Miracle-dz/UniFAR-FTUs huggingface dataset:
Handbook of metallonutraceuticals

Concept, Definition, and Need for Metallonutraceuticals Jayant Lokhande and Yashwant Pathak Roles of Metals in Metabolism Jatin Shah and Jayant Lokhande Ethnopharmacology and Ethnomedicine of Metals Jayant Lokhande, Shriniwas Samant, Ganesh Shinde, and Yashwant Pathak Characterization of Metallonutraceuticals Jayant Lokhande and Yashwant Pathak Characterization Bioavailability and Drug Interactions of Metallonutraceuticals Charles Preuss Therapeutic Applications of Nanometals Amy Broadwater, Bhaskar Mazumder, and Yashwant Pathak Metallonanotherapeutics for Neurodegenerative Diseases Komal Vig and Shivani Soni Nanometals and Complexes in Cancer Diagnosis and Therapy Sajid Bashir, Srinath Palakurthi, Hong-Cai Zhou, and Jingbo Liu Application of Metals in Traditional Chinese Medicine Bhaskar Mazumdar, Shufeng Zhou, Jiayou Wang, and Yashwant Pathak Metalloenzymes: Relevance in Biological Systems and Potential Applications Ravi Ramesh Pathak Application of Nanosilver in Nutraceuticals Pranab Jyoti Das, Bhasker Mazumder, and Charles Preuss Regulatory Pathways and Intellectual Property Rights for Metallonutraceuticals Vishal Kataria, Jayant Lokhande, Vrinda Vedi, and Yashwant Pathak Gold Nanoparticles: A Promising Nanometallic Drug Delivery System with Many Therapeutic Applications Anastasia Groshev, Danielle Dantuma, Vaibhav Alandikar, Samuel Rapaka, Yashwant Pathak, and Vijaykumar Sutariya Index
Impact of Open Innovation Communities on Enterprise Innovation Performance: A System Dynamics Perspective

Open innovation communities (OICs) can help enterprises make full use of external knowledge resources from users, but problems such as low user participation and low conversion rate of creative ideas impact the efficiency of OICs. Most studies on this topic employ qualitative or empirical methods from a static perspective, but ignore the effect of interaction between enterprises and users as well as the cumulative effect of time. A discussion on the dynamic evolution process of open innovation is lacking. Based on a review of the literature on OICs, innovation performance, and system dynamics, this study proposes a conceptual model of innovation performance impact, which comprises the knowledge management, governance mechanism, and user behavior subsystems. Xiaomi’s OIC in China was selected as the research object, and relevant data were collected through a web spider. According to the system dynamics modeling method, a causal relationship analysis was carried out on the three aforementioned interrelated subsystems. Then, a stock flow chart with 32 variables was constructed to determine the initial values and calculation equations for each variable. Finally, the model was constructed and verified using Vensim PLE software. The simulation results were as follows. (1) The number of product releases in the Xiaomi OIC was positively correlated with the number of posts, comments, and views. Compared with user interaction behavior (i.e., commenting and viewing), the impact of user innovation behavior (i.e., posting) on enterprise innovation performance (i.e., number of patents) is clearer. Specifically, regarding interaction behavior, the impact of the users’ commenting behavior on innovation performance (i.e., number of product releases) was relatively clearer than that of their viewing behavior. (2) Governance mechanism (i.e., R&D investment and management expense), which comprises technical and organizational mechanisms, positively affected the innovation performance of enterprises. Compared with the organizational mechanism (i.e., management expense), the impact of the technical mechanism (i.e., R&D investment) on the innovation performance was clearer. (3) Governance mechanism helped to increase the number of users in the OIC, and, in turn, affected the user innovation and interaction behavior. (4) The technical mechanism positively affected knowledge application capability, which, in turn, had a positive impact on the innovation performance of enterprises. Based on these findings, management strategies are proposed for the establishment and development of OICs.
Embracing Crowdsensing: An Enhanced Mobile Sensing Solution for Road Anomaly Detection

