Miracle-dz/UniFAR-FTUs huggingface dataset:
Nucleotide-Level Modeling of Genetic Regulation Using Dilated Convolutional Neural Networks

The expression of genes is the product of a complex regulatory process, whose complete nature remains elusive. In order to better understand gene regulation, this work seeks to improve on efforts to model the locations of regulatory elements of the human genome directly from raw sequences of nucleotides. Past work on building this model has focused on incorporating only small amounts of DNA for this prediction task, making it difficult to model the complex long-term dependencies that arise from DNA’s 3-dimensional conformation. In this work, we model these long-term dependencies using dilated convolutional neural networks, which offer the scaling properties of convolutions while modeling long-term dependencies with the performance of recurrent neural networks (RNNs). We show that this architecture is effective at modeling the locations of transcription factor binding sites, histone modifications, and DNAse hypersensitivity sites. We develop and release a novel dataset for this larger-context modeling task, and show that dilated convolutions perform better than standard deep convolutional neural networks and RNN-based architectures at modeling the locations of regulatory markers in the human genome.
II.—On the Structure of Calymmatotheca kidstoni Calder (emended) and Genomosperma latens gen. et sp. nov. from the Calciferous Sandstone Series of Berwickshire

Synopsis The Lower Carboniferous fossil Calymmatotheca kidstoni Calder is shown to be a simple seed and is redescribed under the new name Genomosperma kidstoni. A second species G. latens is also described. Genomosperma gen. nov. is of interest in possessing a free nucellus with a lagenostome and short salpinx. The nucellus is surrounded by an integument of about eight lobes which are free from one another and from the nucellus from near the base of the seed. The vascular details of t h e seeds have been studied and in each species pollen has been observed in the pollen chamber. Genomosperma is compared with various Pteridosperm seeds.
The assurance of Bayesian networks for mission critical systems

A prerequisite for the assurance of any mission-critical system is a comprehensive understanding of a system’s properties and behaviours. This is a challenging proposition for many AI-based Systems (AISs). Their functionality is often dictated by factors that are often outside the scope of the assurance concerns typical of conventional software systems. These distinctions have implications for all phases of the design, development, deployment and operation of AISs. They pose serious problems for existing software assurance standards, guidelines and techniques: the application of existing practices to an AIS will fail to expose or mitigate numerous system aspects that can contribute to hazardous system behaviours. This thesis introduces a number of techniques that aim to support the resolution of these problems for Bayesian Network-based Systems (BNSs). This class of system has been deployed in many applications, ranging from medical diagnostic systems to naviga- tional controls aboard autonomous systems. To date, there is no published literature on the deployment of these systems in directly safety-critical roles. This thesis introduces ap- proaches aimed at addressing three particular challenges. Firstly, it proposes a framework for conceptualising and communicating the distinctions between BNSs and conventional software systems and uses this framework to generate and refine a set of BNS verification and validation objectives. Secondly, it introduces an assurance-focussed BNS analysis technique that can provide targeted information on mission-critical aspects of a BNS. Finally, it outlines an approach for describing how BNS-specific safety evidence relates to BNS aspects, and how the evidence can be used to derive sufficient confidence in a mission-critical BNS. These contributions are then evaluated in the context of a case study that indicates the utility of the proposed techniques, and how these can be used to comprehensively structure and target the unconventional assurance concerns associated with the development of a mission-critical BNS.
Personality and Coping as a risk factor: Trauma and Post-Traumatic Stress as a stress disorder in the Ekurhuleni Metropolitan Police Department – South Africa

The Metro Police Services has a reputation for being resilient despite the amount of trauma they are exposed to. Research has shown that this occupation is one of the most stressful around the world. However, research surrounding the Metro Police Services suggests that police work is one of society’s most stressful occupations. The way in which individuals respond to such traumatisation’s’ is dependent on numerous factors, two being personality and coping. In so far, this study investigated three main areas around metro police. In order to understand their responses to trauma: whether personality factors were related to post-traumatic stress symptomatology (PTSS) in the Metro Police population; whether coping moderated the relationship between personality factors and PTSS; whether a personality factor predict coping style. A quantitative analysis was conducted among a sample of 36 officers in the Ekurhuleni area of South Africa. This study found that the relationship between Neuroticism and PTSS is mediated by coping, specifically Emotion-Focused and Dysfunctional Coping style. A relationship between Conscientiousness and PTSS showed to be prevalent, however, this is not due to the mediation effect of coping. Furthermore, Neuroticism and Extraversion showed to predict coping style. Specially, Neuroticism showed to affect EFC and DC and Extraversion showed to affect EFC. The descriptive statistics showed that this sample of Metro Police is suffering from PTSD. Implications of these findings are discussed and directions for future research are explored.
Stochastic modelling of the cell cycle

