Miracle-dz/UniFAR-FTUs huggingface dataset:
Lagrangian and vortex-surface fields in turbulence

In this thesis, we focus on Lagrangian investigations of isotropic turbulence, wall-bounded turbulence and vortex dynamics. In particular, the evolutionary multi-scale geometry of Lagrangian structures is quantified and analyzed. Additionally, we also study the dynamics of vortex-surface fields for some simple viscous flows with both Taylor--Green and Kida--Pelz initial conditions. First, we study the non-local geometry of finite-sized Lagrangian structures in both stationary, evolving homogenous isotropic turbulence and also with a frozen turbulent velocity field. The multi-scale geometric analysis is applied on the evolution of Lagrangian fields, obtained by a particle-backward-tracking method, to extract Lagrangian structures at different length scales and to characterize their non-local geometry in a space of reduced geometrical parameters. Next, we report a geometric study of both evolving Lagrangian, and also instantaneous Eulerian structures in turbulent channel flow at low and moderate Reynolds numbers. A multi-scale and multi-directional analysis, based on the mirror-extended curvelet transform, is developed to quantify flow structure geometry including the averaged inclination and sweep angles of both classes of turbulent structures at multiple scales ranging from the half-height of the channel to several viscous length scales. Results for turbulent channel flow include the geometry of candidate quasi-streamwise vortices in the near-wall region, the structural evolution of near-wall vortices, and evidence for the existence and geometry of structure packets based on statistical inter-scale correlations. In order to explore the connection and corresponding representations between Lagrangian kinematics and vortex dynamics, we develop a theoretical formulation and numerical methods for computation of the evolution of a vortex-surface field. Iso-surfaces of the vortex-surface field define vortex surfaces. A systematic methodology is developed for constructing smooth vortex-surface fields for initial Taylor--Green and Kida--Pelz velocity fields by using an optimization approach. Equations describing the evolution of vortex-surface fields are then obtained for both inviscid and viscous incompressible flows. Numerical results on the evolution of vortex-surface fields clarify the continuous vortex dynamics in viscous Taylor--Green and Kida--Pelz flows including the vortex reconnection, rolling-up of vortex tubes, vorticity intensification between anti-parallel vortex tubes, and vortex stretching and twisting. This suggests a possible scenario for explaining the transition from a smooth laminar flow to turbulent flow in terms of topology and geometry of vortex surfaces.
Machine Learning Models for Hate Speech Identification in Marathi Language

Hate speech content has become a significant issue in today’s world. Hate speech detection is an automated task of detecting textual content that contains discriminatory language regarding a person or group based on who they are, their race, gender, caste, etc. In this paper, we discuss the models submitted by our team, Mind Benders, for Marathi subtask A, for "Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages (HASOC)" at Forum for Information Retrieval Evaluation. A training and test dataset in Marathi language containing 1874 and 625 tweets, respectively, were shared by the HASOC organizers. Using these datasets, we propose an approach to automatically classify the tweets into two categories: "NOT" (Non-Hate-Offensive) and "HOF" (Hate and Offensive). The classification models developed are applied to the test dataset. They are experimented with to predict the categories of respective test data.
Synthesis and Electrochemical Performance of the Orthorhombic V2O5·nH2O Nanorods as Cathodes for Aqueous Zinc Batteries

Aqueous zinc-ion batteries offer the greatest promise as an alternative technology for low-cost and high-safety energy storage. However, the development of high-performance cathode materials and their compatibility with aqueous electrolytes are major obstacles to their practical applications. Herein, we report the synthesis of orthorhombic V2O5·nH2O nanorods as cathodes for aqueous zinc batteries. As a result, the electrode delivers a reversible capacity as high as 320 mAh g−1 at 1.0 A g−1 and long-term cycling stability in a wide window of 0.2 to 1.8 V using a mild ZnSO4 aqueous electrolyte. The superior performance can be attributed to the improved stability of materials, inhibited electrolyte decomposition and facilitated charge transfer kinetics of such materials for aqueous zinc storage. Furthermore, a full cell using microsized Zn powder as an anode within capacity-balancing design exhibits high capacity and stable cycling performance, proving the feasibility of these materials for practical application.
The Effect of a Minimum Lot Size Reduction on Residential Property Values: The Case of Houston