Road anomaly detection is essential in road maintenance and management; however, continuously monitoring road anomalies (such as bumps and potholes) with a low-cost and high-efficiency solution remains a challenging research question. In this study, we put forward an enhanced mobile sensing solution to detect road anomalies using mobile sensed data. We first create a smartphone app to detect irregular vehicle vibrations that usually imply road anomalies. Then, the mobile sensed signals are analyzed through continuous wavelet transform to identify road anomalies and estimate their sizes. Next, we innovatively utilize a spatial clustering method to group multiple driving tests’ results into clusters based on their spatial density patterns. Finally, the optimized detection results are obtained by synthesizing each cluster’s member points. Results demonstrate that our proposed solution can accurately detect road surface anomalies (94.44%) with a high positioning accuracy (within 3.29 meters in average) and an acceptable size estimation error (with a mean error of 14 cm). This study suggests that implementing a crowdsensing solution could substantially improve the effectiveness of traditional road monitoring systems.
Performance Evaluation of Recurrent Neural Network on Large-Scale Translated Dataset for Question Generation in NLP for Educational Purposes

–In recent years, neural networks have been used widely to solve many NLP tasks that involve large-scale datasets. Recently, Question Generation (QG) has called great attention since it is a subtask of Question Answering (QA) that has many applications in the real world, mainly for educational purposes. The importance of it could be seen on many recently released large-scale datasets prepared exclusively for this task, most the data used in NLP are available in the English language, but it is not the case for the rest of the languages, like Spanish, which is the third most used language in the world. This research is focused on analyzing the performance of current state-of-the-art neural network models used in QG using translated Spanish large-scale dataset from English. To know the accuracy of the translated Spanish data from English, it has been used state-of-the-art OpenNMT machine translator and Google Translation API, then the results have been analyzed with the corresponding automatic metrics - BLEU, METEOR, ROUGE - and human evaluations such as fluency and adequacy, later, it has been trained a state-of-the-art question generation (QG) neural network model using Spanish translated data to generate automatic questions in Spanish language. Surprisingly, the results outperform the original English results in average 37% on all automatic evaluation metrics. To the best of our knowledge, this work is the first one using large-scale Spanish translated data for QG task using recurrent neural networks for educational purposes.
Automatic Machine Learning-Based Data Analysis For Video Game Industry

The paper analyzes the reviews and sales of video games from review websites Metacritic and VGChartz. It establishes classification and regression models through EasyDL, Vertex AI, and Azure, exploring the relationship between users and video games, media scores, and game sales. It is concluded that users' evaluations of video games are greatly influenced by media attitudes, while there may be a correlation between user evaluation and game sales. In addition, the paper also compares the results of training models on different automatic machine learning platforms. It shows that training on EasyDL is faster in general. In contrast, the training results of Vertex AI are greatly affected by data sets, and the effect of Azure is relatively balanced.
Humans in the Loop: Incorporating Expert and Crowd-Sourced Knowledge for Predictions Using Survey Data

Survey data sets are often wider than they are long. This high ratio of variables to observations raises concerns about overfitting during prediction, making informed variable selection important. Recent applications in computer science have sought to incorporate human knowledge into machine-learning methods to address these problems. The authors implement such a “human-in-the-loop” approach in the Fragile Families Challenge. The authors use surveys to elicit knowledge from experts and laypeople about the importance of different variables to different outcomes. This strategy offers the option to subset the data before prediction or to incorporate human knowledge as scores in prediction models, or both together. The authors find that human intervention is not obviously helpful. Human-informed subsetting reduces predictive performance, and considered alone, approaches incorporating scores perform marginally worse than approaches that do not. However, incorporating human knowledge may still improve predictive performance, and future research should consider new ways of doing so.
YOLO Algorithm for Helmet Detection in Industries for Safety Purpose

