Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Issues in the Design and Analysis of Sequentially Randomized Trials

Adaptive treatment strategies are comprehensive methods for treating chronic diseases according to patients' needs and responses. They are useful in the treatment of diseases such as cancer or AIDS, where the treatment is frequently modified to adapt to the patients' health status. In the first part of this dissertation, we consider two commonly used randomization designs in clinical trial, namely, up-front randomized trial and sequentially randomized trial used to compare treatment strategies. Up-front randomization is the classical method of randomization where patients are randomized at the beginning of the study to pre-specified strategies. On the other hand, in sequentially randomization trials patients are randomized sequentially to available treatment options over the duration of the therapy as they become eligible to receive them. We compare the efficiency of the traditional up-front randomized trials to that of sequentially randomized trials for comparing adaptive treatment strategies both analytically and numerically based on a continuous outcome. In the second part of the dissertation, we consider analyzing right-censored survival data from two-stage sequentially randomized trials. In such analysis, it is often of interest to use median residual lifetime as the summary parameter to assess the treatment effectiveness. However, estimation of the median residual lifetime from sequentially randomized trials is not as straightforward because of its sequential randomization structure. We propose methods for estimating strategy-specific median residual life function from a two-stage sequentially randomized trial. Two types of estimators are proposed by inverting the inverse-probability-weighted estimated survival function and by using inverse-probability-weighted estimating equation function. We provide methods for estimating variances of these estimators and compare them through a simulation study. Our simulation study shows that both methods produce approximately unbiased estimators in large samples. We demonstrate our methods by applying them to a sequentially randomized leukemia clinical trial data set. Diseases such as cancer, leukemia, depression, and AIDS are major causes of morbidity and mortality in the United States. Medical research in the recent times has focused on finding optimal treatment strategies to manage or eradicate these diseases to reduce individual and community burdens. Statistical methodologies proposed in this dissertation will help appropriately design and analyze trials to develop effective treatment strategies and thus will be of significant use for improving public health in the United States and around the world.
Understanding the “How” and “Why” Aspects of Racial-Ethnic Discrimination: A Multimethod Approach to Audit Studies

Researchers have used audit studies to provide causal evidence of racial discrimination for nearly 60 years. Although audits are an excellent methodological tool to investigate the “what,” “where,” and “when” aspects of racial-ethnic discrimination, audits are less appropriate, by themselves, to investigate the “how” and “why” aspects of racial-ethnic discrimination. In this article, I review why audit studies are necessary to study racial-ethnic discrimination, the evidence from audit studies, and their limitations. I then argue that scholars should adopt a multimethod approach to audit studies to move from documenting the existence of racial-ethnic discrimination to examining how and why racial-ethnic discrimination occurs. Adoption of this multimethod approach will result in a deeper understanding of racial-ethnic discrimination with the potential to shape both opinions and policy surrounding discrimination.
Machine Learning–Based Blending of Satellite and Reanalysis Precipitation Datasets: A Multiregional Tropical Complex Terrain Evaluation

This study evaluates a machine learning–based precipitation ensemble technique (MLPET) over three mountainous tropical regions. The technique, based on quantile regression forests, integrates global satellite precipitation datasets from CMORPH, PERSIANN, GSMaP (V6), and 3B42 (V7) and an atmospheric reanalysis precipitation product (EI_GPCC) with daily soil moisture, specific humidity, and terrain elevation datasets. The complex terrain study areas include the Peruvian and Colombian Andes in South America and the Blue Nile in East Africa. Evaluation is performed at a daily time scale and 0.25° spatial resolution based on 13 years (2000–12) of reference rainfall data derived from dense in situ rain gauge networks. The technique is evaluated using K-fold, separately in each region, and leave-one-region-out validation experiments. Comparison of MLPET with the individual satellite and reanalysis precipitation datasets used for the blending and the recent Multi-Source Weighted-Ensemble Precipitation (MSWEP) global precipitation product exhibited improved systematic and random error statistics for all regions. In addition, it is shown that observations are encapsulated well within the ensemble envelope generated by the blending technique.
Adhesion-force micro-scale study of desiccating granular material

