Miracle-dz/UniFAR-FTUs huggingface dataset:
A semiparametric marginalized zero-inflated model for analyzing healthcare utilization panel data with missingness

ABSTRACT Zero-inflated count outcomes arise quite often in research and practice. Parametric models such as the zero-inflated Poisson and zero-inflated negative binomial are widely used to model such responses. However, interpretations of those models focus on the at-risk subpopulation of a two-component population mixture and fail to provide direct inference about marginal effects for the overall population. Recently, new approaches have been proposed to facilitate such marginal inferences for count responses with excess zeros. However, they are likelihood based and impose strong assumptions on data distributions. In this paper, we propose a new distribution-free, or semiparametric, alternative to provide robust inference for marginal effects when population mixtures are defined by zero-inflated count outcomes. The proposed method also applies to longitudinal studies with missing data following the general missing at random mechanism. The proposed approach is illustrated with both simulated and real study data.
Detection of Basic Human Physical Activities With Indoor–Outdoor Information Using Sigma-Based Features and Deep Learning

The devices created on account of the developments in wearable technology are increasingly becoming a part of our daily lives. In particular, sensors have enhanced the usefulness of such devices. The aim of this paper is to detect human physical activity along with indoor/outdoor information by using mobile phones and a separate oxygen saturation sensor. There is no relevant dataset in the literature for this type of detection. For this purpose, data from four different types of human physical activity was collected through mobile phone and oxygen saturation sensors; 12 people aged between 20–65 years participated in the study. During the data collection process, different physical activities under different environmental conditions were performed by the subjects in 10 min. As a next step, a novel deep neural network (DNN) model specifically designed for physical activity recognition was proposed. In order to improve accuracy and reduce the computational complexity, standard deviation (sigma)-based features were introduced. To evaluate its efficacy, we conducted comparisons with selected machine learning algorithms on our proposed dataset. The results on our dataset indicate that the multimodal sigma-based features give the best classification accuracy of 81.60% using our proposed DNN method. Furthermore, the accuracy of the classification made with our proposed DNN method without sigma-based features was 79.04%.
Chromatin Inducible Targeting (CIT): a novel system to manipulate gene expression at expanded CAG/CTG repeats

Epigenetic modifications have drawn significant attention due to their crucial roles in development and disease. The recent emergence of epigenome editing tools provides an attractive strategy for manipulating chromatin structure and gene expression. They have been shown to successfully activate and silence targeting genes in conjunction with chromatin modifying enzymes. A major gap in knowledge pertains to how epigenome editing differs in efficiency at distinct DNA contexts. The focus of this thesis was to build a novel system, chromatin inducible targeting (CIT), to test the effect of sequence context on the efficiency of chromatin modifying enzymes to control gene expression. Specifically, I tested the effect of CAG/CTG repeat expansion on the ability of HDAC5, HDAC3, and DNMT1 targeting to modify chromatin structure. CIT can be divided into three major components. First, a GFP-based reporter monitors gene expression. It contains an intron carrying a varying number of CAG/CTG triplets. Second, I adapted the ParB-INT targeting system such that any protein of interest can be recruited within 300bp of the expanded CAG/CTG repeat tract. Third, an ABA-based chemical inducible proximity system that allows for spatiotemporal and reversible targeting of proteins to chromatin. Notably, CIT is also well suited to ask whether chromatin modifying enzymes work locally to regulate gene expression or in trans. I found that HDAC5 targeting silences the GFP reporter while decreasing local histone acetylation. Interestingly, HDAC5 preferentially silences the reporter with the shorter repeat tract, probably because of the lower levels of histone acetylation present at the expanded repeat tract before targeting. HDAC5 is thought to deacetylate histones by recruiting another HDAC, HDAC3. Surprisingly, however, HDAC3 targeting increased GFP expression, and its effect is insensitive to the size of the repeat tract. This effect is controversial to the current models of HDAC3 function that deacetylation of histone tails by HDAC3 in gene body improves transcriptional output. Moreover, I found that Dnmt1 targeting has a similar effect on gene silencing as HDAC5 targeting: it is more efficient in the context of shorter CAG/CTG repeats. CIT provides a novel strategy to optimize the efficiency of epigenome editing in a highly controlled and flexible manner. Our data uncover novel mechanisms of gene regulation by these chromatin modifiers and guides their use in manipulating chromatin structure. CIT is suitable for screening and can be adapted to study the effect of virtually any sequences on epigenome editing.
The contribution of fish farming to household wellbeing of Fish Farmers in Kitui Central Sub-County, Kitui County

