Miracle-dz/UniFAR-FTUs huggingface dataset:
A general result on the mean integrated squared error of the wavelet hard thresholding estimator under α-mixing dependence

Abstract: In this note, we consider the estimation of an unknown function f for weakly dependent data (α-mixing) in a general setting. Our contribution is theoretical: we prove that a wavelet hard thresholding estimator attains a sharp rate of convergence under the mean integrated squared error (MISE) over Besov balls without imposing too restrictive assumptions on the model. Applications are given for two types of inverse problems: the deconvolution density estimation and the density estimation in a GARCH-type model, both improve existing results in this dependent context. Another application concerns the regression model with random design.
RELATIONSHIP OF ANTHROPOMETRIC VARIABLES WITH FASTING BLOOD SUGAR IN MODERATE AND SEDENTARY WORKERS

Background: Failure to engage in physical activity constitutes the fourth most important risk factor leading to death in the entire world. Modernization has resulted in increased rates of diabetes, primarily because of a decrease in physical activity, and increasing prevalence of obesity. There is a close association between obesity and type 2 diabetes. The likelihood and severity of type 2 diabetes is closely linked with body mass index. Insulin resistance, which is the basis of type 2 diabetes mellitus, is associated with both visceral and subcutaneous fat content. Objective of the Study: To assess relationship of anthropometric variables with fasting blood glucose in moderate and sedentary workers in Jammu region. Materials and Methods: A total of 300 subjects, 150 each from Group-1 (moderate workers) and Group-2 (sedentary workers) consisting of 75 males and 75 females were selected for this study. Record of body weight, height, waist circumference and hip circumference was made as per WHO standards. The body mass index and waist hip ratio were calculated. Abdominal obesity was assessed by measuring waist hip ratio. Fasting blood glucose estimation was done by fully enzymatic glucose oxidase-peroxidase method. Mean and standard deviation were calculated and reported for quantitative variables. The statistical difference in mean value was tested using unpaired ‘t’ test. Linear regression was used for unilateral comparison. A pvalue of <0.05 was considered as statistically significant. All p-values reported are two-tailed. Results: The mean values of age, weight, body mass index, waist circumference, hip circumference, waist-hip ratio (males only), waist-height ratio and abdominal volume index in Group 1 (moderate workers) subjects were significantly less as compared to those of Group 2 (sedentary workers). Relationship of waist circumference with fasting blood sugar in Group 2 was found to be significant, while anthropometric parameters showed no significant relationship with fasting blood sugar. Conclusion: Anthropometric variables such as weight, waist circumference, hip circumference, waist-hip ratio, waist-height ratio and abdominal volume index are significantly affected in sedentary workers, showing that sedentary work profile affects the general body mass index and leads to both central and generalized obesity.
Quantitatively tight sample complexity bounds

I present many new results on sample complexity bounds (bounds on the future error rate of arbitrary learning algorithms). Of theoretical interest are qualitative and quantitative improvements in sample complexity bounds as well as some techniques and criteria for judging the tightness of sample complexity bounds. On the practical side, I show quantitative results (with true error rate bounds sometimes less than 0.01) for decision trees and neural networks with these sample complexity bounds applied to real world problems. I also present a technique for using both sample complexity bounds and (more traditional) holdout techniques. Together, the theoretical and practical results of this thesis provide a well-founded practical method for evaluating learning algorithm performance based upon both training and testing set performance. Code for calculating these bounds is provided.
Molecular Cloning and Evidence for Osmoregulation of the A'-Pyrroline-5-Carboxylate Reductase (proC) Gene in Pea (Pisum sativum L.)l12

Several cDNA clones encoding A1-pyrroline-5-carboxylate re- ductase (P5CR, L-proline:NAD[P]+ 5-oxidoreductase, EC 1.5.1.2), which catalyzes the terminal step in proline biosynthesis, were isolated from a pea leaf library screened with a 32P-labeled Aval fragment of a soybean nodule P5CR cDNA (A.J. Delauney, D.P.S. Verma [1990] Mol Gen Genet 221: 299-305). DNA sequence analysis of one full-length 1.3-kb clone (pPPS3) indicated that the pea P5CR gene contains a single major open reading frame encod- ing a polypeptide of 28,242 Da. Genomic analysis suggested that two to three copies of the P5CR gene are present per haploid genome in pea. The primary structure of pea P5CR is 85% identical with that of soybean and exhibits significant homology to human, yeast, and Escherichia coli P5CR. The sequence of one of four highly conserved domains found in all prokaryotic and eukaryotic P5CRs is similar to the consensus sequence for the NAD(P)H-binding site of other enzymes. The pea P5CR cDNA hybridized to two transcripts, 1.3 and 1.1 kb in size, in polyadenylated RNA purified from leaf tissues of mature, light-grown plants (4 weeks old). Only the 1.3-kb transcript was detected in younger (1 week old) greened seedlings or in etiolated seedlings.
Adjustments for survey unit nonresponse under nonparametric response mechanisms