Precise regulation of cell cycle events by the Cdk-control network is essential for cell proliferation and the perpetuation of life. The unidirectionality of cell cycle progression is governed by several critical irreversible transitions: the G1-to-S transition, the G2-to-M transition, and the M-to-G1 transition. Recent experimental and theoretical evidence has pulled into question the consensus view that irreversible protein degradation causes the irreversibility of those transitions. A new view has started to emerge, which explains the irreversibility of cell cycle transitions as a consequence of systems-level feedback rather than of proteolysis. This thesis applies mathematical modelling approaches to test this proposal for the Mto-G1 transition, which consists of two consecutive irreversible substeps: the metaphaseto-anaphase transition, and mitotic exit. The main objectives of the present work were: (i) to develop deterministic models to identify the essential molecular feedback loops and to examine their roles in the irreversibility of the M-to-G1 transition; (ii) to present a straightforward and reliable workflow to translate deterministic models of reaction networks into stochastic models; (iii) to explore the effects of noise on the cell cycle transitions using stochastic models, and to compare the deterministic and the stochastic approaches. In the first part of this thesis, I constructed a simplified deterministic model of the metaphase-to-anaphase transition, which is mainly regulated by the spindle assembly checkpoint (the SAC). Based on the essential feedback loops causing the bistability of the transition, this deterministic model provides explanations for three open questions regarding the SAC: Why is the SAC not reactivated when the kinetochore tension decreases to zero at anaphase onset? How can a single unattached kinetochore keep the SAC active?
Meditation for level of institutional quality to combat income inequality through financial development

Institutional role to perpetuate the smooth and sustained functioning of economies has consensus in literature but the optimal level of institutional quality for prosperity is hardly discussed. On the other side, widening income inequality is attracting the attention of worldwide researchers now days. This paper is an attempt to explore the relation between income inequality and financial development varying with level of institutional quality. To this end, unbalanced panel data set for 124 countries covering the time span 1990-2015 is used and the instrumental variable threshold regression approach is applied to prove that a threshold level of institutional quality matters to reduce income inequality through financial development. Until then, financial development will be ineffective to overcome income inequality.
Perceptually based learning of shape descriptions for sketch understanding

We are interested in enabling a generic sketch recognition system that would allow more natural interaction with design tools in various domains. Instead of writing recognizer code for each new domain, new shapes should be added by describing them in a shape description language. While writing such descriptions is easier than writing code, it is still not a particularly easy or natural mode of interaction. The most natural way to teach new symbols to the system would be simply drawing them. This thesis presents a learning system that takes in a drawn symbol and produces a textual description of it appropriate for using in a recognition engine. The main challenge is to decide which properties of the example are relevant. People cope with this task in part, we believe, through innate perceptual biases. We use studies of human perception of geometry to understand these biases and use them to help select the relevant properties from a single example. The main generalization power of the system is derived from two sources: 1) a qualitative description vocabulary that reflects properties that people pay attention to and 2) mechanisms, derived from the observations about perception, that adjust the relative importance of different properties based on the overall configuration of the geometric primitives in the example. Using this approach the system is able to adequately describe complex symbols by identifying a small number of relevant properties. Thesis supervisor: Randall Davis Title: Professor of Electrical Engineering and Computer Science
Chinese consumer trust and preferences for organic labels from different regions

Purpose The organic food sold in China can bear organic labels from different countries/regions. The purpose of this paper is to assess the trust and preferences of consumers for tomatoes carrying these different labels. Design/methodology/approach The data came from real choice experiments conducted in Shandong Province, China. A mixed logit model was used to analyze consumer willingness to pay (WTP). Findings Results indicated that, among the four organic labels considered in this study, the highest WTP was expressed for organic label from the European Union, followed by Hong Kong’s organic label, Japanese organic label and, lastly, by the Chinese mainland organic label. Consumer trust has a positive effect on their WTPs for the four organic labels. Providing consumers with information on organic can significantly lift their WTPs, and reduce the gaps between WTPs for different organic labels. Originality/value This research is of academic value and of value to food suppliers. International food marketers are recommended to equip their products with proper organic labels and initiate additional consumer education.
Query refinement for patent prior art search

