Miracle-dz/UniFAR-FTUs huggingface dataset:
A non-linear approach to modelling and control of electrically stimulated skeletal muscle

This thesis is concerned with the development and analysis of a non-linear approach to modelling and control of the contraction of electrically stimulated skeletal muscle. For muscle which has lost nervous control, artificial electrical stimulation can be used as a technique aimed at providing muscular contraction and producing a functionally useful movement. This is generally referred to as Functional Electrical Stimulation (FES) and is used in different application areas such as the rehabilitation of paralysed patient and in cardiac assistance where skeletal muscle can be used to support a failing heart. For both these FES applications a model of the muscle is essential to develop algorithms for the controlled stimulation. For the identification of muscle models, real data are available from experiments with rabbit muscle. Data for contraction with constant muscle length were collected from two muscle with very different characteristics. An empirical modelling approach is developed which is suitable for both muscles. The approach is based on a decomposition of the operating space into smaller sub-regions which are then described by local models of simple, possibly linear structure. The local models are blended together by a scheduler, and the resulting non-linear model is called a Local Model Network (LMN). It is shown how a priori knowledge about the system can be used directly when identifying Local Model Networks. Aspects of the structure selection are discussed and algorithms for the identification of the model parameters are presented. Tools of the analysis of Local Model Networks have been developed and are used to validate the models. The problem of designing a controller based on the LMN structure is discussed. The structure of Local Controller Networks is introduced. These can be derived directly from Local Model Networks. Design techniques for input-output and for state feedback controllers, based on pole placement, are presented. Aspects of the generation of optimal stimulation patterns (which are defined as stimulation patterns which deliver the smallest number of pulses to obtain a desired contraction) are discussed, and various techniques to generate them are presented. In particular, it is shown how a control structure can be used to generate optimal stimulation patterns. A Local Controller Network is used as the controller with a design based on a non-linear LMN model of muscle. Experimental data from a non-linear heat transfer process have been collected and are used to demonstrate the basic modelling and control principles throughout the first part of the thesis.
Culvert Roughness Elements for Native Utah Fish Passage: Phase I

Native fishes have become an increasingly important concern when designing fish passable culverts. Many operational culverts constrict waterways which increase velocities and prevent upstream passage of small fish species. The current method to ensure fish passage is to match the average cross sectional velocity to the sustained swim speed of the fish. This study investigates the passage rates of leatherside chub (Lepidomeda aliciae) and speckled dace (Rhinichthys osculus) at three sites (an arch culvert with substrate bottom, box culvert with bare bottom, and a stream section with no culvert) located on Salina Creek near Salina, UT. It was found that fish were able to pass through all of the sites. However, fish were able to take advantage of the habitat within the culvert that had a substrate bottom more effectively than within the culvert that had no substrate within the barrel. This was reflected in population density estimates at each of the three test sites for each species. It was also found that the substrate at the arch culvert and stream sites scaled with the fish measured in this study. The D50 and D84 were 44 and 205 mm at the arch culvert site and 26 and 126 mm at the stream site. The average fish length was 76 mm for the chub and 64 mm for the dace. It is believed that placing substrate that scales with fish length within the culvert will provide enough velocity heterogeneity to allow the fish to successfully pass.
Single-nucleotide polymorphisms in one-carbon metabolism genes, Mediterranean diet and the risk of pre- and postmenopausal breast cancer

Background: One-carbon metabolism pathway could interfere with the carcinogenesis of breast cancer (BC). Dietary pattern plays an important role in one-carbon metabolism linking the combination of dietary micronutrients. Methods: We assessed associations between single-nucleotide polymorphisms (SNPs) of one-carbon metabolism, adherence to Mediterranean dietary pattern (MDP) and BC risk from a case-control study (818 cases, 935 controls) among Chinese female population. The genotyping of 10 SNPs in seven one-carbon metabolism-related genes (MTHFD1, MTRR, MAT2B, CDO1, FOLR1, UNG2, ADA) were performed. Dietary intake measurements were assessed by a validated food-frequency questionnaire. Gene-diet interactions were analyzed. Results: No evidence demonstrated SNPs of one-carbon metabolism or their haplotypes were associated with BC risk. High adherence to the Mediterranean dietary pattern decreased the risk of breast cancer among post- but not premenopausal women and the association was influenced by the SNPs genotype, with the increasing number of variant allele in MTHFD1 (rs11627387), MTHFD1 (rs2281603), MTRR (rs16879334), MTRR (rs2287780), MAT2B (rs4869087), FOLR1 (rs10501409), UNG2 (rs231622) and ADA (rs244072). The protective effect against BC risk from high adherence to the MDP was gradually weakened and disappeared. For MTHFD1 (rs8003567) and CDO1 (rs34869) genotypes, women with homozygous were less affected by adherence to the MDP than to women who with heterozygotes. No significant gene-diet interactions were observed.Conclusions: SNPs of one-carbon metabolism genes modify the effect of high adherence to MDP against BC risk in Chinese women, as potential effect modifiers. Genetic variants may influence the association between diet and BC risk.
Experimental Dataset of Electrochemical Efficiency of a Direct Borohydride Fuel Cell (DBFC) with Pd/C, Pt/C and Pd Decorated Ni–Co/rGO Anode Catalysts

