Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrodeposited nanoparticles: properties and photocatalytic applications

The work presented in this thesis reports on fundamental studies into electrodeposition of gold and silver nanoparticulate spheroids on a conducting substrate, Fluorine-doped tin-oxide, and the manipulation of the electrodeposition conditions in order to influence and control the size and surface concentration of spheroids. Methods to control the deposition included chemical modification of the surface with an adsorbed monolayer of 3-aminopropyldimethylmethoxysilane, and manipulation of the potential pulse scheme, especially using a double pulse 'nucleation and growth' approach. The optimised method for production of silver and gold nanoparticulate surfaces was utilised to selectively create surfaces that yield strong surface enhanced Raman scattering (SERS) enhancements, as well as metal enhanced fluorescence. These enhancements have been quantified using the probe molecules Trans-1,2-bis(4-pyridyl)ethylene (BPE) and [Os(bpy)2Qbpy]2+ respectively (where bpy is 2,2’-bipyridyl and Qbpy is 2,2’:4,4’’:4’4’’-quarterpyridyl). Spontaneously formed, densely packed monolayers of [Os(bpy)2PIC]2+ have been formed on fluorine-doped tin-oxide (FTO) electrodes, and films of [Os(bpy)2Qby]2+ have been formed on silver nanoparticulate decorated FTO (where bpy is 2,2’-bipyridyl, PIC is 2-(4-carboxyphenyl)imidazo[4,5- f][1,10]phenanthroline, and Qbpy is 2,2’:4,4’’:4’4’’-quarterpyridyl). The quenching mechanism of the polyoxotungstate anion α-[S2W18O62] (POW) on the two osmium polypyridyl complexes in solution has been identified by analysis of the Stern-Volmer plots. The quenching of monolayers of these complexes by POW, coupled to the electrochemical regeneration of the ground state osmium complex by potential application at the FDTO electrode, has been used to photo-catalytically reduce methyl viologen. Finally a wireless gold bipolar electrode in a microchannel, whose potential is floating and managed by exerting potential control over the electrolyte solution rather than individual electrodes, has been used as the basis for an electrochemiluminescent DNA microsensor. The function of the DNA microsensor has been optimised to maximise signal intensity by altering the ECL solution, and by manipulating the pathway by which the ECL reaction proceeds. DNA binding has been detected based on catalysis of the oxygen reduction reaction (ORR) at (DNA linked) platinum nanoparticles. The ORR can be replaced with other reduction reactions to detect other species such as anthraquinones. The possibility of using this device for quantitative sensing of both DNA and other species is discussed.
A Performance Measurement and Analysis Method for Software-Defined Networking of IoV

Internet of Vehicles (IoV), which plays a significantly important role in smart future cities, has become current hot research topics. However, the high heterogeneous nature of IoV has brought many new challenges such as low network performance and difficult network management for IoV. Software-defined networking enables the efficient solution of these problem. This article studies the measurement and analysis technology for software-defined networking of IoV. A new software-defined networking-based IoV heterogeneous networking measurement framework is proposed to build software-defined networking of IoV. We propose a performance measurement and analysis method to measure and characterize its performance. The performance indexes and measure methods about the delay, loss, throughput, delay jitter is in detail derived. The switch selection mechanism is proposed to establish optimal measurement points of advantage. The packet sampling process is presented to quickly obtain the needed measurement information from massive traffic flows. To validate our measurement method and fairly characterize its measurement performance for different controllers, we conduct massive simulation experiments to systematically analyze and compare current famous controllers. In such a case, we provide more comprehensive, systematic measurement analysis for application in software-defined networking of IoV. Experiments results show that our measurement approach is feasible and effective.
Design Methodology for Industrial Internet-of-Things Wireless Systems

