin nucleaire " identifiees par la symetrie de la fonction d'onde rovibrationnelle et la valeur de leur spin nucleaire total. Dans le cas des molecules hydrogenees presentes dans les milieux interstellaires et cometaires, la mesure des rapports entre populations de configuration de spin differentes montre que ces dernieres ne sont pas a l'equilibre thermodynamique attendu dans les conditions de temperature du milieu. L'origine de ce desequilibre reste en debat, et des etudes plus poussees concernant la conversion de spin nucleaire (CSN) dans la phase solide et a l'interface avec la phase gazeuse a basse temperature sont necessaires pour mieux comprendre les observations. Ce travail de these experimental est dedie a l'etude de la CSN du CH4 dans des matrices d'argon et de krypton. La molecule de methane presente trois configurations de spin qui peuvent etre distinguees par spectroscopie d'absorption infrarouge a transformee de Fourier. Dans un premier temps, le travail a consiste en l'etude de la spectroscopie du methane dans ces matrices (attributions, influence de l'environnement cristallin.). Dans un deuxieme temps, nous avons etudie la dynamique de CSN par retour a l'equilibre de matrices prealablement enrichies en une espece de spin donnee. L'influence de (i) la nature, (ii) la concentration en CH4 et (iii) la temperature (4.2 K - 10 K) des matrices sur les temps de conversion mesures ont permis de mettre en evidence les differents mecanismes (inter et intramoleculaires) responsables de la modification des especes de spin nucleaire de CH4. Ces travaux suggerent que, pour des glaces astrophysiques, l'equilibre des populations relatives entre les configurations de spin devrait etre obtenu en phase solide, ce qui remet en cause l'hypothese de la conservation des rapports otho/para dans les glaces cometaires et interstellaires.
Modified Norris-Landzberg Model for Reliability of Pb-free BGA Components

One important task for reliability engineers in new product design phase is to evaluate the long-term reliability of Pb-free solder joints under the service environment conditions. It is a common practice, due to the practical restrictions such as cost and aggressive development cycle time, to map the results under accelerated testing conditions to field conditions via well-benchmarked transform models. One of the most widely adopted models is the modified version based on Norris-Landzberg (NL) Acceleration Factor (AF) model [1]. The popular NL AF model simultaneously makes it easy to apply but difficult to correlate with data from different sources. In fact, there is ongoing discussion that questions the validity of the model [2]. To overcome the shortcomings of the model, Salmela [3] has suggested a correction term to consider package type and solder material along with the temperature and the dwell time on the solder joint. Chuang, et al. [4] have compared several models and confirmed that the prediction based on Salmela’s model is closer to their testing results. Ahmad, et al. [5] have proposed the constants of NL AF model as functions of the characteristic life under the accelerated testing conditions. All of those aforementioned variations of NL AF models, while improving the model prediction, would still need different constants for data under different situations; therefore, it is not convenient to use especially in product design phase where some critical information such as the package detail and testing results may not be available.In this paper, a unified NL AF model has been proposed by introducing an add-in impact function to factor package-related contributors such as package size, die size, joint pitch, and delta CTE. It is demonstrated that such an impact function enables NL AF model to correlate very well with a wide range of experimental data using one unified set of constants that were derived by nonlinear fitting of 112 data points from internal source and public domain publications. The robustness of the derived constants was then validated using the generic algorithm to ensure the best of the goodness-of-fit while minimizing the standard residual error. The resulting model has $\mathrm{R}^{2}$ equals 0.845 which showed a good correlation with the testing results. Furthermore, the derived model has been benchmarked with the testing results of iNEMI Pb-free solder alloy alternative project ([6]–[9]), an in-depth industry wide collaboration. The testing results are representable as two types of components with different solder alloys have been tested under multiple temperature cycling profiles. The benchmarking demonstrates a really good correlation as the majority of the predicted life, from the derived model, fall into + /-50% band compared with the testing results. Hence the proposed NL AF model, with a unified constant set, can be very helpful and handy in product design phase for reliability assessment.
Agent Assignment for Process Management: Competency-Driven Dynamic Resource Management Methodology