The reform of onerous land use regulations in the U.S. is finally having its moment in the spotlight as priority access to billions of dollars in federal grant money is being given to cities willing to make their land use regimes less exclusionary with the hope that this will ease the rising cost of housing (The United States Government, 2022). However, empirical studies on the effects of city-wide land use reform are few and far between due to the fact that examples are so rare. One of the few exceptions is Houston’s 1998 and 2013 reduction of its mandated minimum-lot-size for single-family homes. Given that the this natural-experiment in housing reform remains astoundingly under studied, this paper takes the initiative to estimate the effect that Houston’s minimum-lot-size reduction had on residential property values in the city using appraisal data and a difference-in-differences approach. The results show that that the market-value of single-family homes in Houston rose relative to those of the suburbs and that this was driven by an increase in the value of land. Although these results cannot say to what degree reducing minimum-lot-sizes would improve housing affordability, they do point to a generally more optimal use of land when size restrictions are relaxed.
A NALYSIS ON P SYCHOLOGICAL E FFECT OF L ARGE -S PACE P UBLIC B UILDINGS ON S URROUNDING R ESIDENTS B ASED ON P SYCHOLOGICAL S PACE D ISTANCE T HEORY

With the boom of urban construction, more and more large-space public buildings (LSPBs) have emerged, which widens the psychological space distance between surrounding residents. In this paper, the psychological effect of the LSPBs on the surrounding residents is analysed based on the psychological space distance theory. Eight scenarios were designed according to the construction time of the LSPBs, and the sociality of the surrounding residents. A total of 150 families were selected to make real responses to different scenarios. The responses were analysed in the light of behavioural psychology of people in the LSPBs. The results show that the psychological space distance is unmeasurable, yet affects the behavioural decisions; the psychology of surrounding residences varies with the psychological space distances; the psychological effect on the surrounding residents is negatively correlated with the LSPBs’ construction time, and positively with the sociality of the residents. The research findings lay a theoretical basis for the rational design of the LSPBs.
Analysis, Design and Optimization of Multilayer Antenna Using Wave Concept Iterative Process

The wave concept iterative process is a procedure used for analyses a planar circuits This method consists in generating a recursive relationship between a wave source and reflected waves from the discontinuity plane which is divided into cells. A high computational speed has been achieved by using Fast Modal Transform (FMT). In this paper we study a patch antenna and multilayer circuits, to determine the electromagnetic characteristics of these structures.
TikTok for good: Creating a diverse emotion expression database

Facial expression recognition (FER) is a critical computer vision task for a variety of applications. Despite the widespread use of FER, there is a dearth of racially diverse facial emotion datasets which are enriched for children, teens, and adults. To bridge this gap, we have built a diverse expression recognition database using publicly available videos from TikTok, a video-focused social networking service. We describe the construction of the TikTok Facial expression recognition (FER) database. The dataset is extracted from 6428 videos scraped from TikTok. The videos consist of 9392 distinct individuals and labels for 15 emotion-related prompts. We were able to achieve a F1 score 0.78 for Ekman emotions on expression classification using transfer learning. We hope that the scale and diversity of the TikTokFER dataset will be of use to affective computing practitioners.
An Attention-based Method for Multi-label Facial Action Unit Detection

Facial Action Coding System is an approach for modeling the complexity of human emotional expression. Automatic action unit (AU) detection is a crucial research area in human-computer interaction. This paper describes our submission to the third Affective Behavior Analysis in-the-wild (ABAW) competition 2022. We proposed a method for detecting facial action units in the video. In the first stage, a lightweight CNN-based feature extractor is employed to extract the feature map from each video frame. Then, an attention module is applied to refine the attention map. The attention encoded vector is derived using a weighted sum of the feature map and the attention scores later. Finally, the sigmoid function is used at the output layer to make the prediction suitable for multi-label AUs detection. We achieved a macro F1 score of 0.48 on the validation set and 0.4206 on the test set compared to 0.39 and 0.3650from the ABAW challenge baseline model.
Association Between Serum Albumin Level and Microvascular Complications of Type 2 Diabetes Mellitus

Objective: To analyze the associations between serum albumin (sALB) level and diabetic microvascular complications, including diabetic retinopathy (DR) and diabetic kidney disease (DKD), in patients with type 2 diabetes mellitus (T2DM). Methods: This retrospective study included 951 hospitalized patients with T2DM who had completed screening for DR and DKD during hospitalization. Patients were divided into three groups according to sALB tertiles. Multivariate logistic regression analysis was used to assess the association of sALB with microvascular complications. Results: The prevalence of DR, DKD and macroalbuminuria increased with decreasing sALB levels. Multivariate logistic regression analysis showed that lower levels of sALB (Q1) were associated with higher risk of DR (odds ratio [OR]: 1.59, 95% confidence interval [CI]: 1.12–2.26), DKD (OR: 3.00, 95% CI: 2.04–4.41) and macroalbuminuria (OR: 9.76, 95% CI: 4.62–20.63) compared with higher levels of sALB (Q3) after adjustment for other risk factors. After stratification by sex and age, the effect of lower levels of sALB (Q1) on DR incidence was more obvious in patients with male (OR: 1.60, 95% CI: 1.00–2.56), and aged<65 years (OR: 1.74, 95% CI: 1.14–2.65) ( P < 0.05 for all); the effect of lower levels of sALB (Q1) on the incidence of DKD was significant in both males (OR: 3.78, 95% CI: 2.26–6.32) and females (OR: 2.35, 95% CI: 1.26–4.35) ( P < 0.05 for all), while only the age <65 years (OR: 3.46, 95% CI: 2.16–5.53) was significant in the age subgroup ( P < 0.001). Conclusion: Decreased sALB levels may be an independent risk indicator of DR and DKD in patients with T2DM, and significantly associated with DKD progression. For DR screening, special attention should be paid to men aged <65 years, while screening for DKD should pay attention to people <65 years old.
Prevention of resistance in by NSC23925.

