Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavioural, Socio-economic Factors, Financial Literacy and Investment Decisions: Are Men More Rational and Women More Emotional?

This study covers the gender-wise analysis of how behavioural factors and socio-economic factors along with the level of financial literacy influence investment decisions of Indian retail investors. Equally pertinent is to understand that will it have a different influence and bearing on males and females. Multivariate technique partial least squares-structural equation modelling (PLS-SEM) has been applied to develop the model and analyse the results. The study used a structured questionnaire for collecting data from retail investors. The findings of PLS-SEM show that in both genders, behavioural factors, socio-economic factors and financial literacy factors significantly affect investment decisions. However, the findings demonstrate that for women investors, the model is more effective. This study may be useful for prospective fund managers as, in many earlier studies, women are considered to be risk aversive. The results demonstrate that there is a need to target women, and the scenario today is not similar to the pre-existing ones. JEL Classification: G110, G4
Mini-batch graphs for robust image classification

Current deep learning models for classification tasks in computer vision are trained using mini-batches. In the present article, we take advantage of the relationships between samples in a mini-batch, using graph neural networks to aggregate information from similar images. This helps mitigate the adverse effects of alterations to the input images on classification performance. Diverse experiments on image-based object and scene classification show that this approach not only improves a classifier's performance but also increases its robustness to image perturbations and adversarial attacks. Further, we also show that mini-batch graph neural networks can help to alleviate the problem of mode collapse in Generative Adversarial Networks.
Statistical Assessment of Sustainability of Finger Millet Yield through Rainfall and Soil Fertility Variables using Regression and Principal Component Models in Rainfed Semi-Arid Alfisol

ABSTRACT Field experiments were conducted in farmyard manure (FYM) and maize-residue (MR) blocks during 1984–2011 with the objective of identifying a superior treatment for attaining maximum finger millet yield and soil fertility at Bangalore. The treatments tested in the FYM block were Control; FYM@10tha−1; FYM@10tha−1 + 50% nitrogen, phosphorus, and potassium (NPK); FYM@10tha−1 + 100%NPK; 100%NPK; and in the MR block, Control; MR@5tha−1; MR@5t ha−1 + 50%NPK; MR@5tha−1 + 100%NPK; 100%NPK. FYM@10t/ha + 100%NPK gave a maximum mean yield of 3207 kg/ha in the FYM block, while MR@5t/ha + 100%NPK gave 2548 kg/ha in the MR block. Regression and principal component (PC) models of yield were developed through soil fertility and rainfall variables to assess the treatments. Maximum yield predictability of 60% and 65% under regression, and 76% and 75% under the PC model were observed for the FYM and MR blocks, respectively. FYM@10t/ha + 50%NPK was superior, with maximum gross returns of Rs.41286/ha and benefit–cost ratio (BCR) of 2.27 in the FYM block compared to MR@5t/ha + 100%NPK (gross returns of Rs.34530/ha and BCR of 2.09) in the MR block with maximum soil fertility, and are recommended for adoption under semi-arid Alfisols.
Guidelines for the Development of Restaurant Businesses: Providing Online Food Delivery Services in Khon Kaen, Thailand

This research aims to find the guidelines for developing the restaurant businesses providing online food delivery services in Muang District, Khon Kaen Province, Thailand. Qualitative research was utilized to conduct the research. There were two techniques: namely, Documentary research and In-depth interviews (IDI) with seventeen key informants with at least five years of business experience. The study found that 9 M (Man, Money, Materials, Management, Morale, Message, Marketing, Menu, and Mindset) led to the business-critical successes. Place or distribution channel was an important factor for service marketing mixed factors. The finding showed three service innovations: 1) New service concepts, 2) New service processes, and 3) New service business models for the guidelines to develop restaurant businesses providing online food delivery services.
Prevalence of Work-related Musculoskeletal Symptoms among Dental Students at Ss. Cyril and Methodius University Dental School in Skopje

