Massive Growth Research Articles

Brazilian national production of active pharmaceutical ingredients: regulatory and strategic framework.

Active Pharmaceutical Ingredient (API) is any component of the final pharmaceutical product that serves as the active ingredient. The goal of the API Manufacturing is to produce APIs that are competitively priced and meet the quality standards with the least possible impact on the environment. The global API market is expected to experience massive growth in the coming years reaching the size of USD 355.94 billion. The global Pharmaceutical Industry is facing a new scenario in 2023 after responding to the COVID-19 pandemic. In this new panorama, rethinking the pharmaceutical production and market is necessary. Despite Brazil's prominence in terms of worldwide pharmaceutical spending, only 5% of the APIs required by local pharmaceutical companies are produced domestically. Therefore, Brazil is an untapped field for APIs' manufacturing and faces a scenario of health vulnerability associated with the reliance on foreign API imports to ensure the viability of national Pharmaceutical Production and Services. Huge investments are required to boost the growth of the API Manufacturing sector. Herein is presented a critical analysis of the current regulatory and strategic status of Brazilian national production and/or acquisition of APIs, which represent the key starting materials for the Pharmaceutical Industry.

Semantic Relevance Learning for Video-Query Based Video Moment Retrieval

The task of video-query based video moment retrieval (VQ-VMR) aims to localize the segment in the reference video, which matches semantically with a short query video. This is a challenging task due to the rapid expansion and massive growth of online video services. With accurate retrieval of the target moment, we propose a new metric to effectively assess the semantic relevance between the query video and segments in the reference video. We also develop a new VQ-VMR framework to discover the intrinsic semantic relevance between a pair of input videos. It comprises two key components: a Fine-grained Feature Interaction (FFI) module and a Semantic Relevance Measurement (SRM) module. Together they can effectively deal with both the spatial and temporal dimensions of videos. First, the FFI module computes the semantic similarity between videos at a local frame level, mainly considering the spatial information in the videos. Subsequently, the SRM module learns the similarity between videos from a global perspective, taking into account the temporal information. We have conducted extensive experiments on two key datasets which demonstrate noticeable improvements of the proposed approach over the state-of-the-art methods.

Uncontrolled Urban Growth in Western Balkans Territories after the Communist Collapse—a Review from the Spatial Planning Perspective

With the fall of the Communist Regimen in the Western Balkans Region, governance politics regarding urban and spatial planning processes led to significant changes in several territorial aspects. In this regard, several scientific studies and researches have put forward significant regional differences in urban development between cities of the Balkans that have followed very similar trajectories after the collapse of the “communist empire,” considering their willingness and desire to meet European standards - Tirana, Podgorica, Sarajevo are just some examples. Between the several disparities, these territories represent compared to Central and North European regions, massive and uncontrolled urban growth has been verified – catalyzed by liberal governance politics and private companies, without planning experts, and jeopardizing the need to include public participation in the development processes. This situation has led to significant uncontrolled planning and, consequently, to several negative social-economic impacts driven by it. For this reason, the development of a detailed review study considering spatial planning perspectives in the Western Balkans Region is seen as pivotal to understanding the existing planning disparities that affect the sustainable development of this area. Through an exploratory methodology – using both case study approach methods and territorial impact assessment (TIA) - it will be possible to understand how these events occurred and evolved, enabling the development of specific tools and approaches which might help to minimize the cumulative impacts of these processes. Therefore, the outcomes will define guidelines regarding urban planning processes for the main actors responsible for developing new governance measures toward achieving European standards.

The State of Public Space in Lusaka

Lusaka, a city of around three million people, faces massive urban growth challenges. Designed on the Garden City planning paradigm principles, the city currently lacks open public recreational spaces. The lack of public space is often linked to the high land value alongside the high demand for housing, the lack of national government prioritization of public space provision policies, and a general lack of financial resources available to Lusaka's local council.This article explores the state of formal public spaces in Lusaka, its urban history, development patterns, and the effects of these factors on everyday life and social interactions. It also outlines different private sector attempts to make up for the lack of public spaces through the provision of private green spaces (e.g., green private entertainment centres, private play parks, private back yards, and front yards) and the commercial units and malls that cover some public space functions. It asks questions on where kids play (e.g., private play parks, mall play parks, etc.) and highlights the design elements preventing streets from becoming lively public spaces (e.g., walls and roads).The article also examines Lusaka's plans for creating green and open spaces networks inside the city and their applicability. It studies public space provision plans in Lusaka's Development Plan 2030 and older public space provision attempts. It highlights the urgency and the importance of taking serious steps towards public space provision in the city now. The article used field research, mapping, desktop research, and interviews.

Strategi Komunikasi Dinas Pariwisata Dalam Melakukan Promosi Di Kota Medan

This article aims to find out the communication strategy of the Medan City Tourism Office. During the current pandemic, the tourism sector experienced a significant decline in tourists. Ironically, some tourist attractions were closed to prevent the spread of the virus. In the new normal era, tourism is currently trying to recover the number of tourists. This study uses a library approach. Data was collected through media analysis and observation. The results of the study show that the strategy implemented on the Medan City Tourism Office's social media is tourism content, events, business and organizational structure. This strategy is considered not very effective because there is no massive tourist growth yet.