Background: The major limitation to the success of chemotherapy in osteosarcoma is the development of multidrug resistance (MDR). Preventing the emergence of MDR during chemotherapy treatment has been a high priority of clinical and investigational oncology, but it remains an elusive goal. The NSC23925 has recently been identified as a novel and potent MDR reversal agent. However, whether NSC23925 can prevent the development of MDR in cancer is unknown. Therefore, this study aims to evaluate the effects of NSC23925 on prevention of the development of MDR in osteosarcoma. Methods: Human osteosarcoma cell lines U-2OS and Saos were exposed to increasing concentrations of paclitaxel alone or in combination with NSC23925 for 6 months. Cell sublines selected at different time points were evaluated for their drug sensitivity, drug transporter P-glycoprotein (Pgp) expression and activity. Results: We observed that tumour cells selected with increasing concentrations of paclitaxel alone developed MDR with resistance to paclitaxel and other Pgp substrates, whereas cells cultured with paclitaxel–NSC23925 did not develop MDR and cells remained sensitive to chemotherapeutic agents. Paclitaxel-resistant cells showed high expression and activity of the Pgp, whereas paclitaxel–NSC23925-treated cells did not express Pgp. No changes in IC 50 and Pgp expression and activity were observed in cells grown with the NSC23925 alone. Conclusions: Our findings suggest that NSC23925 of of Pgp. significant incidence of in agents prevention of and hold a higher Calcein
In Vitro and in Silico Liver Models: Current Trends, Challenges and In Vitro and in Silico Liver Models: Current Trends, Challenges and Opportunities Opportunities

Most common drug development failures originate from either bioavailability problems or unexpected toxic effects. The culprit is often the liver, which is responsible for biotransformation of the majority of xenobiotics. Liver may be modeled using liver-on-a-chip devices, which may include established cell lines, primary human cells, and stem cell-derived hepatocyte-like cells. The choice of biological material along with its processing
Challenges and variability in building software product families: Case railway energy settlement system

According to European Union, all member countries shall have a settlement system in use by 2020. The settlement system shall receive energy consumption data from meters installed in trains, validate the data and allocate it for the right user. In this way, the energy consumption can be invoiced from the right user precisely. Erex is a such energy settlement system. The system needs to be adopted for each country to meet their different needs with regards to laws, systems and practices. This means that the system shall allow at least some flexibility. When new partners have entered the partnership and new instances have been created and modified for them with ad-hoc methods, the manageability of the systems has decreased. For this reason, a need to improve the management of the systems as whole has been raised. It would be easier, if the systems would have a shared core and systematically managed variability. This would mean creating a product family with systematically managed commonality and variability. The objective of this thesis was to study, what are the challenges of creating such product family, where all systems share the same principles but some degree of flexibility is allowed. To achieve these objectives, experts from partner countries and the administration and developers of the systems were interviewed. Thereafter, challenges related to product families and their variability were studied from the literature. Then, the challenges found in empirical and theoretical parts were compared. The objective was to see if the results of empirical study support the current literature. The comparison had three key results. Firstly, many of the current challenges are rather typical for software that is derived with ad-hoc methods. These challenges were found both in empirical and theoretical parts. Secondly, there were a group of challenges that were found only in the theoretical part and did not appear in the interviews but were considered as potential for this case. Thus, these challenges can be of great worth when the product family is developed. Lastly, there were challenges discovered only in the empirical part. These challenges are highly case and domain specific and were not investigated in the theoretical part due to their subjects. Experience from domain should be used to address these case specific challenges as they may not be found from any literature. There were only three challenges that could have been addressed in theoretical part by their subject. Compared to the whole amount of challenges found, these three challenges had only little role. Overall, this means that challenges found in the case are rather typical for product families. Thus, experience from the literature and industry can be used to solve these challenges
Dependence of the efficiency of spin Hall torque on the transparency of Pt/ferromagnetic layer interfaces