The weighting cell estimator corrects for unit nonresponse by dividing the sample into homogeneous groups (cells) and applying a ratio correction to the respondents within each cell. Previous studies of the statistical properties of weighting cell estimators have assumed that these cells correspond to known population cells with homogeneous char­ acteristics. In this article, we study the properties of the weighting cell estimator under a response probability model that does not require correct specification of homogeneous population cells. Instead, we assume that the response probabilities are a smooth but otherwise unspecified function of a known auxiliary variable. Under this more general model, we study the robustness of the weighting cell estimator against model misspecification. We show that, even when the population cells are unknown, the estimator is consistent with respect to the sampling design and the response model. We describe the effect of the number of weighting cells on the asymptotic properties of the estima­ tor. Simulation experiments explore the finite sample properties of the estimator. We
Assessment of the Contemporaneous Impacts of Gross Domestic Product and Renewable Energy Consumption, Applying the Dynamic Panel Data: Evidence from Developed Countries

The vast majority of the investigations analyze the effect of renewable energy utilization on gross domestic product (GDP) with single equation model and the others utilize dynamic panel data. The motivation behind this investigation is to build up a concurrent equations model to investigate the collaboration amongst GDP and sustainable power utilization in a dynamic panel data. This model uses GDP and renewable energy consumption as endogenous variables and seven factors as exogenous variables. By using a dynamic panel data of 30 developed countries from 1990 to 2015, with using the two-stage least-squares method. The results confirm the important influence of renewables and non-renewables as well as capital and labor force on GDP in developed countries. Also both GDP and real oil price play an important role in renewable energy consumption. Our findings suggest that energy planners and policy makers need to increase renewable energy investment to ensure sustainable economic development in future.
Framework for Many to One Machine Translation

The frequent domestic and international exchanges have created an opportunity for machine translation to flourish since human translators cannot cater for the translation demand. However, there is slow pace in the development of machine translation tools using the one (source language) to one (target language) framework. The paper proposes a many (source languages) to one (target language) conceptual framework that will ensure faster and efficient development of machine translation tools using the Interlingua rule based machine translation approach. The many to one framework make use of shallow structure: lexical similarity and syntactic similarity and deep structure: a unique universal intermediate representation language. A formal computational grammar will be needed and is exemplified by use of two under resourced languages: Swahili and Kikamba. Evaluation model is proposed at
Knowledge Acquisition Mechanisms during the New Technology Implementation Process of Malaysia’s Automotive Engineering Support Industry

Malaysia’s engineering support industry is crucial in supporting the country’s industrial development because it intergrates into other economic sectors which includes manufacturing, construction, transportation, and the primary industry. To fulfill the rigorous requirement of original equipment manufacturers (OEMs) for parts and components along with precision engineering service, the players/stakeholders in this industry have begun to upgrade their facilities and adopt new technologies. Besides technology adoption, knowledge is the main advantage of a firm to compete in the turbulence and increasingly complex new business environment. This research aims to explain the specific knowledge acquisition mechanisms used for three knowledge levels as proposed by a few reputable researchers in this field. The data was gathered from a semi-structured interview in two automotive tooling companies in Selangor, Malaysia. Thematic analysis was conducted using NVivo. The results of this study found that among the knowledge acquisition mechanisms for declarative knowledge mentioned by the interviewees are basic training, intellectual capital, pre-departure training, and instructor manual. The knowledge acquisition mechanisms for procedure knowledge includes external OJT, hiring external expert, related working experience, local training, benchmarking, and personal observation. Finally, the knowledge acquisition mechanisms for conditional knowledge include continuous improvement, learning by doing, project review, and trial and error. Keywords—knowledge sharing; new technology implementation; engineering support industry; declarative knowledge, procedural knowledge, and conditional knowledge
The Import and Export Business in Plastids: Transport Processes across the Inner Envelope Membrane1

Plastids are the characteristic organelles of plant and algae cells and are, like mitochondria, of endosymbiontic origin. They can be traced back to a single cyanobacterial ancestor that was engulfed by a primitive protist about 1.5 billion years ago ([Yoon et al., 2004][1]). Higher plants possess
Adoption of Modern Hive Beekeeping Technology: The Case of Kacha-BirraWoreda, Kembata Tembaro Zone, Southern Ethiopia

Agricultural Office and LIFT Program, Kembata Tambara Zone, Ethiopia Department of Rural Development and Agricultural Extension, College of Agriculture, Wolaita Sodo University, P. O. Box 138, Wolaita Sodo, Ethiopia Department of Environmental Science, Wolaita Sodo University, P. O. Box 138, Wolaita Sodo, Ethiopia Department of Climate Change and Sustainable Agriculture, Hawassa University, Hawassa, Ethiopia
A prominent organizational feature of the brain is the clustering of cells with similar properties. It is thought that some brain functions depend on this organization. Is this so?