Experiments on five-, four-, three-and two-wet-hydrophilic-grain clusters were performed to investigate evolution of adhesion of granular media during drying on the micro-scale. The experiments show that the adhesion-force of a cluster initially grows at most to three times the original value before decreasing to zero by the end of evaporation. The adhesion-force is composed of capillary pressure force acting over the liquid/solid contact surface area, and surface tension forces acting over the three-phase contact perimeter length. This is in contrast with most macro-scale phenomenological models, in which the only desaturation process variables affecting strength are suction and saturation. Both the contact surface area and contact perimeter length are reduced to zero upon complete liquid evaporation. The morphology of an evaporating water body evolves through slow flow controlled by evaporation rate, interrupted by various modes of fast air entry, which are non-equilibrium jumps of liquid/gas interfaces (Haines jumps). The instabilities involve large adhesion force discontinuities and substantial water mass reconfiguration with water flow in an extremely short time, which makes the process transient. The reconfigurations can reduce the original multi-grain water clusters to four-, three-and two-grain clusters by way of three different instability modes: of thin-sheet instability, or meniscus snap-through instability, depending on the sign of the Gauss curvature of the liquid surface, or finally, for two-grain bridges only, a liquid wire pinch-off. For larger meso-scale assemblies, however, the global adhesion-force evolution is little affected by the jumps. The air entries are potential sites for drying cracks. The (approximately) calculated capillary pressure for two-and three-grain clusters, in no cases is seen to reach high values, predicted from water retention curves.
ASYMPTOTIC ENUMERATION OF GRAPHS WITH GIVEN DEGREE SEQUENCE

We survey results on counting graphs with given degree sequence, focusing on asymptotic results, and mentioning some of the applications of these results. The main recent development is the proof of a conjecture that facilitates access to the degree sequence of a random graph via a model incorporating independent binomial random variables. The basic method used in the proof was to examine the changes in the counting function when the degrees are perturbed. We compare with several previous uses of this type of method.
Ask the audience...Using clickers to enhance introductory business statistics courses

Teaching introductory business statistics presents many challenges, including motivating students to engage in the learning process. This research presents a real-life application of incorporating radio-frequency clickers into the course delivery of introductory business statistics. These “clickers” are part of a student response system that allow students to answer questions and records their responses in real time during class meetings. Using clickers provides a fun and interactive way for faculty to get immediate feedback from students and gauge their level of understanding of class material. It permits the instructor to adjust the pace of the class according to students’ understanding. Clickers also allow students to gauge their own understanding of the material and provide an opportunity to respond to in-class questions anonymously. This paper discusses an application of using clickers in an introductory business statistics courses and an analysis of the results of a student survey on perceived clicker classroom usage, along with a discussion of the lessons learned.
EFFECT OF GUT PEPTIDES ON HYPOTHALAMIC mRNA CONCENTRATION AND DRY MATTER INTAKE IN RUMINANTS

The in vitro effect of metabolites and splanchnic hormones on ovine hypothalamic mRNA concentration for neuropeptides that regulate appetite is not known. Therefore, the objective of this study was to measure the in vitro effect of media containing metabolites (glucose, propionate) or hormones (insulin, cholecystokinin (CCK), glucagon-like peptide-1 (GLP-1), polypeptide YY (PYY)) on hypothalamic mRNA concentration for neuropeptide Y (NPY), agouti-related peptide (AgRP), and proopiomelanocortin (POMC). Hypothalamic tissue from market lambs was obtained at slaughter and immediately incubated in culture media for 2 h at 36o C. Treatments included a control Dulbecco's Modified Eagle Medium (DMEM) or DMEM with the following additions: glucose, propionate, insulin, GLP-1, PYY, CCK, or glucose plus insulin. Abundance of mRNA for NPY, AgRP, and POMC was measured using quantitative reverse transcriptase PCR. Fisher's protected LSD test was used to compare changes in relative mRNAconcentrations for the hypothalamus incubated in the control
Relationship Between Time Management Behavior Perceived Control of Time and Job Satisfaction A Study of Teachers in Higher Education Institutes in India