We report that spin current transport across Pt-ferromagnet (FM) interfaces is strongly dependent on the type and the thickness of the FM layer and on post-deposition processing protocols. By employing both harmonic voltage measurements and spin-torque ferromagnetic resonance measurements, we find that the efficiency of the Pt spin Hall effect in exerting a damping-like spin torque on the FM ranges from 0.10 under different interfacial conditions. We also show that the temperature dependence of the spin torque efficiencies for both the damping-like torque and field-like torque is dependent upon the details of the Pt-FM interface. The "internal" spin Hall angle of the Pt thin films used in this study, after taking the interfacial spin transmission factor into account, is estimated to be ~ 0.20. This suggests that a careful engineering of Pt-FM interfaces can improve the spin-Hall-torque efficiency of Pt-based spintronic devices.
Graph theoretic structural modeling based new measures of complexity for analysis of lean initiatives

Purpose The purpose of this paper is to propose the use of graph theoretic structural modeling for assessing the possible reduction in complexity of the work flow procedures in an organization due to lean initiatives. A tool to assess the impact of lean initiative on complexity of the system at an early stage of decision making is proposed. Design/methodology/approach First, the permanent function-based graph theoretic structural model has been applied to understand the complex structure of a manufacturing system under consideration. The model helps by systematically breaking it into different sub-graphs that identify all the cycles of interactions among the subsystems in the organization in a systematic manner. The physical interpretation of the existing quantitative methods linked to graph theoretic methodology, namely two types of coefficients of dissimilarity, has been used to evolve the new measures of organizational complexity. The new methods have been deployed for studying the impact of different lean initiatives on complexity reduction in a case industrial organization. Findings The usefulness and the application of new proposed measures of complexity have been demonstrated with the help of three cases of lean initiatives in an industrial organization. The new measures of complexity have been proposed as a credible tool for studying the lean initiatives and their implications. Research limitations/implications The paper may lead many researchers to use the proposed tool to model different cases of lean manufacturing and pave a new direction for future research in lean manufacturing. Practical implications The paper demonstrates the application of new tools through cases and the tool may be used by practitioners of lean philosophy or total quality management to model and investigate their decisions. Originality/value The proposed measures of complexity are absolutely new addition to the tool box of graph theoretic structural modeling and have a potential to be adopted by practical decision makers to steer their organizations though such decisions before the costly interruptions in manufacturing systems are tried on ground.
Brand preference for mobile phones among students at a selected higher education institution

It is widely evident that the mobile phone industry is facing rapid growth, with the increased introduction of cheaper mobile phones in South Africa intensifying competition between such companies. A number of studies have been conducted in other countries on brand preferences, but there remains a gap in knowledge with regard to the South African market. It was therefore warranted to academically research factors influencing consumer brand preferences when purchasing mobile phones, in order to understand these preferences, and what consumers consider when making such purchases. The rationale of the study was to provide new insights for local marketers into the factors consumers consider most when looking at mobile phone brands. The aim of this study was therefore to determine brand preferences for mobile phones amongst students at a selected higher educational institution in South Africa. The study adopted a quantitative research approach, where the data obtained was descriptive and cross-sectional in nature. The research population was made up of students studying at the Durban University of Technology (DUT), where convenience sampling was performed on a target population of 378 students. The sample size was selected by giving questionnaires to those students most available to the researcher. The results were then analysed using the Statistical Package for Social Sciences (SPSS) Version 24.0 software. Validity was ensured by conducting a pre-test of the questionnaire, and the study’s reliability was measured using Cronbach’s Co-efficient Alpha test. The study findings showed that brand popularity, prices, product attributes, social influences and marketing communications all affect mobile phone brand preferences amongst students. The study results also showed, however, that there were some product attributes and social influences that did not influence these preferences. Recommendations are given to industry players to increase their knowledge of these important factors, to aid with the improvement of their brands and increasing their market preference in this highly competitive industry.
SWIVEL AND WET FINGERPRINT RECOGNITION TECHNIQUE

This paper assesses the effects of prolonged exposure of fingers to water on the performance of existing fingerprint recognition systems.Many fingers wrinkle or dwindle when immersed in water . When used for biometric identification; recognition rate for wrinkled fingers degrades. Apart from this the existing techniques used are not rotation invariant and fail when enrolled image of a person is matched with a rotated test image . The influence of wrinkling and rotated finger prints has so far not been well understood . In this paper we present a particularized report of how the finger skin inflation due to wrinkling and rotation of fingerprints influences the quality of scanned fingerprints and distinguish the qualitative changes that affect recognition.