Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs

Streaming classification methods assume the number of input features is fixed and always received. But in many real-world scenarios, some features are reliable while others are unreliable or inconsistent. We propose a novel online deep learning-based model called Auxiliary Network (Aux-Net), which is scalable and agile and can handle any number of inputs at each time instance. The Aux-Net model is based on the hedging algorithm and online gradient descent. It employs a model of varying depth in an online setting using single pass learning. Aux-Net is a foundational work towards scalable neural network for a dynamic complex environment dealing ad hoc or inconsistent inputs. The efficacy of Aux-Net is shown on the Italy Power Demand dataset

A STUDY TO EXPLORE THE EFFECT OF BRAND LABEL VS. INFORMATION LABEL IN THE FOOD AND BEVERAGE INDUSTRY TOWARDS GREENWASHING PRACTICES

The study explores the impact of brand labels versus nutritional labels on consumer perceptions in the food and beverage industry addressing the growing concern of greenwashing practices. Brand labels strongly impact consumer choices because of their established associations. However, the influence of labels such as nutritional details in changing consumer perceptions is a less studied area. This research aims to compare the effects of these labels on consumer decisions with a lens of greenwashing. Using a descriptive survey design, data was collected from 271 consumers in retail settings like malls and supermarkets. Participants were exposed to brand labels followed by nutritional labels to assess shifts in perception and purchase intention. Findings indicate that trust and visual attention in the context of brand labelling significantly impact perception and purchase intention of a product. Trust and awareness factors in the context of nutrition labels significantly influence consumer brand-driven perceptions by revealing a product's true value. This highlights greenwashing practices where brands exploit consumer trust through vague or misleading claims. The study underscores the potential of labelling in promoting transparency and encouraging informed and health-conscious purchasing behaviors. These findings are valuable for brands aiming to build trust and for policymakers to design effective labelling regulations. Future research could explore label impacts across varied retail formats and product categories to enhance consumer education on healthful choices

Investor Sentiment and Debt Contracting

**Please note that the full text is embargoed until 08/01/2024** This study examines the impact of investor sentiment on loan spread and financial covenants in debt contracts. Periods of high investor sentiment generally result in pressure on loan spreads due to the ability to issue equity at lower cost. Thus, I conjecture that managers of borrowing firms as well as lenders may trade-off lower spreads against higher or more restrictive covenants during such periods. Therefore, high investor sentiment has two related effects on debt covenants: (i) it encourages higher and more restrictive covenants by lenders at contract inception and, consequently, (ii) it ensures a higher ex-ante probability of eventual covenant violations. Consistent with the conjectures, I find that investor sentiment is positively associated with the intensity and restrictiveness of financial covenants and negatively associated with spreads. Specifically, high investor sentiment periods are associated with higher covenants (performance covenants, capital covenants and covenants intensity) and lower spreads. Further analysis indicates that this relationship is more pronounced for financially constrained firms and for firms that exhibit a lower degree of timely loss recognition in accounting earnings. Additionally, I find that investor sentiment is positively associated with the ex-ante likelihood of covenant violations. Collectively, these findings highlight the importance of the role played by investor sentiment in debt contracting

Online Learning under Haphazard Input Conditions: A Comprehensive Review and Analysis

The domain of online learning has experienced multifaceted expansion owing to its prevalence in real-life applications. Nonetheless, this progression operates under the assumption that the input feature space of the streaming data remains constant. In this survey paper, we address the topic of online learning in the context of haphazard inputs, explicitly foregoing such an assumption. We discuss, classify, evaluate, and compare the methodologies that are adept at modeling haphazard inputs, additionally providing the corresponding code implementations and their carbon footprint. Moreover, we classify the datasets related to the field of haphazard inputs and introduce evaluation metrics specifically designed for datasets exhibiting imbalance

Tube bending with axial pull and internal pressure

Tube bending is a widely used manufacturing process in the aerospace, automotive, and other industries. During tube bending, considerable in-plane distortion and thickness variation occurs. The thickness increases at the intrados (surface of tube in contact with the die) and it reduces at the extrados (outer surface of the tube). In some cases, when the bend die radius is small, wrinkling occurs at the intrados. In industry a mandrel is used to eliminate wrinkling and reduce distortion. However, in the case of a close bend die radius, use of a mandrel should be avoided as bending with the mandrel increases the thinning of the wall at the extrados, which is undesirable in the manufacturing operation. The present research focuses on additional loadings such as axial force and internal pressure which can be used to achieve better shape control and thickness distribution of the tube. Based on plasticity theories, an analytical model is developed to predict cross section distortion and thickness change of tubes under various loading conditions. Results from both the FEA and analytical model indicated that at the intrados the increase in thickness for bending with internal pressure and bending with combined axial pull and internal pressure was nearly the same. But in the case of bending with the combination of axial pull and internal pressure there was a significant reduction of thickness at the extrados. A parametric study was conducted for the case of bending with combined internal pressure and axial pull and it was seen that with proper selection of the pressure and axial pull wrinkling can be eliminated, thickness distribution around the tube can be optimized, and cross section distortion of the tube can be reduced. Predictions of the analytical model are in good agreement with finite element simulations and published experimental results. The model can be used to evaluate tooling and process design in tube bending

Online Learning under Haphazard Input Conditions: A Comprehensive Review and Analysis

The domain of online learning has experienced multifaceted expansion owing to its prevalence in real-life applications. Nonetheless, this progression operates under the assumption that the input feature space of the streaming data remains constant. In this survey paper, we address the topic of online learning in the context of haphazard inputs, explicitly foregoing such an assumption. We discuss, classify, evaluate, and compare the methodologies that are adept at modeling haphazard inputs, additionally providing the corresponding code implementations and their carbon footprint. Moreover, we classify the datasets related to the field of haphazard inputs and introduce evaluation metrics specifically designed for datasets exhibiting imbalance. The code of each methodology can be found at https://github.com/Rohit102497/HaphazardInputsRevie

Forearm bone mineral density in postmenopausal Indian women: correlation with calcium nutrition

Background: Osteoporosis is characterized by low bone mass with micro architectural deterioration of bone tissue leading to enhanced bone fragility, thus increasing the susceptibility to fracture. This study was conducted with the objective of measuring forearm bone mineral density in postmenopausal Indian women and to establish a correlation with indices of calcium nutrition i.e. dietary calcium intake, calcium supplements, serum calcium, serum phosphorus, serum alkaline phosphatase and serum intact parathyroid hormone.Methods: Fifty healthy, ambulatory postmenopausal women were selected and a prospective observational study was conducted to correlate the BMD with indices of calcium nutrition. Patient’s laboratory investigations (serum calcium, serum phosphorous, serum alkaline phosphatase and serum intact parathyroid hormone were done and BMD was assessed with dual-energy X-ray absorptiometry at non-dominant forearm; T-scores and Z-score were derived. Correlation analysis was done to investigate the relationship between indices of calcium nutrition and BMD.Results: The proportion of osteoporosis in forearm was 22%in the deficient group, 60% in the insufficient group and 18% in the sufficient group. Among the study group 15 subjects were osteoporotic by T score mid forearm where as 7 were osteoporotic with T score ultra distal forearm and 11 subjects had osteoporosis with T score total forearm.Conclusions: Out of all the indices of calcium nutrition, the correlation between the serum alkaline phosphatase and T score forearm was statistically significant

Interim report for the International Muon Collider Collaboration

This document summarises the International Muon Collider Collaboration (IMCC) progress and status of the Muon Collider R&D programme