The ubiquity foreseen by the Internet-of-Things (IoT) and powered by the 5G advancements has motivated research on wireless solutions for critical applications, in particular, Industrial IoT (IIoT). Nevertheless, there is little or no research on a unified design methodology for IIoT that tackles the conflicting wireless system performances of Power, Latency, and Reliability (PLR). Obtaining such a framework is vital for empowering further development and fair comparison in future IIoT designs. Thereby, this paper presents a novel design methodology to tackle PLR trade-off in IIoT Wireless Systems (IIoT-WS). This new methodology uses a meet-in-the-middle system approach to design an entire PLR RF system, and a custom Multiple-Criteria Decision Analysis (MCDA) to help decide the best design variables that are both resource-efficient and PLR-balanced for a given application. Finally, to quantify the methodology for critical wireless systems, a lab-demonstrator for automotive application is designed and its performance compared to other wireless systems standards.
DEVS-based Modeling Methodology for Cybersecurity Simulations from a Security Perspective

Security administrators of companies and organizations need to come up with proper countermeasures against cyber-attacks considering infrastructures and security policies in their possession. In order to develop and verify such countermeasures, the administrators should be able to reenact both cyber-attacks and defenses. Simulations can be useful for the reenactment by overcoming its limitations including high risk and cost. If the administrators are able to design various scenarios of cyber-attacks and to develop simulation models from their viewpoints, they can simulate desired situations and observe the results more easily. It is challenging to simulate cyber-security issues, because there is lack of theoretical basis for modeling a wide range of the security field as well as pre-defined basic components used to model cyber-attacks. In this paper, we propose a modeling method for cyber-security simulations by developing a basic component and a composite model, called Abstracted Cyber-Security Unit Model (ACSUM) and Abstracted Cyber-security SIMulation model (ACSIM), respectively. The proposed models are based on DEVS(Discrete Event systems Specification) formalism, a modeling theory for discrete event simulations. We develop attack scenarios by sequencing attack behaviors using ACSUMs and then model ACSIMs by combining and abstracting the ACSUMs from a security perspective. The concepts of ACSUM and ACSIM enable the security administrators to simulate numerous cyber-security issues from their viewpoints. As a case study, we model a worm scenario using ACSUM and simulate three types of simulation models based on ACSIM from a different security perspective.
Wideband Vertically Polarized Antenna With Endfire Radiation for 5G Mobile Phone Applications

This letter presents a wideband slotted substrate integrated waveguide (SIW) antenna for millimeter-wave (mm-wave) fifth-generation (5G) mobile handset applications. The antenna is vertically polarized and has a small clearance of 3.3 mm. To realize a wide operating bandwidth, two sets of vias are employed to perform a change in SIW height. Furthermore, a pair of U-shaped slots is used in both top and bottom faces of SIW to improve impedance matching and front-to-back radiation ratio. The antenna achieves a measured −6 dB bandwidth of 35.7% (23.4–33.6 GHz) and a −10 dB bandwidth of 17.4% (26.2–31.2 GHz). The beamforming capability of the antenna array is investigated. The antenna array has good scanning performance and achieves large spatial coverage.
Decoding Binary Linear Codes Over Channels With Synchronization Errors

Time synchronization is crucial for the safe and reliable operation of the fifth generation (5G) network, especially for applications requiring ultra-reliable low-latency data transmissions. The time synchronization problem, however, becomes increasingly challenging in high-mobility scenarios because the channel conditions, e.g., the multipath delay spread may vary rapidly. While there exist numerous works on the design of efficient channel decoding algorithms, decoding linear codes such as polar codes in the presence of synchronization errors is a less-explored topic. In this paper, we aim to fill this void and develop a systemic approach to decode general binary linear codes over binary symmetric channels with synchronization errors in which the lack of synchronization is modeled as the deletion channel model. The maximum likelihood (ML) decoding problem for binary linear codes over deletion channels is first formulated as a nonlinear optimization problem, in which a set of linear constraints are employed to characterize the input-output relationship of a deletion channel. It turns out that both the objective function and the constraints of this optimization problem are nonlinear, which poses significant challenges against the design of efficient decoding algorithms. As a remedy, we first replace the nonlinear objective function of this optimization problem via a lower bound. And we prove this lower bound is a linear function in the special case that the input is binary. We then apply the linear programming (LP) relaxation approach to obtain an approximate solution to the proposed nonlinear optimization problem. An adaptive branch-and-cut decoding algorithm has also been developed by making use of the ML-certificate property of the LP decoder for deletion channel. It is seen through simulation studies that the proposed decoding algorithm can achieve close-to-optimal bit error rate (BER) decoding performance at moderate computational complexity.
Research on Interactive Design of Social Interaction Training APP for Children with Autistic Spectrum Disorder (ASD) Based on Multi-modal Interaction