AIM: The aim of the study was to investigate the prevalence of work-related musculoskeletal problems in 3rd, 4th, and final year of study in Ss. Cyril and Methodius University Dental School. METHODS: All 3rd, 4th, and final year regular dental students were invited to take part in the study, which involved completing the extended Nordic Musculoskeletal Questionnaire. This questionnaire facilitates an assessment of troubles (ache, pain, or discomfort) with neck, shoulders, upper back, elbows, wrists/hands, low back, hips/thighs, knees, and ankles/feet. RESULTS: Out of a maximum possible number of 146 students, 116 agreed to participate and completed the questionnaire (33 males and 83 females). The response rate was 79.5%. The mean age of students was 22.6 years (SD = 1.52), ranging from 20 to 26 years. During the past 12 months, students have problems mostly with neck 48 (41.4%), upper back 43 (37.1%), and low back 43 (37.1%). Working hours/week was 12 h for 3rd year, 20 h for 4th, and 30 h for 5th-year students. There is a significant difference between the students from third study year with these from 4th and 6th study year regarding the neck (χ2 (2)= 6.46, p < 0.05), upper back (χ2 (2) = 7.38, p < 0.05), and low back (χ2 (2)= 13.79, p < 0.05). CONCLUSIONS: This study reported high prevalence of musculoskeletal symptoms among the dental students. Preventive measures and more ergonomic recommendations are indicated.
Are Pretrained Convolutions Better than Pretrained Transformers?

In the era of pre-trained language models, Transformers are the de facto choice of model architectures. While recent research has shown promise in entirely convolutional, or CNN, architectures, they have not been explored using the pre-train-fine-tune paradigm. In the context of language models, are convolutional models competitive to Transformers when pre-trained? This paper investigates this research question and presents several interesting findings. Across an extensive set of experiments on 8 datasets/tasks, we find that CNN-based pre-trained models are competitive and outperform their Transformer counterpart in certain scenarios, albeit with caveats. Overall, the findings outlined in this paper suggest that conflating pre-training and architectural advances is misguided and that both advances should be considered independently. We believe our research paves the way for a healthy amount of optimism in alternative architectures.
Lovász-Type Theorems and Game Comonads

Lovász (1967) showed that two finite relational structures A and B are isomorphic if, and only if, the number of homomorphisms from C to A is the same as the number of homomorphisms from C to B for any finite structure C. Soon after, Pultr (1973) proved a categorical generalisation of this fact. We propose a new categorical formulation, which applies to any locally finite category with pushouts and a proper factorisation system. As special cases of this general theorem, we obtain two variants of Lovász’ theorem: the result by Dvořák (2010) that characterises equivalence of graphs in the k-dimensional Weisfeiler–Leman equivalence by homomorphism counts from graphs of tree-width at most k, and the result of Grohe (2020) characterising equivalence with respect to first-order logic with counting and quantifier depth k in terms of homomorphism counts from graphs of tree-depth at most k. The connection of our categorical formulation with these results is obtained by means of the game comonads of Abramsky et al. We also present a novel application to homomorphism counts in modal logic.
Mixed Methods Review of A Home-Grown School Feeding Pilot in A Poor Ethnic Minority Community in Vietnam 

Background Undernutrition threatens the health and future of preschool children in disadvantaged ethnic minority communities. Home-grown school feeding (HGSF) in nursery schools could have a positive impact on children’s nutrition while creating multiple benefits for the community and local food system. Evidence is lacking on the implementation and sustainability of HGSF as part of multi-sectoral programs in remote areas. This study assessed a HGSF pilot intervention, implemented within a four-year nutrition-sensitive agriculture (NSA) program, in five nursery schools in a mountain ethnic minority community in Vietnam. It aimed to gain insights into the diversity and cost of school meals, food sources, effects on children’s nutritional status and on process aspects related to implementation and sustainability, especially HGSF synergy with other NSA program components. Methods Mixed-methods assessment covered school meal diversity and cost; food sources; anthropometric data; and the process, including changes triggered by HGSF, perceived barriers and facilitators to implementation, and prospects for sustainability. Data came from participants selected by purposive sampling for semi-structured interviews (n = 30) and seven focus group discussions (n = 76), and from field observations and transect walks. Results School meals increased daily dietary diversity; meals cost USD 0.65/child/day. About 44% of the foods used were home-grown. There was an indicative reduction in underweight children, an increase in school attendance, and improvements in food preferences and WASH practices. Parents’ caring and feeding practices improved and their willingness to pay for school meals increased. At community level, local food systems became less cash crop-oriented and more self-reliant in production of nutrient-rich foods, contributing to household food security and income generation. Social capital increased. Positive changes were attributed to HGSF and to synergy among NSA program components. Enhanced confidence and motivation, stimulated by role models and change agents, facilitated the process. Socio-economic conditions of poor households and limited resilience to external shocks were barriers that threatened sustainability. Conclusions This study showed that implementing HGSF in a mountain ethnic minority area with a high prevalence of undernutrition benefitted children and their communities, when integrated in a multi-sectoral program that mobilises all stakeholders and stimulates both supply and demand of nutritious food.
Peningkatan Literasi Keuangan pada UMKM melalui Pelatihan dan Pendampingan Pembukuan Sederhana