Using a Safety helmet is crucial for ensuring the safety of employees in the construction, power, and manufacturing sector. However, employees frequently remove their helmets due to a lack of security awareness and inconvenience, exposing themselves to further hazards. Employees without helmets would experience higher injuries in incidents like falling, electrical shock, and dropping heavy loads. As a result, fast and accurate safety helmet detection is an absolute necessity for all management. Conventional human monitoring is time-consuming and difficult to supervise employees in a large population. Because of its low accuracy and poor resilience, the industry’s conventional helmet identification method is not recommended for use. Therefore, this research offers a deep learning approach to identifying safety helmet wearing with good accuracy. Collecting the requisite images is done using the Kaggle website. A total of 5000 images are obtained, and 1000 from that will be utilized to test the DL model. Region-based Convolutional Neural Network (RCNN) and You Only Look Once (YOLO) is selected as DL model for helmet detection. The measures such as mean Average Precision (mAP), recall, and precision are used to Figure out the best model out of two. The YOLO has achieved the greatest mAP success rate of 97.12%.
Design and Optimization of High Performance SRAM Based on 110nm Process

This paper introduces the single port $2432\times 16$ bit for microprocessor based on 110nm logic low-power process. Full custom design of high-speed low-power SRAM. In the design process, in order to obtain high speed and control power consumption, the circuit and layout of 6T memory cell are newly designed. Aiming at the large capacity of this design, the memory array is partitioned and the SRAM efficiency is improved by using hierarchical decoding. After the circuit design, the whole layout of SRAM is fully customized, and the function, speed and power consumption are simulated. The working frequency of this design is 132-473MHz, the voltage range is 1.25v∼1.65v, and the area is $44925\text{um}^{\ \wedge}\ 2$. The average power consumption under 1.5V power supply voltage can reach 5.83mW, which is better than the previous design on the whole.
Anthropometry of Farm Workers of Kashmir Region of India for Equipment Design

Anthropometric data (25 body dimensions, relevant to design of farm machinery) of 610 farm workers was collected from Kashmir region of India. The comparison between the Kashmir region data and different regions of India and six foreign countries is presented. There were significant differences in weight, stature and other body dimensions between the populations. Kashmiri women were taller by 31 mm as compared to south Indian female workers, but had differences in hand length. No differences existed between stature eye height, hand length and inside grip diameter among females from Kashmir and North-eastern regions. Kashmiri women were heavier and fatter as compared to other selected regions of the country. Indian men were shorter by 75 mm as compared to Americans. The muscular strength (elbow flexion) of Indian workers was lower (241 N) as compared to Americans (270.7 N). Similarly, hand grip strength of Indian workers was lower (301.8 N) than Americans (398 N). Application of data in design of agricultural equipment is demonstrated.
Acoustic noise insulation for air-cooled data centre hard disk drive enclosures: Effect on thermal management

Modern data centres widely use hard disk drive (HDD) enclosure systems where multiple HDDs are integrated into a single rack-mounted enclosure. These systems often use forced air-cooling. However, cooling fans also produce acoustic noise and may restrict the performance of the HDD servo system. One way to control noise is to use acoustic insulation materials. However, these acoustic insulation materials may also act as thermal insulators, which can adversely influence the thermal management system performance. This paper investigates the effects of a simplified acoustic insulator and its influence on cooling system efficiency. Acoustic simulations were conducted using the Finite Element Method (FEM) in the frequency domain. Aerodynamic simulations were conducted, solving steady-state RANS equations and the energy equation.
Image Watermarking Algorithm of Embed & Extraction for RGB Noisy Images Using SVD, DCT, Arnold Transform & Error Acceptance Gabor Filter for Copyright Protection