A patent is a contract between the inventor and the state, granting a limited time period to the inventor to exploit his invention. In exchange, the inventor must put a detailed description of his invention in the public domain. Patents can encourage innovation and economic growth but at the time of economic crisis patents can hamper such growth. The long duration of the application process is a big obstacle that needs to be addressed to maximize the benefit of patents on innovation and economy. This time can be significantly improved by changing the way we search the patent and non-patent literature. Despite the recent advancement of general information retrieval and the revolution of Web Search engines, there is still a huge gap between the emerging technologies from the research labs and adapted by major Internet search engines, and the systems which are in use by the patent search communities. In this thesis we investigate the problem of patent prior art search in patent retrieval with the goal of finding documents which describe the idea of a query patent. A query patent is a full patent application composed of hundreds of terms which does not represent a single focused information need. Other relevance evidences (e.g. classification tags, and bibliographical data) provide additional details about the underlying information need of the query patent. The first goal of this thesis is to estimate a uni-gram query model from the textual fields of a query patent. We then improve the initial query representation using noun phrases extracted from the query patent. We show that expansion in a query-dependent manner is useful. The second contribution of this thesis is to address the term mismatch problem from a query formulation point of view by integrating multiple relevance evidences associated with the query patent. To do this, we enhance the initial representation of the query with the term distribution of the community of inventors related to the topic of the query patent. We then build a lexicon using classification tags and show that query expansion using this lexicon and considering proximity information (between query and expansion terms) can improve the retrieval performance. We perform an empirical evaluation of our proposed models on two patent datasets. The exper-
Housing wealth and household consumption in urban China

Using a large Chinese household survey data set, we investigate the effect of home value appreciation on urban household consumption. The paper identifies the causal effect of housing wealth using both Two-Stage Least Squares (2SLS) estimates and regression discontinuity designs. The research demonstrates that the housing boom in China has resulted in higher consumption and that a 10% increase in home wealth raises overall consumption by approximately 3%. The average marginal propensity to consume out of housing wealth is about 5 cents with substantial heterogeneity across household characteristics. The findings highlight the role of mortgage debts, health insurance, education and risk preference in explaining the variation in household consumption. Our results persist when we adopt different proxies for housing wealth.
Mathematics and Music: The Effects of an Integrated Approach on Student Achievement and Affect

MATHEMATICS AND MUSIC: THE EFFECTS OF AN INTEGRATED APPROACH ON STUDENT ACHIEVEMENT AND AFFECT Elizabeth Rebecca Wentworth This study looks at the use of integrated mathematics and music lessons at the high school level. Four lessons were taught by the researcher in both a research and a control class to determine how mathematically motivated music instruction affects students understanding of operations of functions, composition of functions, inverse functions and domain and range. A pretest-posttest was used to determine the effect of these lessons and a questionnaire was used to identify differences between groups and to help determine the effect of musical applications of mathematics on students’ mathematical perceptions, self-efficacy and grit. The pretest-posttest included both a standard mathematics section and a section involving non-musical applications. A gain score approach using independent sample t tests was used to determine the impact of the integrated instruction. The research group demonstrated significantly greater gains both overall and on the applications portion of the exam. Additional qualitative analysis was done to determine how the posttests differed between groups. Three major differences were identified: the research group used function notation more frequently than the control group, the control group demonstrated confusion between composition of functions and inverse functions while the research group did not and the research group showed more mathematical work for the applications portion of the exam than the control group. Qualitative analysis was also done to identify trends in the questionnaire data. Among the major differences between groups was the increased willingness to work with mathematical applications in the future by the research group compared to the control group. The integrated instruction led to comparable and in some cases significantly better mathematics outcomes than the control group and led students to an increased willingness to work with mathematical applications both on the posttest and moving forward.
Apakah Corporate Governance Disclosure, Intellectual Capital, Dan Karakteristik Perusahaan Merupakan Faktor Determinan Nilai Perusahaan? (Studi Empiris Pada Perusahaan Sektor Infrastruktur, Utilitas, Dan Transportasi Periode 2015-2017)

Abstract . This study aims to determine the effect of corporate governance disclosure, intellectual capital, firm characteristics (profitability, leverage, and firm size) on firm value . Population this study the infrastructure, utilities, and transportation sector companies listed on the Indonesia Stock Exchange (IDX) 2015-2017 period. Sampling technique used by purposive sampling method and analysis of data with the regression analysis data panel.The analysis results are corporate governance disclosure, intellectual capital and firm characteristics (profitability, leverage, and firm size) simultaneously determine firm value. But partially that profitability, leverage, and firm size has a significant positive effect on firm value. While corporate governance disclosure and intellectual capital have no effect on firm value. Abstrak . Penelitan ini bertujuan untuk mengetahui pengaruh corporate governance disclosure, intellectual capital, karakteristik perusahaan (profitabilitas, leverage, dan ukuran perusahaan) terhadap nilai perusahaan . Popoulasi penelitian ini adalah perusahaan se k tor infrastruktur, utilitas, dan transportasi yang terdaftar di Bursa Efek Indonesia (BEI) periode 2015-2017. Teknik samp ling menggunakan purposive sampling dan analisis data dengan analisis regresi data panel. Hasil analisis; corporate governance disclosure, intellectual capital dan karakteristik perusahaan (profitabilitas, leverage, dan ukuran perusahaan) secara simultan merupakan faktor detemininan nilai perusahaan . Namun demikian secara parsial profitabilitas, leverage, dan ukuran perusahaan berpengaruh positif signifikan terhadap nilai perusahaan. Sedangkan variabel corporate governance disclosure dan intellectual capital tidak berpengaruh terhadap nilai perusahaan. Kata kunci . Coporate Governance Disclosure, Intellectual Capital, Profitabilitas, Ukuran Perusahaan, Nilai Perusahaan , Leverage .
The Strategic Effects of Trademark Protection