Convergence of data mining and process management is ideal -- but still limited. An example of such a convergence is presented in the form of Competency-driven Dynamic Resource Management (CDRM) Methodology that addresses the lack of agent-assignment-strategy in Workflow Management Systems (WfMS). Currently, WfMSs do not have any strategy to allocate resources (employees, agents) to their business processes on the basis their history of success of business process performance. Traditionally, WfMS uses role concept to allocate resources to their business processes -- one cause of poor business process performance since all eligible agents may be assigned to a task instead of only assigning those which are expected to be "successful". To solve this problem, the CDRM Methodology applies data mining techniques using their work history as a data source and process model as a source of domain knowledge to first perform analytical analysis of employees' performance. It then updates its findings into an organizational database -- a data source wherefrom WfMS make assignments. Thus, through this convergence, the CDRM Methodology enables WfMS to allocate only successful agents -- instead of merely role based static list of all eligible agents causing poor performance.
Urbanisation and incidence of psychosis and depression

Background Previous studies of differences in mental health between urban and rural populations are inconsistent. Aims To examine whether a high level of urbanisation is associated with increased incidence rates of psychosis and depression, after adjustment for age, marital status, education and immigrant status. Method Follow-up study of the total Swedish population aged 25–64 years with respect to first hospital admission for psychosis or depression. Level of urbanisation was defined by population density and divided into quintiles. Results With increasing levels of urbanisation the incidence rates of psychosis and depression rose. In the full models, those living in the most densely populated areas (quintile 5) had 68–77% more risk of developing psychosis and 12–20% more risk of developing depression than the reference group (quintile 1). Conclusions A high level of urbanisation is associated with increased risk of psychosis and depression for both women and men.
Data Mining: A Tutorial Based Primer

(Each Chapter concludes with a Chapter Summary, Key Terms, and Exercises.) Preface. I. DATA MINING FUNDAMENTALS. 1. Data Mining: A First View. Data Mining: A Definition. What Can Computers Learn? Is Data Mining Appropriate for my Problem? Expert Systems or Data Mining? A Simple Data Mining Process Model. Why not Simple Search? Data Mining Applications. 2. Data Mining: A Closer Look. Data Mining Strategies. Supervised Data Mining Techniques. Association Rules. Clustering Techniques. Evaluating Performance. 3. Basic Data Mining Techniques. Decision Trees. Generating Association Rules. The K-Means Algorithm. Genetic Learning. Choosing a Data Mining Technique. 4. An Excel-Based Data Mining Tool. The iData Analyzer. ESX: A Multipurpose Tool for Data Mining. iDAV Format for Data Mining. A Five-Step Approach for Unsupervised Clustering. A Six-Step Approach for Supervised Learning. Techniques for Generating Rules. Instance Typicality. Special Considerations and Features. II. TOOLS FOR KNOWLEDGE DISCOVERY. 5. Knowledge Discovery in Databases. A KDD Process Model. Step 1: Goal Identification. Step 2: Creating a Target Data Set. Step 3: Data Preprocessing. Step 4: Data Transformation. Step 5: Data Mining. Step 6: Interpretation and Evaluation. Step 7: Taking Action. The CRISP-DM Process Model. Experimenting with ESX. 6. The Data Warehouse. Operational Databases. Data Warehouse Design. On-line Analytical Processing (OLAP). Excel Pivot Tables for Data Analysis. 7. Formal Evaluation Techniques. What Should be Evaluated? Tools for Evaluation. Computing Test Set Confidence Intervals. Comparing Supervised Learner Models. Attribute Evaluation. Unsupervised Evaluation Techniques. Evaluating Supervised Models with Numeric Output. III. ADVANCED DATA MINING TECHNIQUES. 8. Neural Networks. Feed-Forward Neural Networks. Neural Network Training: A Conceptual View. Neural Network Explanation. General Considerations. Neural Network Learning: A Detailed View. 9. Building Neural Networks with iDA. A Four-Step Approach for Backpropagation Learning. A Four-Step Approach for Neural Network Clustering. ESX for Neural Network Cluster Analysis. 10. Statistical Techniques. Linear Regression Analysis. Logistic Regression. Bayes Classifier. Clustering Algorithms. Heuristics or Statistics? 11. Specialized Techniques. Time-Series Analysis. Mining the Web. Mining Textual Data. Improving Performance. IV. INTELLIGENT SYSTEMS. 12. Rule-Based Systems. Exploring Artificial Intelligence. Problem Solving as a State Space Search. Expert Systems. Structuring a Rule-Based System. 13. Managing Uncertainty in Rule-Based Systems. Uncertainty: Sources and Solutions. Fuzzy Rule-Based Systems. A Probability-Based Approach to Uncertainty. 14. Intelligent Agents. Characteristics of Intelligent Agents. Types of Agents. Integrating Data Mining, Expert Systems, and Intelligent Agents. Appendix. Appendix A: Software Installation. Appendix B: Datasets for Data Mining. Appendix C: Decision Tree Attribute Selection. Appendix D: Statistics for Performance Evaluation. Appendix E: Excel 97 Pivot Tables. Bibliography.
EVENT TIMES IN APPLICATION TO A SUICIDE RISK 2 STUDY 3 By