Dataset includes Direct Borohydride Fuel Cell (DBFC) impedance and polarization test in anode with Pd/C, Pt/C and Pd decorated Ni–Co/rGO catalysts. In fact, different concentration of Sodium Borohydride (SBH), applied voltages and various anode catalysts loading with explanation of experimental details of electrochemical analysis are considered in data. Voltage, power density and resistance of DBFC change as a function of weight percent of SBH (%), applied voltage and amount of anode catalyst loading that are evaluated by polarization and impedance curves with using appropriate equivalent circuit of fuel cell. Can be stated that interpretation of electrochemical behavior changes by the data of related cell is inevitable, which can be useful in simulation, power source investigation and depth analysis in DB fuel cell researches.
Radio Frequency Interference from Near-Earth Satellites

A pessimistic statistical model was developed for predicting the extent of radio frequency interference (RF1). Based on the assumptions underlying the model, DSN S-band operations can expect one RF1 interruption every 4.1 days, with the average incident lasting 24 s. This implies that 52 or more such satellites, with uncorrelated orbital trajectories, will cause in excess of 5 min of RF1 per day at a DSN station.
How do those affected by a disaster organize to meet their needs for justice? Campaign strategies and partial victories following the Grenfell Tower fire

Previous research has shown that disasters often involve a sense of injustice among affected communities. But the process through which ‘disaster communities’ organise to confront such injustices have not been investigated by social psychology. This study addresses this gap by examining how community members impacted by the Grenfell Tower fire self-organized to demand justice in response to government neglect. Thematic analysis of interviews with fifteen campaigners helped us to understand the shared responses of those involved in support campaigns following the fire. Campaigners aimed to: overcome injustice against the government inactions in the aftermath of the fire; empower their community against government neglect; create a sense of community for people who experienced injustice. Community members created a petition calling on the government to build trust in the public inquiry; they achieved their goals with the participation of people from wider communities. We found that reaching out to allies and building shared social identity among supporters were two main ways to achieve campaign goals. The study suggests ways that ‘disaster communities’ can be sustained after the disaster to form the basis of effective collective action. Specifically, shared social identity is a key mechanism for communities who are affected by a disaster, enabling them to act as one when they seek justice as well as overcome the effects of disaster.
Fixed-wing state level HIL via factor graph incremental smoothing

Many robotics problems such as simultaneous localization and mapping (SLAM) and bundle adjustment (BA) can be formulated as a nonlinear least squares graph optimization. In these strategies, each node in the graph represents a robot position or a sensor measurement obtained at that position. Edges represent constraints between these nodes. The first part of the problem known as front-end is generating the graph. The second part, known as back-end, aims to find a configuration that best explains the constraints usually modeled as error functions. Clearly this is an expensive operation since every movement or measurement adds nodes to the graph that may become optimization hard for limited real-time applications. In order to overcome this problem, an innovative method called incremental smoothing, optimizes only a small subset of the graph nodes, reducing the computational load considerably. Besides, to explore this novel algorithm we propose a state-level hardware-in-the loop (HIL) for a small fixed-wing UAV. It consists of an aerial flight simulator extended with our sensor fusion plugin and the UAV aerodynamic model, an autopilot and a ground control station. MAVLink communications protocol interfaces these modules. Furthermore, we validate our approach with three mission scenarios exploiting different maneuvers ranging from a simple square flight to a much more challenging lawn-mower search pattern. Experiments have shown that the proposed method performed satisfactorily.
Calretinin versus Hematoxylin and Eosin Stain for Diagnosis of Hirschsprung’s Disease; Comparison in Ganglionic, Transitional, and Aganglionic Zones

