Miracle-dz/UniFAR-FTUs huggingface dataset:
Labeling of graphs, sumset of squares of units modulo n and resonance varieties of matroids

This thesis investigates problems in a number of different areas of graph theory and its applications in other areas of mathematics. Motivated by the 1-2-3-Conjecture, we consider the closed distinguishing number of a graph G, denoted by dis[G]. We provide new upper bounds for dis[G] by using the Combinatorial Nullstellensatz. We prove that it is NP-complete to decide for a given planar subcubic graph G, whether dis[G] = 2. We show that for each integer t there is a bipartite graph G such that dis[G] > t. Then some polynomial time algorithms and NP-hardness results for the problem of partitioning the edges of a graph into regular and/or locally irregular subgraphs are presented. We then move on to consider Johnson graphs to find resonance varieties of some classes of sparse paving matroids. The last application we consider is in number theory, where we find the number of solutions of the equation x1 + · · · + xk = c, where c ∈ Zn, and xi are all units in the ring Zn. Our approach is combinatorial using spectral graph theory.
Effects of Electroplating Effluents on Growth, Heavy Metals Accumulation and Concentrations in Amaranthus viridis Lin.

Pollution in recent times has become prevalent due to industrial expansion, hence, releasing pollutants into the environment. Thus, this study aimed at investigating the effects of effluents from electroplating companies on growth, heavy metals accumulation and concentrations in Amaranthus viridis. Seeds of A. viridis were obtained from the National Institute of Horticulture, Ibadan. Loam soils were collected from Lagos State University and two samples of electroplating effluents were obtained from Oregun, Lagos. Seeds were sown, nursed, and transplanted in a uniform bucket filled with 5 kg loam soil and transplanted seedlings were treated with Effluent A (5 and 10% conc.) and Effluent B (5 and 10% conc.) and control respectively. Growth parameters such as plant height and so on were measured and plant samples harvested were analyzed for heavy metal concentrations using Atomic Absorption Spectrophotometer. Data collected were subjected to a one-way analysis of variance. Results revealed that Effluents A and B are highly acidic and above discharge limits. Also, the result revealed that 5% conc. of Effluents A and B had more effects on growth (p < 0.05) of A. viridis across the harvests than 10% conc. in relation to control. This result showed that the effluent samples affect the growth rhythms of plants. Results further revealed vigorous accumulation of the heavy metals: Zn (241.66 µg kg–1 ± 0.10 at third harvest in Effluent A: 10%), Cu (68.25 µg kg–1 ± 0.23 at first harvest in Effluent B: 5%), Cr (500 µg kg–1 ± 0.90 in harvests at all concentrations.) and Ni (500 µg kg–1 ± 0.90 at third harvest in Effluent B: 5%) and all these metals are far above the control and permissible limits of WHO/FAO recommendations. From this study, it could be concluded that electroplating effluents had adverse effects on growth and increased metals’ bioaccumulation in A. viridis. Therefore, the treatment of effluents to enhance an eco-friendly environment should be done.
Finite element based solutions of thin-shell problems with a small strain

In this thesis, we consider the deformation of shell structures defined as thin three-dimensional elastic bodies. These can be modelled using a lower-dimensional theory but the governing partial differential equation of thin shells contains fourth-order derivatives which require C1-continuity in their solutions. Consequently, both the unknown and its first derivatives have to be continuous.Employing a finite element method in our study suggests that the C1-finite element representation of the shell solution has to be employed. Therefore, appropriate interpolation functions defined on a typical finite element are studied on both straight and curvilinear boundary domains. Our study of C1-finite element representations shows that the Bell triangular finite element which is derived from the quintic polynomials is more appropriate than the bi-cubic Hermite rectangular element as it converges faster and provides higher accuracy on domains with straight boundaries. However, when the physical boundary is curved, a straight-line approximation is not exact and the performance of the Bell triangular element decreases in terms of both accuracy and convergence rate. To retain a convergence rate and accuracy of the solution of a C1-problem on a curvilinear boundary domain, the C1-curved triangular finite element is introduced. It is proved to show superiority in both convergence rate and accuracy when solving the C1-problem on a curved boundary domain.Furthermore, numerical comparisons between the solutions obtained from the linear and nonlinear governing equations with the linear constitutive law are also reported here. These comparisons confirm that the solutions obtained from the linearised governing equation agree with those of the nonlinear when a loading is small and they start to disagree when the loading becomes larger.
Quality of Life in Adult Cancer Patients With Underage Children: An Integrative Review