According To Popular Belief, Individuals Who Manages Their Time Well Are Subjected To Less Stress, More Efficiency Resulting In High Level Ofperformance And Satisfaction. This Paper Presents A Confirmatory Factor Analysis Of The Time Management Behaviour Scale Originally Developed Of Macan Et Al. (1990). With The Fast-Growing Rate Of Academicians In India, There Is A Growing Demands And Challenges Need To Understand The Concept Of Time Management Behaviour In Context Of Faculty Members. Three Underlying Dimensions Of Time Management (Setting Goals And Priorities, Preference For Organization And Mechanics Of Time Management) Are Confirmed In The Setting Of Faculty Members Of Higher Education Institutions In India. The Scale Was Empirically Tested In Indian Context To Establish Unidimensional, Reliable And Valid Scale Using Confirmatory Factor Analysis (CFA) And Structural Equation Modelling (SEM) With AMOS Version 20.0.
Understanding purchase intention of university students towards skin care products

The purpose of this paper is to examine the factors which will contribute to consumers’ purchase intention on skin care products. Four factors, namely, brand awareness, brand association, perceived quality and brand loyalty, were included in this study. ,In total, 150 sets of self-administered questionnaires were distributed to students in a local private university in Melaka. Convenience sampling was used and data collected were analysed using SmartPLS to perform the measurement model and structural model. ,Findings have showed that there are positive relationships between brand awareness, brand association, perceived quality and brand loyalty and consumers’ purchase intention towards skin care products. Furthermore, it is concluded that perceived quality is the most significant factor in influencing consumers’ purchase intention. ,Firms are able to benefit from this study by formulating their brand management tactics referring to the findings to have competitive advantage over their competitors.
Investigating the Impact of Applying Different Strategies of Formative Assessments on Students’ Learning Outcomes in Summative Assessments in a Private School in Sharjah, UAE

Among contemporary methods for improving the learning of students, formative assessments stand out amongst the most essential and powerful. While formative assessment thoughts and practices appear to have a demonstrated record in upgrading students’ ability to take in information, these practices are difficult to completely incorporate into teachers' everyday classroom practices. This study investigated the impact of applying different strategies of formative assessment practices on students’ learning outcomes in summative assessments in one of the private schools in Sharjah, UAE. This study consists of two groups of participants including twelve teachers and seventeen high school students in a private school in Sharjah, UAE. A qualitative method was taken towards gathering teachers’ and students’ perceptions of the formative assessment practices accompanied by open-ended questions through semi-structured interviews. Data analysis revealed that a significant effect is achieved through using a variety of formative assessment practices on students’ learning outcomes in the summative assessments. Most teachers and students are aware of the importance of using these strategies to improve the learning skills for each student. Therefore, formative assessments can be considered as a tool for improving the students’ academic level, adding to the procedure and results of learning.
A forensic study of unnatural deaths in Kuwait : epidemiological, virtual autopsy and DNA investigations