Objective: To compare the results of calretinin stain with hematoxylin and eosin (H&E) stain for diagnosis of Hirschsprung’s disease. Materials and Methods: A prospective double-blind diagnostic study was done. Hirschsprung’s patients who underwent transanal endorectal pull through (TERPT) surgery between February 2015 and February 2017 were included. The pulled-through specimens were sampled at the ganglionic, transitional, and aganglionic zones. Each specimen was stained with calretinin and H&E. Agreement and kappa analysis were done. Results: Fifty-one Hirschsprung’s patients (153 specimens) were included for analysis. There were 37 males (72.5%) and 14 females (27.5%) with a median age at surgery of four months. Thirty-one specimens showed a negative stain for calretinin (aganglionic bowel) and 33 specimens showed no ganglion cells in the H&E stain. One hundred twenty-two specimens in calretinin stain were consistently positive with ganglionic bowel and 120 specimens in the H&E stain showed ganglion cells. Agreement and Cohen’s kappa coefficient were 97.4% and 0.921 (95% confidence interval 0.845 to 0.997), respectively. Disconcordance was found in four specimens. Three out of four were in the transitional zone. One was in the aganglionic zone, which has no muscular layer attached. (Thirty-six specimens had no muscular layer.) Conclusion: Calretinin stain was found to be comparable with the H&E stain and could be used for diagnosis of Hirschsprung’s disease. In rectal suction biopsy specimen in which the muscular layer was not included, both calretinin and H&E can be used. Keywords: Megacolon, Hematoxylin and eosin (H&E), Calretinin, Rectal suction biopsy (RSB), Full thickness biopsy
Review on Mathematical Approaches of Cancer Cell Invasion at Subcellular Level

Metastasis is a process of cancer cell invasion which is the main cause of death among cancer patients. Invasion of a cancer cell on tissue compartment is initiated by the formation of protrusions known as invadopodia and the degradation of extracellular membrane (ECM) barrier. Invadopodia is one of the subcellular views on a cancer cell formed by several processes including ligand formation, signal transduction, chemotaxis, matrix metalloproteinases (MMPs) up regulation and degradation of ECM proteins. Mathematical approach of the cancer cell invasion based on the hypothesis and illustration of previous studies has been considered in order to understand the vivo dynamics of invasion. This study had been done progressively at tissue and cellular levels in the past decades. Recently, mathematical modelling on the study of cancer cell invasion at subcellular level have received much attention since there is potential on anti-invasion therapies for treating the cancer patients. Here, the reviews of mathematical models on cancer cell invasion at subcellular level are able to extend our knowledge on the fields of mathematical medicine and biology.
Enabling Greater Penetration of Solar Power via the Use of CSP with Thermal Energy Storage

At high penetration of solar generation there are a number of challenges to economically integrating this variable and uncertain resource. These include the limited coincidence between the solar resource and normal demand patterns and limited flexibility of conventional generators to accommodate variable generation resources. Of the large number of technologies that can be used to enable greater penetration of variable generators, concentrating solar power (CSP) with thermal energy storage (TES) presents a number of advantages. The use of storage enables this technology to shift energy production to periods of high demand or reduced solar output. In addition, CSP can provide substantial grid flexibility by rapidly changing output in response to the highly variable net load created by high penetration of solar (and wind) generation. In this work we examine the degree to which CSP may be complementary to PV by performing a set of simulations in the U.S. Southwest to demonstrate the general potential of CSP with TES to enable greater use of solar generation, including additional PV.
Identification and control of induction machines using artificial neural networks

The use of artificial neural networks (ANNs) to identify and control induction machines is proposed. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics, and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Both systems are inherently adaptive as well as self-commissioning. The current controller is a completely general nonlinear controller which can be used together with any drive algorithm. Various advantages of these control schemes over conventional schemes are cited, and the combined speed and current control scheme is compared with the standard vector control scheme. <<ETX>>
Design a platform for providing home-based services concerning: care, safety, comfort and fun

Currently the information about a house is scattered over different websites and stored on different servers on the internet. House owners, inhabitants and renters perceive this to be a problem. Additionally, they often have problems sharing data with third parties in a simple and secure way, without any external applications using their private data without their permission. Besides end-users, several stakeholders are involved in this problem such as service providers and data providers. These different stakeholders need to have a platform where their needs can be met by cooperating with each other to offer the best service possible. The problem that is addressed in this thesis is how to create this platform: to decide which services can be implemented in the platform that will use the end-users’ data, to choose the software architecture and how to solve the trust issue between end-users and the different parties involved.
Commonly used Algorithms in Data Science Along with Internal Logics and Implementations through R Programming