As many as 24.7% of cancer patients are also parents to children younger than 18 years of age. This population faces unique challenges, and quality of life in parental cancer patients has not been well studied. This integrative review assessed parental cancer patients’ quality of life. PubMed and Scopus were searched using the following terms: quality of life, distress, anxiety, coping, emotion, social support, employment, work, psychosocial, physical, function, parental cancer, and parents with cancer. English publications conducted within the past 15 years that used an objective instrument to measure quality of life in adult cancer patients with children 18 years of age or younger were included. Studies with an intervention focus were excluded. After review of 672 articles, nine studies met the criteria for inclusion. Several instruments were utilized to measure quality of life. Some parental cancer patients reported decreased quality of life when compared with other cancer patients and the general population at diagnosis and years after. Parental cancer patients may be at an increased risk of decreased quality of life. With this understanding, health-care providers should complete comprehensive assessments routinely so that these patients’ unique needs may be more adequately addressed.
Feasibility and Early Outcomes of a Parent Training Intervention to Engage Parents in Children’s Media Education

The importance of parents in mediating adolescents’ Internet use is documented by many studies in the literature. Very few, however, regard interventions to support parents in this role. We wanted to assess the feasibility and the early outcomes of an Internet-based parent educational group course aimed to support parents in adolescents’ media education. The intervention was conducted with two different groups of parents (N = 20, 75% women; mean age = 46.9 y; SD = 6.3) at different time-points. The intervention included five sessions, during which information about parental mediation strategies was provided and practical exercises based on the Acceptance and Commitment Therapy (ACT) approach were proposed. The intervention generated greater awareness, openness and flexibility and increased parental familiarity with technological devices. Overall, the proposed web-based and group-based parent training model has shown good feasibility and promising early outcomes in supporting parents as Internet mediators.
LRO‐LAMP Lunar South Pole Cold Traps: Assessment of H2O and Potential CO2 and NH3 Reserves

Nighttime Lyman Alpha Mapping Project (LAMP) observations are used to investigate condensed volatiles at the south polar region of the Moon. This study incorporates LAMP data from the first ∼7 years of the mission and Diviner annual maximum temperatures to search for volatile signatures associated with H2O, NH3, and CO2. Other stable potential species, for example, SO2 and H2S, are not identifiable with the ultraviolet ratio‐temperature techniques and are not directly addressed in this study. We confidently detect a ∼20% increase in normalized Off‐band (175–190 nm) to On‐band (148–162 nm) albedo ratios (consistent with condensed surface volatiles) at temperatures below ∼115 K. Elevated normalized ratios extend to temperatures capable of supporting pure aforementioned ices over geologically long time scales. Although ∼115 K is consistent with H2O lifetimes of ∼1‐Myr, the presence of CO2 and NH3 are not uniquely delineated by the data trends with temperature. Future spectral modeling to appropriately identify the composition and abundance of these condensed volatiles remains necessary. Normalized albedo ratios are further analyzed for candidate species via maximum temperatures to inform the likelihood of ice signatures: H2O (70 K < T ≤ 115 K), NH3 + H2O (60 K < T ≤ 70 K), and CO2 + NH3 + H2O (T ≤ 60 K). We compare normalized albedo ratios across seven regions of interest (ROI), including Faustini, Shoemaker, Haworth, Cabeus, Amundsen, Nobile, and an unnamed region. Such comparisons allow for characterization of relative abundances of volatiles across the ROI important for their utilization in future crewed and robotic missions to the Moon.
Incidence of Human Leptospirosis among Scrub Typhus and Chikungunya Negative Children in West Bengal, India, 2022