Forensic science is growing rapidly in the world today. During the past decade, medico-legal investigations have been highly expanded to include all areas of forensic science. The present study investigated three important aspects of forensic biology. First, this present project investigated, a total number of 5,703 reported medico-legal cases diagnosed as un-natural deaths by The Forensic Department in Kuwait, during the year 2003-2009. The results show that accidental, homicidal and suicidal deaths accounted for 86%, 8% and 6%, respectively. The results showed that most people who died of unnatural deaths were more predominant in the age group 20-29 years (third decade). Road Traffic Accidents accounted for 65% of accidental deaths, and 4% out of them were related to alcohol consumption. The results also illustrated that the highest rate of homicide in Kuwait was due to stab wound injuries (38%) compared to the lower rate of homicidal pattern for infanticides (3%). Similarly, the study showed that the most common method of suicide in Kuwait was death by hanging and this accounted for (60%). This study further demonstrated the effectiveness of virtual autopsy technique as a new tool in forensic investigations to determine various un-natural death causes. A total of thirty (30) male forensic cadavers were employed in this project. The cases were RTA (11), firearm injuries (10), drowning (4), head injuries (3) and lastly strangulation (2). All these cases were compared to the findings of traditional autopsy. The results show similar findings for virtopsy compared to traditional autopsy. This study clearly revealed that virtopsy could be an effective alternative in certain situation, being noninvasive and rapid. The present project also investigated 28 samples of human blood, saliva or semen. The experiments were done at four different temperatures (55°C, 37°C, 24°C and 4°C) and four different humidity ranges (41%, 55%, 58% and 61%), respectively. The results showed that, DNA quantity in blood, saliva and semen samples remained more or less the same at temperatures of 4°C, 24°C and 37°C compared to values for day one with all other days. In contrast, when the temperature was raised to 55 °C, the DNA started to degrade with time until it reached zero at day 12 for saliva and day 15 for blood, but not for semen. The results clearly show that DNA in saliva and blood samples is extremely sensitive to heat compared to semen. In conclusion, the study reveals the different causes of unnatural deaths, the value of virtual autopsy and the need for early DNA measurement in Kuwait.
Designing a Controller with Image-based Pipelined Sensing and Additive Uncertainties

Pipelined image-based control uses parallel instances of its image-processing algorithm in a pipelined fashion to improve the quality of control. A performance-oriented control design improves the controller settling time with each additional processing resource, which creates a resources-performance trade-off. In real-life applications, it is common to have a continuous-time model with additive uncertainties in one or more parameters that may affect the controller performance and the aforementioned trade-off. We present a robustness analysis framework for performance-oriented pipelined controllers with additive model uncertainties. We present a technique to obtain discrete-time uncertainties based on the continuous-time uncertainties for given uncertainty bounds. To benchmark such uncertainty bounds for a real system, we consider uncertainties in one element of the system, potentially caused by multiple uncertain parameters in the model. Robustness and its impact in the trade-off analysis are studied. We also provide a robustness-oriented pipelined controller design that takes into account the benchmarked uncertainties. Our results show that in performance-oriented designs, the tolerable uncertainties for a pipelined controller decrease when increasing the number of pipes. In robustness-oriented designs, the controller robustness is enhanced with each newly added pipe. We show the feasibility of our technique by implementing a realistic example in a Hardware-in-the-Loop simulation.
Estudo de ruptura da barragem da Pampulha, em Belo Horizonte: retroanálise da brecha do acidente de 1954 e ruptura hipotética nas condições atuais