The brain is not a masala of cells. Brodmann’s work boosted the idea that the brain is composed of various regions which have different histological structure and organisation of cells. The cortex is composed of layers, where each layer has distinct cell types and organisation. These cortical layers and regions have distinct functions. For example, in Fig. 1, Brodmann’s area 17, the striate area, is responsible for basic visual processing, while Area 4, the giant pyramidal area, is responsible for driving motor activity (Brodmann, 2007).
Multi-Temperature Heat Pump with Cascade Compressor Connection

Object of the study is a multifunctional heat pump with several evaporators and condensers designed for simultaneous provision of technological processes with heat and cold. The aim of the work is the development and study of the scheme for this type of heat pumps, which ensures minimum irreversibility in the "compressor-gas coolers" chain, without the use of adjustable ejectors installed after evaporators and used as flow mixers. Obtained technical solution ensures the stabilization of heat pump coefficient of performance (COP) and prescribed thermal regimes of heat exchangers at a variable flow rate of the refrigerant. The novelty of the elaboration is inclusion of a compressor of the first stage with a serially connected intermediate heat exchanger and a control valve that are located before the compressor inlet of the second stage of the heat pump, which allows establishing rational pressure after the first stage of compressors. A scheme for the temperature regulation at the inlet of first stage compressors by regulating the flow through the primary circuits of the recuperative heat exchangers has been proposed. Control system of first stage compressor allows providing the required modes of operation of the heat pump. Exergetic analysis of the sections of the hydraulic circuit of heat pump located between the evaporators and gas coolers established that reduction of irreversible losses in the heat pump could be ensured due to optimal choice of the superheat value of gas after the evaporators.
Reactive Oxygen Species Are Involved in Plant Defense against a Gall Midge

Reactive oxygen species (ROS) play a major role in plant defense against pathogens, but evidence for their role in defense against insects is still preliminary and inconsistent. In this study, we examined the potential role of ROS in defense of wheat ( Triticum aestivum ) and rice ( Oryza sativa ) against Hessian ﬂy ( Mayetiola destructor ) larvae. Rapid and prolonged accumulation of hydrogen peroxide (H 2 O 2 ) was detected in wheat plants at the attack site during incompatible interactions. Increased accumulation of both H 2 O 2 and superoxide was detected in rice plants during nonhost interactions with the larvae. No increase in accumulation of either H 2 O 2 or superoxide was observed in wheat plants during compatible interactions. A global analysis revealed changes in the abundances of 250 wheat transcripts and 320 rice transcripts encoding proteins potentially involved in ROS homeostasis. A large number of transcripts encoded class III peroxidases that increased in abundance during both incompatible and nonhost interactions, whereas the levels of these transcripts decreased in susceptible wheat during compatible interactions. The higher levels of class III peroxidase transcripts were associated with elevated enzymatic activity of peroxidases at the attack site in plants during incompatible and nonhost interactions. Overall, our data indicate that class III peroxidases may play a role in ROS generation in resistant wheat and Different The determined after when the larvae had either or pupated. Ten were tested for each H 2 O 2 for each Each test repeated three Ten larvae were reared in medium containing no H 2 at same for each and were used as controls.
Thunken, T and Baldauf, SA and Bersau, N and Frommen, JG and Bakker, TCM (2019)Parasite-induced colour alteration of intermediate hosts

Parasites with complex life cycles often alter the phenotypic appearance of their intermediate hosts in order to facilitate ingestion by the final host. However, such manipulation can be costly as it might increase ingestion by less suitable or dead-end hosts as well. Species-specific parasitic manipulation is a way to enhance the transmission to suitable final hosts. Here, we experimentally show that the altered body colouration of the intermediate host Gammarus pulex caused by its acanthocephalan parasite Pomphorhynchus laevis differently affects predation by different fish species (barbel, perch, ruffe, brown trout and two populations of three-spined stickleback) depending on their suitability to act as final host. Species that were responsive to colour manipulation in a predation experiment were more susceptible to infection with P. laevis than unresponsive species. Furthermore, three-spined stickleback from different populations responded to parasite manipulation in opposite directions. Such increased ingestion of the intermediate host by preferred and suitable hosts suggests fine-tuned adaptive parasitic manipulation and sheds light on the ongoing evolutionary arms race between hosts and manipulative parasites.
University of Birmingham Lower Limb Rehabilitation Using Patient Data

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A Gene Regulatory Network Model for Cell-Fate Determination during Arabidopsis thaliana Flower Development That Is Robust and Recovers Experimental Gene Expression Profiles