Leptospirosis caused by the bacterium Leptospira, has been classified by the World Health Organisation (WHO) as a neglected tropical disease with worldwide significance. Leptospirosis in endemic places affects adults more frequently and severely than it affects children. There is a lack of data specifically focusing on children, and it is yet unknown why this discrepancy exists. As the majority of human leptospiral infections are mild or asymptomatic in endemic areas, goal of our study was to describe the prevalence of the Leptospira disease spectrum and the variations in clinical manifestations among patients admitted for febrile illness in a tertiary care facility.
INTEGRATED ANTI-MONEY LAUNDERING INITIATIVES IN THE MALAYSIAN BANKING INDUSTRY TOWARDS FATF FULL-COMPLIANT STATUS

Background and Purpose: This study aims to demonstrate the integrated anti-money laundering (AML) initiatives in the Malaysian banking industry, with particular focus towards achieving the Financial Action Task Force (FATF) full-compliant status. Methodology: This study adopts a qualitative approach, which includes reviews and analysis of secondary data in relevant literature and documents relating to money laundering risk in the Malaysian banking industry. Findings: The integrated AML initiatives combine domestic and international efforts, which are anchored by the Malaysian Central Bank and FATF, respectively. Malaysia has been proactively abiding by the FATF requirements, and affirmative progression can be seen from the improved FATF-compliant status throughout the years. Conclusion and Contributions: This study adds new knowledge to the existing literature by integrating domestic and international AML efforts. Achieving a FATF full-compliant status is not impossible for Malaysia with the current integrated AML initiatives in place, and this forms a strong pillar that could protect the Malaysian banking industry from money laundering risk. Keywords: Money laundering, AML, risk, banking industry, Malaysia. Cite as: Mat Isa, Y. , Hoque, M. N. , Mohd Sanusi, Z. , & Haniff, M. N. (2023). Integrated anti-money laundering initiatives in the Malaysian banking industry towards FATF full-compliant status. Journal of Nusantara Studies, 8(1), 117-139. http://dx.doi. org/10.24200/jonus.vol8iss1pp117-139
Digital challenges of production processes in a company

Industry 4.0 will facilitate and simplify communication processes in manufacturing. Digital technologies are gaining ground, from the emergence of cloud computing to Big Data analytics and IoT. The rapid evolution of digital technologies has fundamentally changed the competitive landscape of manufacturing companies, forcing manufacturing companies to digitise and transform their organisations. ERP systems play a key role for SMEs, as this is an area where SMEs have been lagging far behind large companies. At the same time, there are technical and human barriers to the adoption of advanced technologies, the combined effect of which can cause serious disruption to manufacturing processes. In recent years, digitalisation changes have created a number of new opportunities to secure long-term competitive advantages by systematically improving production performance and/or gradually reducing production costs. The aim of this paper is to illustrate the emerging challenges through a concrete company case study.
Simple modeling of stochastic classical nano-bit data corruption : Probability distribution consideration

Motivated by a real-world application of quantum-dot cellular automata (QCA) and with the help of Monte-Carlo simulations and analytic continuum theory, we have studied the corruption or error process of a binary nano-bit model resulting from an interaction with stochastically independent Brownian agents (BAs). Besides, the more specific link to a real-world application, in this work, we have extended the scope of the study and have used the new technique to reproduce results from previous works by Newman and Triampo [Phys. Rev. E 59, 5172 (1999) and Phys. Rev. E 60, 1450 (1999)]. The new findings include 1) the effect of a “patch” or “cluster” of bits on the simulation results, 2) the log-normal vs. normal distribution of the local bit density, and 3) new results for local bit corruption in two dimensions. The theory is compared with the results of simulations, and good agreement is found. The connection of this binary nano-bit model with the real world is discussed, especially in the context of molecular electronics and the quantum-dot cellular automata paradigm. With model extension such as taking into account a more realistic correlation between bits, our hope is that this work may contribute to an understanding of the soft error or the corruption of data stored in nano-scale devices.
Online Failure Detection using Deep Learning in FPGA PCB Interface