The concept of integrating data from disparate sources to ac7 celerate scientific discovery has generated tremendous excitement in 8 many fields. The potential benefits from data integration, however, 9 may be compromised by the uncertainty due to incomplete/imperfect 10 record linkage. Motivated by a suicide risk study, we propose an ap11 proach for analyzing survival data with uncertain event times arising 12 from data integration. Specifically, in our problem deaths identified 13 from the hospital discharge records together with reported suicidal 14 deaths determined by the Office of Medical Examiner may still not 15 include all the death events of patients, and the missing deaths can 16 be recovered from a complete database of death records. Since the 17 hospital discharge data can only be linked to the death record data 18 by matching basic patient characteristics, a patient with a censored 19 death time from the first dataset could be linked to multiple po20 tential event records in the second dataset. We develop an integra21 tive Cox proportional hazards regression, in which the uncertainty in 22 the matched event times is modeled probabilistically. The estimation 23 procedure combines the ideas of profile likelihood and the expecta24 tion conditional maximization algorithm (ECM). Simulation studies 25 demonstrate that under realistic settings of imperfect data linkage, 26 the proposed method outperforms several competing approaches in27 cluding multiple imputation. A marginal screening analysis using the 28 proposed integrative Cox model is performed to identify risk fac29 tors associated with death following suicide-related hospitalization 30 in Connecticut. The identified diagnostics codes are consistent with 31 existing literature and provide several new insights on suicide risk 32 prediction and prevention. 33
Truncated WT1 protein isoform expression is increased in MCF-7 cells in a long-term estrogen depletion

Background The WT1 gene codes for a transcription factor that presents several protein isoforms with diverse biological properties, capable of positively and negatively regulating genes involved in proliferation, differentiation, and apoptosis. WT1 protein is overexpressed in more than 90% of breast cancer, however, its role during tumor progression is still unknown. Methodology In this work were analyzed the expression of WT1 isoforms (36-38 kDa and 52-54 kDa, and 17 AA (+/−) and KTS (+/−)) in breast cancer cells. On the other hand, with the purpose of mimicking the process of switch from a hormone-dependent to a hormone-independent neoplasm, an assay was performed using the MCF-7 cells cultured in long-term estrogen depletion (MCF-7 LTED cells) to determine the WT1 protein isoforms expression by western blot and RT-PCR, and Her2/neu and Estrogen receptor (ER) expression by quantitative RT-PCR assay. Growth kinetics and sensitivity to tamoxifen were performed in the MCF-7 LTED cells by trypan blue exclusion. Results The western blot shows the presence of the 52-54 kDa WT1 isoform in the ER (+) breast cancer cells, but not in the ER (−) cells. The 36-38 kDa WT1 isoform was detected in all the breast cancer cell lines analyzed. Using specific primers was found that 17 AA (+) / KTS (−) WT1 isoform was the most frequent in four breast cancer cell lines. During the sampling of the MCF-7 cells in estrogen depletion, an increase in the short-term of 52-54 kDa WT1 isoform was observed and this was kept until week 13, thereafter, its expression was absent; alternately, the 36-38 kDa WT1 isoform was observed from week 1 and it remained constant until week 27. MCF-7 LTED cells growth kinetic decreased 1.4 folds and were not sensitive to tamoxifen antiproliferative effect (p ≤ 0.05). Finally, were observed an increase of expression of ER and Her2/neu in the MCF-7 LTED cells. Conclusions The 36-38 kDa WT1 isoform expression occurs during the modifications of the hormonal environment, suggesting that it may be playing an important role in its adaptation and tumor progression.
Unconventional Monetary Policies, an Appraisal