: We are living in the age of advance technology where we are talking about the nanotechnology. As we know this era needs fast processing systems which can be perform any task in very short time. Now if we are talking about the current era so there is a most important issue is there which is pilgrims , there is lots of content which is easily copied from internet and user represent those work as there own work. We also know currently we are living in web era where anything can be copy in a few seconds. There is lots of algorithms are available which are able to protect the content but all those algorithms are not in terms of noise effect on RGB color image. So in this paper basically we present an system which is able to resolve the issue of copy right with reduction in noise issue. According to our proposed approach we are basically using the error tolerant approach according to this approach we will not utilize the complete system we are using only those apart which are require rest we simply truncate. According to our proposed approach basically we design an algorithm which will take the input RGB nosiy image and for reduction of noise we will use error acceptance DWT filter. Now as per the image water ,marking we proposed two more process which are embed & extract process to complete this process we proposed one more error acceptance based algorithms which is Arnold transform. Here we are also using Arnold algorithm but that Arnold algorithm is accurate one. Here we also discuss the applications and need of the digital watermarking applications.
Global Atlas of Palliative Care at the End of Life

Palliative care, while still a relatively new component to modern healthcare, is increasingly recognised as an essential part of all healthcare systems. Despite this, it is widely acknowledged that there is still inadequate access to hospice and palliative care worldwide, and with an ageing population who are going to be living and dying with more complex conditions, the demand for care is only going to increase.
Netsourcing: Renting Business Applications and Services Over a Network

From the Publisher: The definitive decision-maker's guide to renting business applications over a network. Netsourcing: The market, the players, the services A guide to the fast-changing netsourcing playing field Integrating netsourcing options within a total IT sourcing portfolio Even large-size customers can benefit from selective netsourcing Best practices for evaluating and selecting providers Choosing partners that fit your approach to businessand have real staying power Minimizing the risks of netsourcing partnerships Realistic best practices for managing technical, contractual, operational, and managerial risk Previewing new strategic options in netsourcing What you need to know about "next-generation" netsourcing servicesand service providers Managing the netsourcing relationship successfully Achieving the "holy grail": the "win-win" outsourcing relationship Enterprise case studies: key outsourcing successes and failures What works, and what doesn't: the experiences of today's leading global companies Netsourcing is the practice of renting or "paying as you use" access to supplier-managed business applications, made available to multiple customers over the Internet or other networks. The concept of delivering business applications as a serviceor "apps on tap"was initially called application service provision (ASP). But that term has proved too narrow. Today customers are using netsourcing to hand over entire business processes to service providers, smanage customer-grown applications. The netsourcing value proposition to customers is compelling: no upfront infrastructure costs or costly software licenses, business applications delivered in days/weeks, scalable solutions that grow or contract with the customer's business, flexible solutions with minimal switching costs, and minimal expensive in-house support staffto name a few. Given these benefits, who wouldn't want to netsource? On the downside, there are significant netsourcing risks that must be mitigated. The netsourcing of business applications is still seen as an immature option primarily offered by unstable dot.com start-ups. Business managers worry about the reliability and security of the Internet, feel that their business requirements are too idiosyncratic for canned, "one-to-many" solutions, and do not trust outsiders to supply mission-critical systems. So how can businesses leverage the value offered by netsourcing while reducing its risks? How can businesses compare and integrate netsourcing with other sourcing options? Every business is asking questions like these. Netsourcing delivers the answers. Based on unparalleled research at the world's leading enterprises, this book identifies the key factors associated with successful outsourcingfrom planning through ongoing relationship management, and beyond. The authors show you how to take full advantage of the dramatic changes roiling the outsourcing marketplace, helping you realistically assess the promise of next-generation outsourced servicesand the capabilities of the service providers who offer them.
Guest editorial for themed section Black Panther and Afrofuturism: theoretical discourse and review