A number of studies have found that the difficulty in social interactive behaviors and recognize items are two core syndromes of Autistic Spectrum Disorder (ASD) children. Previous research has found that ASD children paid more attention to robots comparing to people.Intervention programs with robots as instructors or partners were also proved to be effective in improving ASD children’s social skills.Yet, few studies find robot intervention works in ASD children training.So research explore the possibility of apply such intervention programs into product design.The present study aimed at involving an animated character of robot in an application (APP) of intervention program to facilitate ASD children’s learning of social interactive skills.In order to achieve the goal, a training system based on sensory integration training was established by the design software of Sketch.Augmented Reality (AR) technology was used to create a multi-modal interactive environment of the APP.The present study is among the first attempt to apply sensory integration training in APP design, aiming at promoting social and cognitive performance in ASD children.
Optimizing Crop Load for New Apple Cultivar: “WA38”

Crop load management is growing increasingly important as a factor related to biennial tendencies, post-harvest disorders, and inconsistent fruit quality in apples like “Honeycrisp”. Washington State University released a new apple cultivar, called “WA38”, in 2017. Limited literature is available about the productive characteristics of this new cultivar. An experimental trial evaluating the effect of crop load on leaf area, fruit quality, mineral composition, and return bloom of “WA 38” was conducted for two consecutive years (2017 and 2018) to determine an optimal crop load. Trees were trained as a spindle and grafted on Malling-9 Nic29 (Nic29) rootstocks. Crop loads were adjusted to 2, 4, 6, and 8 fruits/cm2 of trunk cross-sectional area (TCSA). Crop load had a significant effect on production, with yields ranging from 28 to 83 MT/ha in 2017. Fruit quality was impacted by increasing crop load, with a reduction in fruit weight, soluble solid content, firmness, dry matter, titratable acidity, and a delay in maturity. Leaf-to-fruit ratios were higher in lower crop loads. Relatively consistent flower bud formation was seen at the 6 and 8 fruits/cm2 categories. A possible threshold for optimal fruit quality and consistent bloom was identified around 6 fruits/cm2 TCSA.
THE OPTIMIZATION OF TRUCKS FLEET SCHEDULE IN VIEW OF THEIR INTERACTION AND RESTRICTIONS OF THE EUROPEAN AGREEMENT OF WORK OF CREWS

The importance of compliance with the schedule of work of road trains on the highway transport network of the European Union is shown. The possible options for work and rest modes for truck drivers on international routes have been analyzed. A model for optimizing the truck fleet operation plan has been developed. This model has two levels, that is, the general graph contains subgraphs designed with incompatible vertices to determine the active and shortest schedule. Each of the subgraphs reflects alternative routes and schedules of a truck. The model also includes restrictions on the total cycle time and active period duration of available unloading points. To find the shortest schedule, integer programming with a guaranteed optimal solution was applied. Testing of the proposed algorithm was performed for the example of serving orders for international freight transportation between the cities of Ukraine, Poland, and the Czech Republic. The active schedule is based on the criterion of the minimum of the total duration of drivers’ work. The results obtained are valid, consistent with the rules of the European Agreement. They indicate that the choice of the best schedule for a single car on a unitary route is not the best solution for the entire truck fleet and the entire flow of orders.
Relationship between Resilience and Quality of Life in Patients with Fear of Hypoglycemia: The Mediating Effects of Anxiety and Depression