Fisheries are a significant sector to the national and household economies in Kenya. The Kenya government initiated the Economic Stimulus Program (ESP) in 2010 to help aquaculture projects in order to jump start the economy by providing food and income to the rural inhabitants as a way of eradicating poverty and creating jobs to the poverty stricken areas. However, there is little information on the contribution of fish farming to the household wellbeing of the farmers adopting the fish farming inKitui Central sub-county. Therefore, the researcher carried out this study to determine the contribution of fish farming to the household wellbeing of the fish farmers in the Kitui Central SubCounty, Kitui County. A sample of sixty (60) fish farmers were used from the targeted 200 fish farmers who benefitted from the government ESP support. Semi structured questionnaires were used to collect primary data that was analyzed using Excel and Statistical Package for Social Sciences (SPSS) version 22. The study revealed that fish farming had a significant contribution to the household wellbeing (income) of households in Kitui Central Sub-county, Kitui County. This was by improving household income (38.9%) and putting idle land to use (24.1%). The harvested fish was sold to the market as indicated by 63% of the respondents as well as home consumption (37%). This ended up improving the livelihood of the fish farmers. Other benefits from fish farming included; more household assets (50.6%), fees payment (40.7%), better health care (38.9%) and 33.3% diet diversity. It was also established that there is a strong positive correlation (r = 0.73, P < 0.05) between fish farming and household wellbeing. This study presents lessons from farmers who are attempting to eke out a livelihood from small scale fish farming with or without government support. It illustrates some of the successes and challenges of the activity and offers insight to future fish farming success for farmers willing to attempt it. To the existing farmers it provides an eye opener on their weaknesses. This research will enable the government, other development partners to get information to help them make informed decisions in future and refocus on how best to support the fish farming industry for sustainability.
Bandit Algorithms in Information Retrieval

Bandit algorithms, named after casino slot machines sometimes known as “one-armed bandits”, fall into a broad category of stochastic scheduling problems. In the setting with multiple arms, each arm generates a reward with a given probability. The gambler’s aim is to find the arm producing the highest payoff and then continue playing in order to accumulate the maximum reward possible. However, having only a limited number of plays, the gambler is faced with a dilemma: should he play the arm currently known to produce the highest reward or should he keep on trying other arms in the hope of finding a better paying one? This problem formulation is easily applicable to many real-life scenarios, hence in recent years there has been an increased interest in developing bandit algorithms for a range of applications. In information retrieval and recommender systems, bandit algorithms, which are simple to implement and do not require any training data, have been particularly popular in online personalization, online ranker evaluation and search engine optimization. This survey provides a brief overview of bandit algorithms designed to tackle specific issues in information retrieval and recommendation and, where applicable, it describes how they were applied in practice. Dorota Głowacka (2019), “Bandit Algorithms in Information Retrieval”, Foundations and Trends © in Information Retrieval: Vol. 13, No. 4, pp 299–424. DOI: 10.1561/1500000067. Full text available at: http://dx.doi. org/10.1561/1500000067
Gridless Sparse Direction Finding Method for Correlated Signals with Gain-Phase Errors

In practical array systems, the gain-phase errors among antennas degrade the performance of direction finding significantly. In this paper, a novel sparse system model for direction of arrival (DOA) estimation in the scenario with gain-phase errors is proposed by exploiting the signal sparsity in the spatial domain. In contrast to the existing sparse-based methods using the grids to construct the dictionary matrix, a novel gridless method based on atomic norm and convex optimization is proposed, where the gain-phase errors are described by a diagonal matrix. With the Schur complement, a semidefinite programming is formulated from the optimization problem, and can be solved efficiently. With the gain-phase errors, the corresponding Cram’er-Rao lower bound (CRLB) of direction finding is derived as an estimation benchmark. Simulation results show that the proposed method performs better than the state-of-the-art methods in the scenario with correlated signals and gain-phase errors.
An Approach for Parameter Estimation of Maneuvering Targets With Nonlinear Motions