The major Central Banks have cut their key rates sharply in recent months in response to the rapid slowdown in the economy. These conventional monetary policies have shown their limitations, however. In the first place, central banks have little room for manoeuvre: Target rates are now between 0 and 0.25% for the Fed, 1.25% for the ECB, and 0.5% for the Bank of England (BoE). Second, despite previous rate cuts, monetary and financial conditions have deteriorated further. Finally, the financial crisis has weakened channels for the transmission of conventional monetary policies.Consequently, the central banks have implemented unconventional monetary policies, in the first place in order to tackle the liquidity crisis in the interbank market, and then, when the limits to cutting key rates became clearer, with a view to improving overall financing conditions for the economy.The measures taken by the ECB have resulted in a 45% expansion of its balance sheet between September 2008 and January 2009. These measures have primarily sought to boost the liquidity of the interbank market, while the other central banks (the Fed, the BoE and the BoJ) have also sought to influence the price of certain financial assets (public or private) through their purchases.The measures taken by the other central banks have pushed down interest rates right across the yield curve, putting downward pressure on their currencies, especially vis-a-vis the euro, which could worsen deflationary pressures in the euro area. This is what happened, for example, after the Fed's announcement of its Treasury bonds purchase facility on Wednesday 18 March, when the euro gained nearly 5% against the dollar. This situation prompted the President of the ECB to announce that the Governing Council intended to decide on new non-standard measures at its meeting on 7 May. He also said that the main refinancing rate of 1.25% could be cut further if circumstances warranted.
Procedures for Office Analysis: a Critical Review

Because office automation has not fulfilled its promise of making work more productive andsatisfying, researchers have developed techniques for specifying better requirements for officeautomation and support. Four such office analysis techniques have been publicly proposed, differingin how much of the complete analysis-to-prescription cycle they cover, what aspects they analyze,and how they bound the "office. " Review of these analysis processes points to three key issues:1. Office analysis is weak on prescribing specific support/automationproducts;2. we do not know how to evaluate different analysis techniques; and3. we have not yet specified the criteria by which we would decide whichtechnique is good.In answer to these issues, we suggest that extensions of some promising schemes forprescribing specific products be explored; that techniques be compared using an efficient "transcriptexperiment" approach; and that the criteria for acceptability for an analysis method be that itsdescriptions be reliable and valid, and that its prescriptions be valuable to the workers in thereorganized, computer-supported office.
The Exact Rank of Sparse Random Graphs

Two landmark results in combinatorial random matrix theory, due to Koml\'os and Costello-Tao-Vu, show that discrete random matrices and symmetric discrete random matrices are typically nonsingular. In particular, in the language of graph theory, when $p$ is a fixed constant, the biadjacency matrix of a random Erd\H{o}s-R\'enyi bipartite graph $\mathbb{G}(n,n,p)$ and the adjacency matrix of an Erd\H{o}s-R\'enyi random graph $\mathbb{G}(n,p)$ are both nonsingular with high probability. However, very sparse random graphs (i.e., where $p$ is allowed to decay rapidly with $n$) are typically singular, due to the presence of"local"dependencies such as isolated vertices and pairs of degree-1 vertices with the same neighbour. In this paper we give a combinatorial description of the rank of a sparse random graph $\mathbb{G}(n,n,c/n)$ or $\mathbb{G}(n,c/n)$ in terms of such local dependencies, for all constants $c\ne e$ (and we present some evidence that the situation is very different for $c=e$). This gives an essentially complete answer to a question raised by Vu at the 2014 International Congress of Mathematicians. As applications of our main theorem and its proof, we also determine the asymptotic singularity probability of the 2-core of a sparse random graph, we show that the rank of a sparse random graph is extremely well-approximated by its matching number, and we deduce a central limit theorem for the rank of $\mathbb{G}(n,c/n)$.