Background: Fear of hypoglycemia is an important problem in individuals with diabetes and could produce a negative impact on blood glucose control and quality of life in individuals with type 1 diabetes. Aim: To analyze (1) the associations among resilience, diabetes-related quality of life, and anxiety and depression in patients with type 1 diabetes with fear of hypoglycemia and (2) whether anxiety and depression mediate the relationship between resilience and quality of life. Design: A non-experimental, descriptive correlational design was used. Methods: Participants were 30 patients with type 1 diabetes with fear of hypoglycemia. Data were collected using several questionnaires administered between September 2019 and March 2020. Results: Resilience played a significant role in the anxiety and depression that accompanies diabetes. Mediation analysis was performed to assess whether the association between resilience and quality of life was mediated by anxiety and depression in series. The results show that the effect of resilience was mainly mediated by anxiety but not by depression. Conclusions: This study provides further evidence that high resilience could be a protective factor against the development of psychological symptomatology, which has a high prevalence in chronic conditions such as diabetes and can improve quality of life. Impact: Our study addresses the relationship between the positive psychological characteristic of resilience and anxiety, depression, and quality of life and the association between these variables. The results indicate that resilience has a positive impact on quality of life in people with type 1 diabetes who experience fear of hypoglycemia. Moreover, health professionals who provide care to these individuals should consider implementing programs to build resilience.
LINKING SOIL BACTERIAL COMMUNITY AND CROP YIELD IN A WHEAT (TRITICUM AESTIVUM L.) - ALFALFA (MEDICAGO SATIVA L.) INTERCROPPING SYSTEM

Diverse intercropping has been utilized to improve crop productivity on agricultural fields. Beneficial plant rhizobacteria are associated with plant root surface and may increase yield. In the research, the bacterial communities in soils of monoculture and intercropping wheat and alfalfa (cv. Winter star) were studied using MiSeq sequencing of the 16S rDNA gene. Intercropping pattern improved wheat yield in the field. The dominant taxonomic groups in the rhizosphere soil were Proteobacteria, Acidobacteria, Bacteroidetes, Actinobacteria, Planctomycetes, Chloroflexi and Nitrospirae and these were present across 4 samples. Intercropping significantly affected the diversity and composition of bacterial communities compared to monoculture. The enrichment of bacterial communities such as the populations of Rhizobiales, Burkholderiales, Pseudomonales and Bacillus could be important factors contributing to yield increases in intercropping wheat. In addition, some populations, such as Sphingomonadals and Xanthomonadales, indicated contrary changes, their diversity declined in intercropping systems, meaning that these bacterial populations were affected by cropping patterns.
Heuristic Gait Learning of Quadruped Robot Based on Deep Deterministic Policy Gradient Algorithm

The gait control of the quadruped robot has always been a hot topic in the field of robot research. At present, the traditional control methods have many limitations such as low intelligence and poor autonomy. With the development of artificial intelligence technology, the application of reinforcement learning to the quadruped robot autonomous learning strategy provides a promising solution. Deep deterministic policy gradient (DDPG) algorithm has achieved good performance in continuous control tasks, but such value-based reinforcement learning algorithms have the problem of too high epoch estimates when performing function approximation, then reached a bad strategy actually. In order to solve the above-mentioned problem, this paper proposed a heuristic gait learning method for quadruped robot based on DDPG, inspired by the Double Q-learning algorithm, two independent critics were used to select the smaller value to update the parameters. The Open AI Gym platform was used for experimental verification, which proved that the proposed improved DDPG algorithm had better performance.
Generalisation behaviour of predators toward warning signals displayed by harmful prey: answers from a videogame played by humans