UMKM diharapkan menjadi garda terdepan untuk memperkuat pilar ekonomi dalam mencapai tujuan pembangunan berkelanjutan atau Sustainable Development Goals (SGDs). Hal ini dikarenakan UMKM menjadi salah satu usaha yang paling mampu bertahan dalam kondisi perekonomian yang memburuk terutama dalam kondisi pandemi Covid-19 ini. Oleh karena itulah, UMKM harus memiliki pengelolaan keuangan yang baik supaya usaha yang dijalankan dapat berkelanjutan. Salah satunya dengan memiliki pencatatan keuangan yang benar serta mampu menyusun laporan keuangan yang diperlukan untuk mengambil keputusan dalam merencanakan strategi bisnis yang selanjutnya. UMKM Batik di Desa Tegalrejo Kecamatan Gedangsari belum memiliki pencatatan yang baik sehingga tidak mampu menghasilkan laporan keuangan. Hasil pelatihan dan pendampingan membuat pembukuan sederhana dan menyusun laporan keuangan ini meningkatkan kesadaran pelaku UMKM akan pentingnya informasi yang dihasilkan laporan keuangan sebagai dasar pengambilan keputusan dan penyusunan strategi bisnis untuk mencapai usaha yang berkelanjutan.
Abnormal WBC Scattergrams by Sysmex XN550, A Supplementary Diagnostic Tool for Malaria to the Conventional Methods

Background: In India, malaria has a major impact on health system. It is usually diagnosed based on symptomatology, parasite detection in the peripheral smear (PS) or rapid diagnostic tests (RDT) such as malaria antigen test (MAT). Detection of malaria by MAT is considered as the gold standard. A rapid, cost effective screening of malaria can be done with the automated analyzers. The present study was undertaken to assess the efficacy of WBC scattergram generated by Sysmex XN 550 hematology analyzer to diagnose malaria. Methods: A prospective study was conducted over a period of 4 months from August to November 2019, after obtaining institutional ethical clearance. All cases diagnosed as Plasmodium vivax / Plasmodium falciparum infections on malaria antigen test (MAT) were included. Their hemogram and WBC scattergrams obtained from Sysmex XN 550 were studied. Thick & thin Smears were made and stained with Leishman’s stain for microscopy. Results: A total of 101 cases were diagnosed as malaria positive by MAT and thick smear. Ninety-seven were positive by Leishman’s stain. Abnormal scattergrams were 81 out of 101 malaria positive cases. The commonest pattern was double neutrophil zone (n=22) followed by double neutrophil with less space between neutrophil and eosinophil (n=17). An abnormal event on X axis was observed in 16 patients. Gray zone and double eosinophil areas were observed in 11 and 4 cases respectively. The sensitivity of the analyzer was found to be 80.19%. Conclusion: Scattergram of automated haematology analyser (Sysmex XN 550) has good sensitivity, which can be increased to a better level if combined with thrombocytopenia and symptomatology of the patients.
Well-being of Students Affected by Disaster: A Case Study of 2004 Tsunami in Sri Lanka