Os estudos de cenarios de ruptura hipotetica de barragens se tornaram obrigatorios para determinadas classes de risco de barragens desde a promulgacao da Lei No 12.334, de 20 de setembro de 2010 que estabelece a Politica Nacional de Seguranca de Barragens (PNSB). No entanto, as metodologias, os custos e premissas de projeto, que sao de responsabilidade do proprietario da barragem, podem variar consideravelmente, obtendo-se assim resultados genericos que podem apresentar manchas de inundacao muito improvaveis ou incorretas. No presente trabalho foram avaliadas manchas de inundacao resultantes de diversos cenarios hipoteticos da ruptura da Barragem da Pampulha, que fica localizada no municipio de Belo Horizonte, no estado de Minas Gerais. O lago formado pela barragem faz parte do conjunto moderno da Pampulha que recentemente ganhou notoria importância por receber o titulo de patrimonio cultural da humanidade pela Unesco. Nestes cenarios foram avaliados metodos e premissas que usualmente sao adotados em estudos de rupturas hipoteticas. Em relacao a brecha de ruptura foi realizada uma retroanalise da ruptura que ocorreu em abril de 1954 onde foram comparados os resultados das equacoes de previsao com a geometria da brecha observada. Para verificar a influencia e os impactos sobre o hidrograma de ruptura e envoltoria da mancha de inundacao foram realizadas analises de sensibilidade variando o coeficiente de rugosidade Manning, o volume propagado, a equacao de formacao da brecha, o tamanho das celulas dos bidimensionais. Os resultados foram avaliados por meio de uma abordagem de comparacao entre as manchas previstas e observadas nos cenarios base, com calculo dos indices de desempenho F. Os resultados sugerem que alguns parâmetros e criterios sao mais sensiveis a alteracoes, destacando-se o modelo hidraulico de propagacao e a topografia. O modelos bidimensionais HEC-RAS 2D e FLO-2D foram mais conservadores que o modelo unidimensional HEC-RAS ID em que a mancha de inundacao resultante foi 35% inferior ao cenario base (no cenario Base foi utilizado o Modelo HEC-RAS 2D). Ja a modelagem realizada com modelo digital de elevacao (MDE) gratuita SRTM gerou uma mancha 16% inferior ao cenario base em que foi utilizado o MDE gerado a partir do perfilamento a laser LiDAR. Por fim, apesar das diversas incertezas inerentes ao processo de ruptura de barragens, os resultados das analises dos cenarios sao imprescindiveis para o planejamento de acoes emergenciais descritas na PAE.
Developing and Training Human Resources in Organizations

1. Introduction. 2. The Organizational Role of the Training Specialist. 3. Identifying Training Needs. 4. Maximizing the Trainee's Learning. 5. Evaluating Training Programs. 6. On-Site Training Methods. 7. Off-Site Training Methods. 8. Developing and Training Leaders: Theoretical Approaches. 9. Management and Executive Development. 10. Societal Concerns. Author Index. Subject Index.
A Bi-LSTM and k-NN Based Method for Detecting Major Time Zones of Overloaded Vehicles

Overloaded vehicles such as large cargo trucks tend to cause large traffic accidents. Such traffic accidents often bring high mortality rates, including injuries and deaths, and cause fatal damage to road structures such as roads and bridges. Therefore, there is a vicious circle in which a lot of the budgets is spent for accident restoration and road maintenance. It is important to control overloaded vehicles that are around roads in urban areas. However, it often takes a lot of manpower to track down on overloaded vehicles at appropriate interception points during a specific time. Moreover, the drivers tend to avoid interception by bypassing the interception point, while exchanging interception information with each other. In this work, the main bridges in a city are chosen as the interception point. Since installing vehicle-weighing devices on the road surface is expensive and the devices cause frequent faults after the installation, inexpensive general-purpose Internet of Things (IoT) sensors, such as acceleration and gyroscope sensors, are installed on the bridges. First, assuming that the sensing value of the overloaded vehicle is different from the nonoverloaded vehicle, we investigate the difference in the sensed values between the overloaded and nonoverloaded vehicles. Then, based on the hypothesis, we propose a new method to identify prime time zones with overloaded vehicles. Technically, the proposed method comprises two steps. In the first step, we propose a new bridge traffic classification model using Bidirectional Long Short-Term Memory (Bi–LSTM) that automatically classifies time series data to either high or low traffic condition. The Bi–LSTM model has higher accuracy than existing neural network models because it has a symmetric neural network structure, by which input information can be processed in forward and backward directions. In the second step, we propose a new method of automatically identifying top-k time zones with many overloaded vehicles under the high traffic condition. It first uses the k-Nearest Neighbor (NN) algorithm to find the sensing value, most similar to the actual sensing value of the overloaded vehicle, in the high traffic cluster. According to the experimental results, there is a high difference of the sensing values between the overloaded and the nonoverloaded vehicle, through statistical verification. Also, the accuracy of the proposed method in the first step is ~75%, and the top-k time zones in which overloaded vehicles are crowded are identified automatically.