The persistence of several warning signals in sympatry is a puzzling evolutionary question because selection favours convergence of colour patterns among toxic species. Such convergence is shaped by predators’ reaction to similar but not identical stimulus, i.e. generalisation behaviour. However, studying generalisation behaviour in complex natural communities of predators is challenging, and is thus generally limited to simple variations of prey colour patterns. Here, we used humans as surrogate predators to investigate generalisation behaviours on two prey communities with different level of warning signals complexity. Humans’ generalisation capacities were estimated using a computer game simulating a simple (4 morphs) and a complex (10 morphs) community of defended (associated with a penalty) and palatable butterflies. Colour patterns used in the game are actually observed in natural populations of the defended butterflies H. numata, and generalisation behaviour of natural predator’s communities on these colour patterns have previously been investigated in the wild, allowing direct comparison with human behaviour. We investigated human predation behaviour by recording attack rates on the different defended and palatable colour patterns, as well as player survival time (i.e. score). Phenotypic similarity among the different colour patterns was precisely quantified using a custom algorithm accounting for both colour and pattern variations (CPM method). By analysing attack behaviours of 491 game players, we found that learning was more efficient in the simple prey community. Additionally, profitable prey gained protection from sharing key visual features with unprofitable prey in both communities while learning, in accordance with natural predator behaviours. Moreover, other behaviours observed in natural predators, such as colour neophobia, were detected in humans and shaped morph vulnerability during the game. Similarities between our results in humans and the reaction of natural predator communities to the same colour patterns validate our video-game as a useful proxy to study predator behaviour. This experimental set-up can thus be compared to natural systems, enabling further investigations of generalisation on mimicry evolution.
Didactic Transposition On The Concept Of Central Angle And Circumferential Angle In Junior High School

A study was conducted to analyze the didactic transposition process on the concept of central and circumferential angles in junior high school. This research is a hermeneutic phenomenology research. Geometry textbooks, the 2013 curriculum and junior high school mathematics textbooks are the data sources in this study. Descriptive analysis is used to analyze the didactic transposition process. The results of this study indicate that there is no structural change in the concept of the central angle and the circumferential angle from scholarly mathematics to school mathematics. But there is a change in form (content) in the concept of the central angle and the circumferential angle from scholarly mathematics to school mathematics. In school mathematics, the concepts presented are contextual, concrete and simple. Whereas in scholarly mathematics, the concepts presented are abstract. This change in form adjusts the level of cognitive development of students.
A Work Project, presented as part of the requirements for the Award of a Master Degree in Finance from the NOVA – School of Business and Economics. The impact of Microfinance on Women Empowerment in the Egyptian Society

This paper demonstrates results from a sample of 1168 randomly picked women from one of the leading microfinance institutions in Egypt: Tasaheel. This study tests whether microfinance helped women empowerment through increasing their income levels. The results show that loans increase women’s income on average. The sample shows that microfinance’s impact is unequal, helping the poor increase their revenue more. Socio-economic conditions affect the extent to which women benefit from the loans through their effect on the cost of debt. The cost of debt has a negative impact on the change in income.
Genetic variation for micronutrients and study of genetic diversity in diverse germplasm of rice

An experiment was carried out to explore high iron (Fe) and zinc (Zn) donors, and to study the extent of genetic divergence based on such micronutrients and agro-morphological traits including seed yield in a set of 92 diverse germplasm lines of rice. Grain Fe (8.3-52.15ppm) and Zn content (3.0-52.7ppm) revealed wide variation among the germplasm. P44 mutant selection1, ORCZ 75-3-1, Basudha, Malliphulajhuli, Tikimahsuri and Nikipankhia were rich in both Fe and Zn. P44 mutant selection1 and ORCZ 75-3-1 had high yield potential while above local land races were poor yielding. The total set of genotypes were grouped into 12 distinct clusters. Jabaphulla, Parijat and Sakaribanki emerged as most divergent genotypes, but moderate low in Fe and Zn content. Interestingly, most of the local land races and the breeding lines clubbed into two separate distinct clusters respectively. The Fe and Zn dense genotypes identified above belong to the same distinct single cluster that showed high Fe and Zn content. Hence, such donors may serve as valuable material for Fe and Zn biofortification breeding.