The main objective of the study was to identify the long-term well-being of students affected by the tsunami of December 2004. The specific aims of the study were to evaluate the psychological, social and educational well-being of students affected by the tsunami, 13 years after the tsunami; and to examine the nature of psycho-social counselling and material support and how these services contributed to their well-being. The methods used to gather data were both quantitative and qualitative with purposive sampling, using the class teachers’ nominations. Six school teachers and five counsellors and 43 girls and 42 boys from the Southern Province were enrolled in the study. The results of the study showed how students affected by the tsunami had to face different trauma related experiences such as their family members remaining missing and their family members’ death or injury, although the students themselves had escaped the tidal waves. Thus, the trauma related to experiences of the tsunami caused the students to have many psychological and emotional difficulties. The qualitative results showed that the students had reached a quite satisfactory level of well-being, 13 years after the tsunami. The children had attended psycho-social education awareness programs and received psycho-social “training” and counselling interventions. These were implemented in order to successfully develop the students’ well-being. The findings suggested that the students required further professional counselling services and welfare facilities within the school system and also a drug prevention program in order to further their well-being, based on a long-term plan.
Integrated Sensing and Communication-Assisted Orthogonal Time Frequency Space Transmission for Vehicular Networks

Orthogonal time frequency space (OTFS) modulation is a promising candidate for supporting reliable information transmission in high-mobility vehicular networks. In this paper, we consider the employment of the integrated (radar) sensing and communication (ISAC) technique for assisting OTFS transmission in both uplink and downlink vehicular communication systems. Benefiting from the OTFS-ISAC signals, the roadside unit (RSU) is capable of simultaneously transmitting downlink information to the vehicles and estimating the sensing parameters of vehicles, e.g., locations and speeds, based on the reflected echoes. Then, relying on the estimated kinematic parameters of vehicles, the RSU can construct the topology of the vehicular network that enables the prediction of the vehicle states in the following time instant. Consequently, the RSU can effectively formulate the transmit downlink beamformers according to the predicted parameters to counteract the channel adversity such that the vehicles can directly detect the information without the need of performing channel estimation. As for the uplink transmission, the RSU can infer the delays and Dopplers associated with different channel paths based on the aforementioned dynamic topology of the vehicular network. Thus, inserting guard space as in conventional methods are not needed for uplink channel estimation which removes the required training overhead. Finally, an efficient uplink detector is proposed by taking into account the channel estimation uncertainty. Through numerical simulations, we demonstrate the benefits of the proposed ISAC-assisted OTFS transmission scheme.
Phytochemical screening and Thin layer chromatographic identification of Terpenoids from the root extract of Achyranthes aspera l.- An Indian Ethanomedicine

Medicinal plants are big source of information for wide variety of chemical constituents which could be developed as drug with precise selectivity. Achyranthes aspera Linn is one of the important medicinal plants having many therapeutic uses. The present study deals with preliminary phytochemical screening and TLC investigation of Achyranthes aspera Linn. In qualitative analysis, the phytochemical compounds such as steroids, triterpenoids, sugars, alkaloids, phenolic compounds, flavonoids were screened in root methanolic extract by using standard methods. Phytochemical screening of plant revealed the presence of alkaloids, flavonoids steroids reducing sugar, glycosides and Terpenoids. The present study revealed that Achyranthes aspera roots are important source of many therapeutically and pharmacologically active constituents.
Modeling of Spiral Structure in a Multi-Component Milky~Way-Like Galaxy

Using recent observational data, we construct a set of multi-component equilibrium models of the disk of a Milky Way-like galaxy. The disk dynamics are studied using collisionless-gaseous numerical simulations, based on the joined integration of the equations of motion for the collision-less particles using direct integration of gravitational interaction and the gaseous SPH-particles. We find that after approximately one Gyr, a prominent central bar is formed having a semi-axis length of about three kpc, together with a multi-armed spiral pattern represented by a superposition of m= 2-, 3-, and 4-armed spirals. The spiral structure and the bar exist for at least 3 Gyr in our simulations. The existence of the Milky Way bar imposes limitations on the density distributions in the subsystems of the Milky Way galaxy. We find that a bar does not form if the radial scale length of the density distribution in the disk exceeds 2.6 kpc. As expected, the bar formation is also suppressed by a compact massive stellar bulge. We also demonstrate that the maximum value in the rotation curve of the disk of the Milky Way galaxy, as found in its central regions, is explained by non-circular motion due to the presence of a bar and its orientation relative to an observer.
What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory

We develop a variational framework to understand the properties of functions learned by fitting deep neural networks with rectified linear unit activations to data. We propose a new function space, which is reminiscent of classical bounded variation-type spaces, that captures the compositional structure associated with deep neural networks. We derive a representer theorem showing that deep ReLU networks are solutions to regularized data fitting problems over functions from this space. The function space consists of compositions of functions from the Banach spaces of second-order bounded variation in the Radon domain. These are Banach spaces with sparsity-promoting norms, giving insight into the role of sparsity in deep neural networks. The neural network solutions have skip connections and rank bounded weight matrices, providing new theoretical support for these common architectural choices. The variational problem we study can be recast as a finite-dimensional neural network training problem with regularization schemes related to the notions of weight decay and path-norm regularization. Finally, our analysis builds on techniques from variational spline theory, providing new connections between deep neural networks and splines.
The impact of Rural Enterprise Development Hub (RED Hub) project on beneficiaries maize yield in Mqanduli, South Africa

The study analysed the impact of Rural Enterprise Development Hub (RED Hub) Project on maize yield of beneficiaries. Out of a total of 398 beneficiaries, 200 maize farmers were sampled using the Cochran sample size formula followed by convenience sampling at the second stage. With the use of a 'before' and 'after' approach, a survey was conducted using structured questionnaires which were administered on the beneficiaries of the project in Mquanduli community within the 9 villages of the community. Descriptive and inferential statistics were used to analyze the data. It was established that, a P-value of less than 0.05 was statistically significant. The study revealed a significant average annual yield increase of maize farmers who benefitted in the project from 1,003 to 1,891 kg with an increase of 88.53% on hectare basis (t = 100.3 and p <0.05). Also, there was an average increase in annual yield from 1,976 to 4,351 kg which was significant with an increase of 120.19% per maize farm (t = 32.7 and p<0.05 p-value). Determinants of increase in maize productivity were identified using regression analytical technique; They were fertilizer (t = -4.46 and p <0.05), seedling (t = 4.47 and p<0.05) and capital (t = 4.35 and p<0.05). The study recommends sustained subsidy and direct delivery of productive inputs to beneficiary farmers and additional provision to accommodate more maize farmers in Mqanduli. Key words: Rural, yield, beneficiaries, farmers, community.
PENGARUH EARNING PER SHARE (EPS) DAN PRICE EARNING RATIO (PER) TERHADAP RETURN SAHAM PADA PERUSAHAAN LQ45 PERIODE 2017-2019

Perusahaan yang memiliki kinerja cukup baik akan lebih diminati oleh para investor. Kinerja perusahaan yang meningkat akan berpengaruh pada meningkatnya harga saham dan diharapkan return saham yang diterima investor meningkat. Salah satu kelompok perusahaan yang diminati oleh para investor adalah perusahaan-perusahaan yang masuk kedalam indeks LQ45. Penelitian ini bertujuan untuk mengetahui pengaruh earning per share dan price earning ratio terhadap return saham baik secara parsial maupun simultan. Metode yang digunakan dalam penelitian ini adalah metode kuantitatif dengan jenis perumusan masalah asosiatif. Populasi dalam penelitian ini adalah perusahaan LQ45 yang terdaftar di BEI. Berdasarkan kriteria yang ada, pengambilan sampel dilakukan dengan teknik purposive sampling. Teknik analisis data yang digunakan dalam penelitian ini adalah uji normalitas data, korelasi product moment, korelasi berganda, regresi linier berganda, koefisien determinasi, uji t-test, dan uji f-test. Hasil penelitian ini menunjukkan baik secara parsial maupun simultan variabel earning per share dan variabel price earning ratio tidak memiliki pengaruh yang signifikan terhadap return saham