Flowers are icons in developmental studies of complex structures. The vast majority of 250,000 angiosperm plant species have flowers with a conserved organ plan bearing sepals, petals, stamens, and carpels in the center. The combinatorial model for the activity of the so-called ABC homeotic floral genes has guided extensive experimental studies in Arabidopsis thaliana and many other plant species. However, a mechanistic and dynamical explanation for the ABC model and prevalence among flowering plants is lacking. Here, we put forward a simple discrete model that postulates logical rules that formally summarize published ABC and non-ABC gene interaction data for Arabidopsis floral organ cell fate determination and integrates this data into a dynamic network model. This model shows that all possible initial conditions converge to few steady gene activity states that match gene expression profiles observed experimentally in primordial floral organ cells of wild-type and mutant plants. Therefore, the network proposed here provides a dynamical explanation for the ABC model and shows that precise signaling pathways are not required to restrain cell types to those found in Arabidopsis, but these are rather determined by the overall gene network dynamics. Furthermore, we performed robustness analyses that clearly show that the cell types recovered depend on the network architecture rather than on specific values of the model’s gene interaction parameters. These results support the hypothesis that such a network constitutes a developmental module, and hence provide a possible explanation for the overall conservation of the ABC model and overall floral plan among angiosperms. In addition, we have been able to predict the effects of differences in network architecture between Arabidopsis and Petunia hybrida.
Content-based Image Retrieval System for Medical Domain Using Spatial Color and Texture Histograms

—Indexing and retrieving are two important tasks for color image databases. These tasks are possible when using the histogram as an efficient technique for content-based image retrieval domain. In this paper, a content-based image retrieval system that can be used in the medical domain is presented. The system is using an original combination of two types of histograms: a spatial color histogram and a texture histogram based on the Local Binary Pattern descriptor. Both histograms are computed in the HVC color space. The computation of the binary code associated to a Local Binary Pattern descriptor is made in an original manner using the NBS distance instead of using a simple difference between colors’ components.
REFINE2: A tool to evaluate real-world performance of machine-learning based effect estimators for molecular and clinical studies

Data-adaptive (machine learning-based) eﬀect estimators are increasingly popular to reduce bias in high-dimensional bioinformatic and clinical studies (e.g. real-world data, target trials, -omic discovery). Their relative statistical eﬃciency (high power) is particularly invaluable in these contexts since sample sizes are often limited due to practical and cost concerns. However, these methods are subject to technical limitations that are dataset speciﬁc and involve computational trade-oﬀs. Thus, it is challenging for analysts to identify when such methods may oﬀer beneﬁts or select amongst statistical methods. We present extensive simulation studies of several cutting-edge estimators, evaluating both performance and computation time. Critically, rather than use arbitrary simulation data, we generate synthetic datasets mimicking the observed data structure (plasmode simulation) of a real molecular epidemiologic cohort. We ﬁnd that machine learning approaches may not always be indicated in such data settings, but that performance is highly context dependent. We present a user-friendly Shiny app REFINE2 (Realistic Evaluations of Finite sample INference using Eﬃcient Estimators) that enables analysts to simulate synthetic data from their own datasets and directly evaluate the performance of several cutting-edge algorithms in those settings. This tool may greatly facilitate the proper selection and implementation of machine-learning-based eﬀect estimators in bioinformatic and clinical study contexts.
A Holistic Robust Motion Control Framework for Autonomous Platooning

Safety is the foremost concern for autonomous platooning. The vehicle-to-vehicle (V2V) communication delays and the sudden appearance of obstacles will trigger the safety of the intended functionality (SOTIF) issues for autonomous platooning. This research proposes a holistic robust motion controller framework (MCF) for an intelligent and connected vehicle platoon system. The MCF utilizes a hierarchical structure to resolve the longitudinal string stability and the lateral control problem under the complex driving environment and time-varying communication delays. Firstly, the H-infinity feedback controller is developed to ensure the robustness of the platoon under time-varying communication delay in the upper-level coordination layer (UCL). The output from UCL will be delivered to the lower-level motion-planning layer (LML) as reference signals. Secondly, the model predictive control (MPC) algorithm is implemented in the LML to achieve multi-objective control, which comprehensively considers the reference signals, the artificial potential field, and multiple vehicle dynamics constraints. Furthermore, three critical scenarios are co-simulated for case studies, including platooning under time-varying communication delay, merging, and obstacle avoidance scenarios. The simulation results indicate that, compared with single-structure MPC, the proposed MCF can offer a better suppression on position error propagation, and get improvements on maximum position error in the three scenarios by 19.2%, 59.8%, and 15.3%, respectively. Lastly, the practicability and effectiveness of the proposed MCF are verified via the hardware-in-the-loop experiment. The average conducting time of the proposed method on the Speedgoat real-time target machine is 1.1 milliseconds, which meets the real-time requirements.