To compensate the range cell migration and Doppler frequency spread of a maneuvering target during the integration time, this paper proposes a new parameter estimation method based on sub-band dual-frequency conjugate (SDFC)–Radon chirp rate–quadratic chirp rate algorithm. In this method, SDFC process is first applied to reduce the equivalent frequency and Radon chirp rate–quadratic chirp rate algorithm is then performed to obtain the estimates. Both simulated and real-data results demonstrate the effectiveness of the proposed algorithm.
Mesta (Hibiscus spp.) – a potential feedstock for bioethanol production

ABSTRACT Mesta crop biomass is one of the unexplored lignocellulosic feedstocks for second-generation bioethanol production. The compositional analysis of two mesta species, namely Hibiscus sabdariffa and H. cannabinus were carried out which revealed that the mesta contains 41.89–46.50% cellulose that can be saccharified to release fermentative sugar. Among different physical and physico-chemical pretreatment methods employed, cold alkali (2%) treatment showed maximum cellulose enrichment (38.71%) and significant lignin removal (27.27% of total). Optimization of saccharification process for pretreated mesta biomass was carried out using Box–Behnken design. Based on the observations, use of 4.02% substrate loading, 15.02 FPU/mL of cellulase from psychrotolerant Aspergillus niger SH3, and 5.01 IU/gds of β-glucosidase from Pseudomonas lutea BG8, led to 533.25 mg/gds sugar release from the pretreated biomass. Simultaneous saccharification and fermentation was carried out using efficient thermotolerant yeast strain Saccharomyces cerevisiae LN that resulted in 4.1 g/L ethanol production. It can be concluded that mesta crop can be a good source for the production of second-generation biofuel and the ethanol yield can be further improved by use of accessory enzymes and co-fermenting yeast.
THE IMPACT OF OCEAN ENVIRONMENT ON AUTOMATIC AURAL CLASSIFICATION OF MARINE MAMMALS

Passive acoustic monitoring (PAM) is widely in use to study marine mammals in their underwater habitats. Since marine mammals can be found in all ocean basins, their habitats cover diverse underwater environments. Properties of the ocean environment, such as sound speed profile, bathymetry, and sediment properties can be markedly different between these diverse habitats, leading to differences in how a marine mammal’s vocalization is altered by propagation effects. This distortion of vocalizations may impact the accuracy of PAM systems. Thus, to develop a PAM system capable of operating in numerous environments one must understand how propagation effects impact these systems. Previous effort has shown that a prototype aural classifier developed at Defence R&D Canada could successfully discriminate several cetacean species’ vocalizations in a relatively limited data set. The aural classifier was found to be an effective PAM tool because it employs perceptual signal features, which model features used by the human auditory system. The current work used the OASES (Ocean Acoustics and Seismic Exploration Synthesis) pulse propagation model to examine the robustness of the classifier under various environmental conditions. Preliminary results from transmitting cetacean vocalizations over several ranges in a simulated underwater environment are discussed. The modelled environment used to obtain these results was based on environmental data collected during propagation trials. Aural classification accuracy was compared for signals propagated over different ranges and provided a preliminary measure for the robustness of the perceptual features to propagation effects.
Hopping Conductivity in Granular Metals