This article proposes that Black Panther, with its aesthetic and thematic emphasis on Afrofuturism, as well as its spectacular technical production, makes a unique contribution to cinematic history in several significant ways. In order to establish these noteworthy contributions, both the film and Afrofuturism are engaged with. This article is divided into three distinct parts. Part I provides a brief theoretical overview of Black Panther and Afrofuturism. Part II, a short review, follows. Co-authored by Mark Kirby-Hirst, the review contextualises and analyses the film within the bounds of Afrofuturism and twenty-first century art and film criticism, in an effort to argue for the relevance and import of such a unique and yet mainstream piece of cinema history; which, we conclude, is owing in no small part to the rise in popularity of decolonising tendencies in the humanities, in art, and in wider twenty-first century visual culture. The last section of this article, Part III, provides a brief synopsis of the contributing articles to this special themed section of Image & Text.
Secure and efficient scheme for fast initial link setup against key reinstallation attacks in IEEE 802.11ah networks

IEEE 802.11ah is a recently released IEEE standard to specify a wireless communication system with a long‐range, low‐power, and low data transmission rate over smart devices used in Internet of Things (IoT) systems. This new standard belongs to IEEE 802.11 wireless local area networks (WLANs) protocol family. It requires lightweight protocols to support the low‐power and low‐latency features of the IoT devices. On the other hand, an upcoming solution of fast initial link setup (FILS) specified by IEEE 802.11ai standard is a brand‐new approach aiming to establish fast and secure links among devices in WLANs to meet this new demand. It is natural and feasible to apply it to the 802.11ah networks to support massively deployed wireless nodes. However, security concerns on the link connection by the FILS scheme have not been fully eliminated, especially in the authentication process. It has been explored that a type of recently revealed malicious attack, key reinstallation attack (KRA) might be a threat to the FILS authentication. To prevent the success of the KRAs, in this paper, we proposed a secure and efficient FILS (SEF) protocol as the optional substitute of the FILS scheme. The SEF scheme is designed to eradicate potential threats from the KRAs without degrading the network performance.
Rank-Oriented Disaster Management: The Korean Experience

ABSTRACT Rank is the position or standing in the Korean field of disaster management, whereas ability is the competence or required proficiency in carrying out appropriate disaster management. This paper aims to examine the ways to improve emphasis on rank in Korea for the ultimate goal of increasing related productivity. A qualitative content analysis with the support of descriptive approach has been used as the main methodology. With respect to this, rank-oriented disaster management has been systematically compared with ability-oriented disaster management via the five stakeholders, namely the public officials, businessmen, researchers, volunteers, and local community. The key tenet is that the nation needs to change its current rank-oriented disaster management into ability-oriented disaster management as a form of cultural change. This paper, as a pioneer study, rigorously discusses the issue of rank versus ability in the Korean field of disaster management.
Step-by-step implementation of BIM-LCA: A case study analysis associating defined construction phases with their respective environmental impacts

Building Information Modelling (BIM) supports construction processes by dealing with the variety and complexity of design in a single virtual model. The model may also be complemented by the static and energy performance of buildings. Facing the growing demand of sustainability strategies in the construction sector, the consideration of environmental information within the planning process influences the decision making of planners and stakeholders. Nevertheless, the life cycle assessment of buildings has been so far excluded in BIM, due to the high variety of accurate information and time required. In this paper, a systematic framework is presented and applied to a case study. BIM-LCA assists actors along the planning and designing phase, from the building conception as a whole, up to the elements’ details and materials’ definition. BIM and LCA intertwine in an application scheme of seven phases for integral planning and four levels of structural composition of a building. With respect to these, involved actors examine potential solutions through a tool which exploits alternative specifications in order to assess the environmental impacts. The goal of this paper is to demonstrate the application of a BIM-LCA model regarding decision making for reliable values of environmental impact in a given structural level of the building. The main findings of this framework are due to the multitude of actors and information orchestrated, namely to uncertainties which characterize the whole planning process and data handling. Through BIMLCA, actors are assisted by ensuring flexibility of models and consistency of results throughout planning and designing.