The terms machine learning, deep learning and data science are buzz words now a days. The usage of these techniques with some technologies like R and Python is most common in the industry and academics. The current work is dealing with the inherent logics existing in the algorithms like Classification, Dimensionality reduction and Recommender systems along with the suitable examples. Some of the applications mentioned here like Facebook, Twitter and LinkedIn to exploit the usage of these algorithms in their daily usage. The discussion about online platforms like Amazon, Flipkart are other areas where the recommender systems were most commonly used algorithms. The outcome of the work is the logical things hidden in the usage of the algorithms and the implementation wise which are packages and functions helpful for the implementation of the algorithms. The belief is the work will be helpful for the researchers and academicians in the context of algorithmic perspective and they can extend the work by contributing their thoughts and views on the same work. Unlike in the normal programming, R/Python simplifies the logic of algorithms so that the lines of code and understanding of the problem is bit simple when compared with general programming languages. The work explains the mail respondents related to the allocation of the house by the company as a response to their mail by considering Urban, semi-urban and rural areas of the customers, the income range of the customers also observed in the allocation of the house. The implementations are with R by using classification and the corresponding results were published with the explanation of the values found in the implementation.
Heavy Truck Modeling for Fuel Consumption Simulations and Measurements

Fuel consumption for heavy trucks depends on many factors like roads, weather, and driver behaviour that are hard for a manufacturer to influence. However, one design possibility is the power train configuration. Here a new simulation program for heavy trucks is created to find the configuration of the power train that gives the lowest fuel consumption for each transport task. For efficient simulations the model uses production code for speed and gear control, and it uses exchangeable data sets to allow simulation of the whole production range of engine types, on recorded road profiles from all over the world. Combined with a graphical user interface this application is called STARS (Scania Truck and Road Simulation). The forces of rolling resistance and air resistance in the model are validated through an experiment where the propeller shaft torque of a heavy truck is measured. It is found that the coefficient of rolling resistance is strongly dependent on tire temperature, not only on vehicle speed as expected. This led to the development of a new model for rolling resistance. The model includes the dynamic behaviour of the tires and relates rolling resistance to tire temperature and vehicle speed. In another experiment the fuel consumption of a test truck in highway driving is measured. The altitude of the road is recorded with a barometer and used in the corresponding simulations. Despite of the limited accuracy of this equipment the simulation program managed to predict a level of fuel consumption only 2% lower than the real measurements. It is concluded that STARS is a good tool for predicting fuel consumption for trucks in highway driving and for comparing different power train configurations. The report is available on the Internet: http://www.fs. isy.liu. se/Publications/Lic/01_LIC_924_TS. pdf.
Signal Processing for Active Control

Signal Processing for Active Control sets out the signal processing and automatic control techniques that are used in the analysis and implementation of active systems for the control of sound and vibration. After reviewing the performance limitations introduced by physical aspects of active control, Stephen Elliott presents the calculation of the optimal performance and the implementation of adaptive real time controllers for a wide variety of active control systems. Active sound and vibration control are technologically important problems with many applications. 'Active control' means controlling disturbance by superimposing a second disturbance on the original source of disturbance. Put simply, initial noise + other specially-generated noise or vibration = silence [or controlled noise]. This book presents a unified approach to techniques that are used in the analysis and implementation of different control systems. It includes practical examples at the end of each chapter to illustrate the use of various approaches. This book is intended for researchers, engineers, and students in the field of acoustics, active control, signal processing, and electrical engineering.
Selecting Optimal Access Roads for Mobile Crane in Wind Farm Project

Wind farms, always constructed on sites of uneven terrain or topography. So, mobile crane used to lift and assembly of wind turbine is faced with problem of unpaved access roads which have a negative influence on wind farm construction time. Therefore the selection of the shortest access road routes is essential to minimize wind farm construction time. This paper presents a formulation based on technique of Genetic Algorithms (GA) to find the optimal access roads routes, this formulation consider a good fast tool used for planning the construction process. To verify the efficiency of the proposed formulation, illustrative example has implemented in MAT LAB and results of this example are clarified. [M. Kotb, A. Elhelloty, and M. Shaaba. Selecting Optimal Access Roads for Mobile Crane in Wind Farm Project. Life Sci J 2019;16(6):28-31]. ISSN: 1097-8135 (Print) / ISSN: 2372-613X (Online). http://www.lifesciencesite. com. 5. doi:10.7537/marslsj160619.05.