We study the effects of trademark protection on firms’ profits and strategy using the 1996 Federal Trademark Dilution Act, which granted additional legal protection to selected trademarks. We find that the FTDA raised treated firms’ operating profits and was followed by a spike in trademark lawsuits and lower entry and exit in affected product markets. Treated firms reduced R&D spending, produced fewer patents and new products, and recalled a higher number of unsafe products. Our results suggest that stronger trademark protection negatively affected innovation and product quality. (JEL D22, K2, L43, O31, O34, O38) Authors have furnished code/data and an Internet Appendix, which are available on the Oxford University Press Web site next to the link to the final published paper online.
Wind Turbine Optimization Under Uncertainty with High Performance Computing

The widespread proliferation of wind turbines for power generation is driving the development of devices that are both e cient and minimally disruptive to surrounding communities. Optimized con gurations can become ine ective in the presence of unexpected operating scenarios, for example in the presence of insect or dust contamination, thus requiring recalibration and adjustments. Robust design procedures aim at limiting the potential impact of uncertainties on performance and are an e ective risk-mitigation strategy. In this work a wind turbine multi-physics simulation tool EOLO that represents the aerodynamic loading, realistic turbulent wind scenarios, uid-structural interactions and acoustics is presented. The geometrical con guration of a realistic turbine is optimized under insect contamination (input uncertainty) using a novel Simplex Stochastic Collocation (SSC) method. This methodology provides a wealth of information regarding the overall performance statistics (output uncertainties) and forms the basis for the exploration of several robust design options. We introduce a new process that extends the usual concept of variance minimization. The proposed robust design strategy is coupled to a customized multi-objective genetic algorithm. The overall process requires a large number of computations and therefore we developed a simulation environment LELAND to carry out these analysis on large scale parallel clusters. Leland is a dynamic scheduler that starting from a small initial set of computations automatically selects the new candidate simulations to be performed to increase the e ciency of both the optimization procedure and the uncertainty quanti cation method.
Subcarrier optical wireless communications in atmospheric turbulence

In this thesis, we focus on performance study of subcarrier optical wireless communications (OWC) systems in atmospheric turbulence. Laser beam propagating through turbulence channel induces scintillation and phase aberration, which can result in significant performance degradation. The error rate performance of subcarrier OWC systems with lower order phase-shift keying (PSK) over the Gamma-Gamma turbulence channels is investigated using a direct integration method. Such analysis is generalized to M -ary PSK modulated OWC systems over strong atmospheric turbulence channels through a moment generating function approach. Since noncoherent or differentially coherent modulation schemes do not require carrier phase information at the receiver, such modulation schemes can be employed in scenarios where the carrier phase information cannot be tracked accurately. Error rate expressions of such OWC systems with noncoherent or differentially coherent modulation schemes over the Gamma-Gamma turbulence channels are also developed. Asymptotic relative performance of subcarrier OWC systems with noncoherent or differentially coherent modulation schemes with respect to those using coherent modulation schemes is quantified analytically. Besides atmospheric turbulence, other sources can also introduce performance degradation to an outdoor OWC system. Through our analysis, it is shown that pointing errors can also degrade the performance of an OWC system significantly. The effect of pointing errors together with the Gamma-Gamma turbulence channel can be evaluated using the analytical tools we developed. As another performance impairment source, the effect of carrier phase synchronization error on performance of subcarrier binary PSK and quadrature PSK systems over atmospheric turbulence channels is also studied. In order to quantify the asymptotic noise reference loss for OWC systems over the lognormal channels, a novel auxiliary random variable technique is introduced. Since the performance of outdoor subcarrier OWC systems is found to be impaired severely under strong turbulence conditions, spatial diversity techniques are introduced to mitigate the effects of turbulence induced fad-