This research paper is aimed to present a real-time failure detection technique while working with Field Programmable Gate Arrays (FPGA) and interfaced Printed Circuit Boards (PCBs). In this research, we explored the feasibility of currently available innovative Deep Learning (DL) algorithms to detect the defects in variety of PCBs. In our proposed technique, we trained the YOLOv5 (You Only Look Once) algorithm with a few hundreds of defective PCBs’ images, which were obtained from Kaggle, an online community of data scientists and machine learning practitioners. The advantage of using YOLOv5 is that the detection is carried out in real-time. In the next phase, after training, the algorithm undergoes validation and testing, where we tested with different images. The obtained results are promising, as the Deep Learning process successfully detects the defects on the PCBs.
THE USE OF SINGING METHOD TO INCREASE STUDENT’S SPEAKING SKILL IN USING PRONOUN AT LANGUAGE CLUB STAI RAKHA AMUNTAI

This research illustrates the increasing of students’ speaking skill through singing method which the formulation of study whether the singing method can increase the student’s speking skill in using pronoun or not. The objectives of this research is to describe the use of singing method to increase student's speaking skill in using pronoun. The techniques of data collecting in this research was Classroom Action Reasearch (CAR) included the observation checklist, test, and documentation. The location of this research was at Language Club STAI RAKHA Amuntai and the subject of the research was 8 students of English class. The instrument of this research included lesson plan, obsevation checklist, and the questions of pre-test and post-test. The result of this research revealed that the pre-test and post-test data is analyze by using statistic formula. According to the report of research result, the use of singing method in using pronoun in the classroom can help students increase their speaking skill. The improvement in the precentage score, which was proved it; the pre-test 1 get 0%, the post-test 1 get 42,8%, the pre-test 2 get 0%, and post-test 2 get 100%. Furthermore according to the observation checklist, the majority of the students response is interesting to the singing method in classroom. Based on the result, it can be concluded that the use of singing method in using pronoun can increase students’ speaking skill as well as their desire to speak. Then, it is suggest to teachers and other researchers, to be able to this research has inspiration to improve students’ speaking skill.
Contraception, female cycle disorders and injuries in Swiss female elite athletes—a cross sectional study

Aim: The national Olympic committee of Switzerland has conducted an online survey among female elite athletes with a focus on cycle disorders, contraception, and injuries in 2021. Methods: A total of 1,092 female elite athletes from 107 different sports were asked to answer the questionnaire. A descriptive analysis was carried out to determine location parameters and create frequency tables. Results: The questionnaire was completed by 408 athletes (37.4%) from 92 different sports. 43.4% participated in a lean sport. 57.1% reported no injuries, 32.6% one injury, and 10.2% two or more injuries per year. A considerable proportion reported being affected by primary amenorrhoea (10.8%). Primary amenorrhoea occurred significantly more often in female athletes with a BMI lower than 21.7 kg/m2 (15.2%) than in athletes with a BMI above 21.7 kg/m2 (7.4%, p = 0.021). Considering contraception, 25.8% of female athletes were currently using an oral contraceptive pill. The proportion of female athletes not using contraception at all or using non-hormonal contraceptive methods was high at 54.4%. In lean sports, significantly more athletes used no or non-hormonal contraceptives (p < 0.05). Conclusion: Among top Swiss female athletes, a considerable proportion used non-hormonal or no contraceptives. This trend was more evident in lean sports. Delayed menarche and cycle irregularities were common among female athletes, especially among athletes with high training volumes as well as a BMI below 21.7 kg/m2. This orienting survey underlines the importance of specialized gynecological care for elite female athletes.
TRFFIC FLOW MODELS WITH THE CONSISTENCY OF ACLASS