)Work supported by the National Science Foundation. *Alfred P. Sloan Research Fellow. E. F. Gross, Vsp. Fiz. Nauk 76, 433 (1962), and 103, 431 (1971) [Sov. Phys. Usp. 5, 195 (1962) and 14, 104 {1971)). A. Compaan and H. Z. Cuxnmins, Phys. Rev. B 6, 4753 (1972). Y. Petroff, P. Y. Yu, and Y. B. Shen, Phys. Bev. Lett. 29, 1558 (1972). P. Y. Yu, Y. R. Shen, Y. Petroff, and L. M. Falicov, Phys. Rev. Lett. 30, 283 (1973). E. F. Gross, A. G. Zhilich, B. P. Zakharchenya, and A. V. Varfalomeev, Fiz. Tverd. Tela 3, 1445 (1961) [Sov. Phys. Solid State 3, 1048 (1961)j. S. Nikitine, J. B. Grun, and M. Certier, Phys. Kondens. Mater. 1, 214 (1963). W. S. Brower, Jr., and H. S. Parker, J. Cryst. Growth 8, 227 (1971). A. Compaan and H. Z. Cummins, Bull. Amer. Phys. Soc. 18, 75 (1973). Air Products and Chemicals, Inc. , Allentown, Pa. The data points in Fig. 2 indicate the observed Raman intensity divided by the incident laser power. Absorption corrections, which are less than 4' in this frequency range, have not been included. B. Loudon, Advan. Phys. 13, 423 (1964); J. L. Birman, "Theory of Crystal Space Groups and Infra-Bed and Raman Processes in Insulating Crystals" in Handbuch der Physik, edited by S. Flugge (Springer, New York, 1973, to be published), Vol. 25, Part 2b. ' See, for example, M. Born and M. Bradburn, Proc. Roy. Soc. , Ser. A 188, 161 (1947); L. N. Ovander, Opt. Spectrosk. 9, 571 {1960) [Opt. Spectrosc. 9, 302 (1960)] . '3J. L. Birman, to be published. P. F. Williams and S. P. S. Porto, Bull. Amer. Phys. Soc. 18, 411 (1973); P. F. Williams, Ph. D. thesis, University of Southern California, 1973 {unpublished) . P. Y. Yu, Y. R. Shen, and Y. Petroff, Bull. Amer. Phys. Soc. 18, 411 (1973). R. M. Martin, Phys. Rev. B 4, 3676 (1971).
Using devitalised seeds in myrmecological research

Field studies of myrmecochory (seed dispersal by ants) can benefit from the use of devitalised seeds, particularly where these studies may involve invasive plants or plants outside of their natural range. Here, we test three different methods of seed devitalisation – gamma irradiation (10.6 kGy over 9.1 h at 23.7–25.4 °C), heating (150 °C for 30 min) and freezing (submerged in liquid nitrogen for 10 min) – in three different Australian plants: Acacia longifolia, Acacia melanoxylon and Kennedia rubicunda. We further test their suitability post‐treatment as stimuli for use in field studies of myrmecochory. Gamma radiation and exposure to heat effectively inhibited germination, whereas freezing did not. The devitalisation treatments did not appear to affect the attractiveness of seeds to ants as there was no significant difference in daily collection rate of control seeds compared to devitalised seeds.
Healthy Eating Index-2010 and General/Central Obesity Among Adult Women Living in Tehran, Iran

Background: The prevalence of central and general obesity is increasing to epidemic levels and turning to a social health problem. A possible association may exist between nutritional adequacy and obesity. Objectives: This study aimed to investigate the relationship of general and central obesity with diet quality in Iranian women by 2010 version of Healthy Eating Index (HEI-2010). Methods: A total of 460 women aged 20 50 years old participated in this cross-sectional study. Dietary intake data was collected using a validated food frequency questionnaire. Anthropometric assessment was performed by standard methods and HEI-2010 was used to investigate diet quality. The association between HEI-2010 and general/central obesity was analyzed by logistic regression. Results: The frequency of general and central obesity was 31 (15.1%) and 95 (21.5%), respectively. Of the participants, 330 (74.8%) had a low HEI-2010 total score. After adjusting for confounders, those with the high HEI-2010 total score had lower risk of central obesity (OR = 0.3; CI 95%: 0.14 0.70); however, the results were not significant for general obesity. Among the components of HEI-2010, the scores of dairy, total vegetables, empty calorie foods, refined grains and sodium were negatively associated with both general and central obesity (P ≤ 0.05). Conclusions: Lower risk of general and abdominal obesity is associated with a higher quality of dietary intake. Furthermore, the nutrition education programs for preventing obesity should be emphasized to promote higher intakes of dairy, fruits and vegetables and preventing high consumption of energy-dense foods and sodium.
Immunohistochemical Study of NR2C2, BTG2, TBX19, and CDK2 Expression in 31 Paired Primary/Recurrent Nonfunctioning Pituitary Adenomas

This study investigated potential markers for predicting nonfunctioning pituitary adenoma (NFPA) invasion and recurrence by high-throughput tissue microarray analyses. We retrospectively studied two groups of patients: 60 nonrecurrent NFPA cases that included noninvasion and invasion subtypes and 43 recurrent cases that included primary NFPA. A total of 31 paired patient samples were evaluated (12 patients with one surgery and 31 who had undergone two operations, with both tumors analyzed). Expressions of nuclear receptor subfamily 2 group C member 2 (NR2C2), B cell translocation gene 2, T-box-19 (TBX19), and cyclin-dependent kinase 2 (CDK2) in surgically resected specimens were assessed by immunohistochemistry. The relationships between marker expression and clinical characteristics including age, sex, tumor volume, and follow-up time were analyzed. Tumor volume and invasion as well as follow-up time were significantly associated with invasion and recurrence (P < 0.01). Of the 60 nonrecurrent samples, 15/41 and 13/19 showed high NR2C2 expression in the noninvasion and invasion groups, respectively (χ2 =5.287, P = 0.021). NR2C2 was also overexpressed in 43 primary recurrent cases (χ2 =5.433, P = 0.02), whereas CDK2 (χ2 = 11.242, P = 0.001) and TBX19 (χ2 = 4.875, P = 0.027) were downregulated. In the 31 paired samples, NR2C2 was more highly expressed in the recurrent as compared to the primary tumor. High NR2C2 expression was associated with NFPA invasion, recurrence, and progression, while TBX19 and CDK2 were associated with NFPA recurrence.
Terror management theory: The effect of death on criminogenic thought patterns

Terror Management Theory has been applied with judges and juries in the courtroom, but not yet with criminals themselves. The current study looks for an association between criminogenic thought patterns and worldviews of criminal behavior. Thought patterns were assessed with the Measure of Criminogenic Thinking Styles (MOCTS), while worldviews were measured with the associate section of the Measures of Criminal Attitudes and Associates. Results indicated that mortality salience did not increase criminogenic thinking. However, criminogenic thinking scores from the MOCTS were correlated with scores on the associate scale under mortality salience. These findings may suggest that participants with a worldview of criminal behavior resort to their worldview with complementarily high levels of criminogenic thinking following anxiety from a mortality salience.
Morphology and Stellar Populations in the Gas-Rich, Giant LSBGs

An unexpected characteristic of low surface brightness galaxies (LSBGs) is that a significant number are massive and possess substantial amounts of atomic gas. We present preliminary results of an ongoing program to obtain BVRIJHK imaging, along with some nuclear spectroscopy, of a well-defined sample of LSBGs which are gas-rich and of similar size to giant, high surface brightness spiral galaxies (HSBGs). These LSBGs span the entire range of Hubble disk morphologies. While their disks are bluer, on average, than comparable HSBGs, the optical morphology of massive LSBGs indicates that many of these systems have undergone previous star formation episodes. They typically have long disk scale lengths, and range from $M_B = -16 to -22 (H_0 = 75 km/s Mpc^{-1})$. About half of the LSBGs with bulges show evidence of nuclear activity, and $\sim 30%$ have appear to be barred. These massive, gas-rich LSBGs apparently have varied, and often complex, evolutionary histories.
IMPROVING HYBRID REPUTATION MODEL

Peer-to-Peer (P2P) systems have the ability to bond with millions of clients in business and knowledge scenario. The mechanism that leads users to distribute files without the need of centralized servers has achieved wide recognition among internet users. This also permits for a range of applications further than simple file sharing. he main problem lies in the fact that peers have to customarily intermingle with mysterious peers in the absence of trusted third parties. Usually the lack of incentives often makes these strange peers to act as freeriders and thus reduce the system performance. The trustworthiness among peers is portrayed by applying the knowledge obtained as a result of reputation mechanisms. This paper endows with a new reputation model in association with a detailed survey of diverse reputation models. The proposed model suggests a hybrid reputation model through dynamic regrouping.