This note discusses a recently discovered internal inconsistency of a class of higher-order traffic flow models. It shows that this class of models are mathematically consistent, and that the supposed internal inconsistency is not part of their intrinsic property. Rather, it is a result of insisting on the universality of a special conservation law and imposing incompatible solutions on a equations.
Improvised Explosive Device Detection Using CNN With X-Ray Images

—The concept of a smart city and its associated services have been extensively explored in terms of innovation development and the application of technological concepts. One of the significant concerns in promoting smart living is the security of personal lives and assets, which are at risk from organized crime and acts of terrorism. A considerable amount of attention is paid to preventing bomb attacks in public places, especially the detection of an Improvised Explosive Device (IED). This research focuses on developing an analysis model that can accurately classify instances of x-ray images of baggage or objects as containing IEDs or not. The model provides an alternative to conventional techniques that fail to detect concealed or hidden devices. For this specific project, sample images are generated by experts to cover a range of cases encountered in operations during the past decade. These images are then used to develop a deep learning model, employing several data augmentation methods to overcome the issue of a limited number of training samples. As compared to a related work that exploits neural networks, the proposed model usually achieves higher accuracy rates for unseen samples, with the best accuracy rate being 0.985. Furthermore, an empirical study is conducted to determine the optimal size of the training set that exhibits good predictive performance. The study reveals that a large training set, apart from using a lot of resources, may not yield the best results as it may indicate overfitting.
Clustering Words to Match Conditions: An Algorithm for Stimuli Selection in Factorial Designs.

With the increasing refinement of language processing models and the new discoveries about which variables can modulate these processes, stimuli selection for experiments with a factorial design is becoming a tough task. Selecting sets of words that differ in one variable, while matching these same words into dozens of other confounding variables is time consuming and error prone. To assist experimenters in this thankless task, we present a simple method to perform it with little effort. The method is based on Kmeans clustering as a way to detect small and tight clusters of words that match in the desired variables. We have formalized the procedure into an algorithmic format, that is, a series of easy-to-follow steps. In addition, we also provide an SPSS syntax that helps in choosing the correct size of the clustering. After reviewing the theory, we present a worked example that will guide the reader through the complete procedure. The dataset of the worked example is available as a supplementary material to this paper.
Study Effect of the Aqueous and Alcoholic Extracts of Radish and Ginger on the Gram Negative Bacteria that Cause Urinary Tract Infection in Balad City

This study aimed to investigate the inhibitory effect of aqueous and alcoholic extracts of radish and ginger on bacterial species isolated from urinary tract and auditory system infections. Prior research has shown the potential of natural plant extracts as alternatives to synthetic antibiotics. In this study, extracts were tested at concentrations of 10, 25, 50, and 100 mg/ml for each extract against six different bacterial species. Results demonstrated that the hot alcoholic extract was more efficient than the hot water extracts of the two plants, with 100 mg/ml concentration having the highest inhibition ability. In addition, the inhibitory effect increased with increasing extract concentration. The hot alcoholic extracts of both ginger and radish were found to have higher inhibitory effects against the bacterial species, with the hot alcoholic ginger extract being more effective than the radish water extract. Furthermore, the synergistic effects of the hot alcoholic and water extracts of radish and ginger were tested against all of the identified bacterial species. Finally, sensitivity testing demonstrated that the isolated bacteria showed differences in their sensitivity and resistance to different antibiotics. Overall, this study highlights the potential of natural plant extracts as a source of new antibiotics for the treatment of bacterial infections. Existing research has shown the potential of natural plant extracts as alternatives to synthetic antibiotics for the treatment of bacterial infections, including UTIs. However, there is a lack of studies investigating the inhibitory effect of specific plant extracts, such as radish and ginger, on bacterial species isolated from UTIs and auditory system infections. This study aims to address this research gap by investigating the inhibitory effect of aqueous and alcoholic extracts of radish and ginger on six different bacterial species. The importance of this research gap lies in the increasing prevalence of antibiotic resistance and the need for alternative treatments. The research motivation is to explore the potential of natural plant extracts as a source of new antibiotics for the treatment of bacterial infections.