Implementation of Micro Business Productive Assistance for UMKM as an Effort to Grow a Sustainable Economy

This article discusses the Analysis of Micro Business Productive Assistance (BPUM) for Micro, Small, and Medium Enterprises (UMKM) as an effort to Grow and Develop a Sustainable Economy in East Kalimantan, so to explore the topics discussed, this research uses literature study research sourced from theories relevant to the problems in this study, Findings in this study that Micro Business Productive Assistance provides stimulus effective in improving and strengthening UMKM institutions amid the problems faced such as the Covid-19 pandemic and previous UMKM problems. The findings in this study make the conclusion that BPUM is effective in a certain time but in the context of sustainable economic growth, UMKM receiving BPUM are not always able to rely on this program. This is because this program is not sustainable and follows the system of state financial mechanisms available. This means that UMKM must be able to maximize BPUM optimally and be able to make their services progress and sustainable. The massive economic growth of UMKM, followed by strengthening through a creative economy and targeting aspects of the global market, will make UMKM able to survey all issues. So that the impact caused by the existence of a sustainable and creative economy UMKM in the digitalization era makes economic growth in the region increase with the addition of Gross Domestic Product (GDP) and National Income (PN). For BPUM assistance to East Kalimantan UMKM as a whole in 2021 has been realized effectively and optimally, but in 2022 there are several mechanisms that are still not running in several regions and there is a reduction in budget assistance deposited into UMKM

Dynamic Partitioning and Popularity based Caching for Optimized Performance in content-centric fog networks: DPPCOP

With the massive growth of information generation, processing, and distribution in the Internet of Things (IoT), the existing cloud architectures need to be designed more effectively using fog networks. The current IP-address-based Internet architecture is unable to deliver the desired Quality-of-Service (QoS) towards the increasing demands of fog networking-based applications. To this end, Content-Centric Networking (CCN) has been developed as the potential future Internet architecture. CCN provides name-based content delivery and is established as an architecture for next-generation fog applications. The CCN-based fog environment uses the cache of in-network fog nodes to place the contents near the end-user devices. Generally, the caching capacity of the fog nodes is very small as compared to the content catalog size. Therefore, efficient content placement decisions are vital for improving the network performance. To enhance the content retrieval performance for the end-users, a novel content caching scheme named “Dynamic Partitioning and Popularity based Caching for Optimized Performance (DPPCOP)” has been proposed in this paper. First, the proposed scheme partitions the fog network by grouping the fog nodes into non-overlapping partitions to improve content distributions in the network and to ensure efficient content placement decisions. During partitioning, the scheme uses the Elbow method to obtain the “good” number of partitions. Then, the DPPCOP scheme analyzes the partition’s information along with the content popularity and distance metrics to place the popular contents near the end-user devices. Extensive simulations on realistic network topologies demonstrate the superiority of the DPPCOP caching strategy on existing schemes over various performance measurement parameters such as cache hit ratio, delay, and average network traffic load. This makes the proposed scheme suitable for next-generation CCN-based fog networks and the futuristic Internet architectures for industry 4.0.

Solar, Wind and Their Hybridization Integration for Multi-Machine Power System Oscillation Controllers Optimization: A Review

Massive growth in global electrical energy demand has necessitated a genuine exploration and integration of solar and wind energy into the electrical power mix. This incorporation goes a long way in improving the cumulative generated power capacity of the power system. However, wind and solar photovoltaic (PV) are intermittent in nature, making the provisioning of a good maximum power tracking (MPPT) scheme necessary. Furthermore, the integration is characterized by synchronization challenges and introduces various modes of power system oscillations as it is converter-driven. This greatly affects the overall stability of the integrated power mix. Consequently, various technological models have been designed to address these challenges ranging from MPPT schemes, phase-lock loop (PLL), virtual synchronous generator (VSG), power system stabilizers (PSS), flexible AC transmission system (FACTS), coordinated control and artificial intelligence (AI). In this work, a multi-machine power system model is reviewed for integration stability studies. Various technical solutions associated with the integration are also reviewed. MPPT, PLL, VSG, PSS, FACTS, coordinated control, and various optimization technique schemes used for damping controller design are discussed.

Global Trends in Knowledge Production and the Evolving Peer Review Process

This essay thus seeks to provide further critique and clarity to the peer review process and the ways in which management of peer review is evolving. These changes occur within a context of massive growth in the knowledge production process: global trends, information technologies, and policies that encourage more people globally to take part in the research process. Associated with these global changes are stressors on the peer review process and particularly questions about who gets to be a peer reviewer and who has the right to produce knowledge under these processes. Less a formal review and analysis of peer review across LIS, this essay takes the form of an autoethnographic narrative that that seeks to draw upon the researcher’s personal observations, experience, and reflections to critically examine changes to the peer review system that are taking place.

THE IMPACT OF BRAND AUTHENTICITY AND BRAND COMMUNITY ON BRAND TRUST AND MSME GROWTH IN BUKALAPAK PARTNER APPLICATION USERS

The massive growth of SMEs gave an opportunity to the tech industry in creating innovations. Applications with advanced and user-friendly features offered SMEs owners an opportunity to enlarge their businesses. This study’s objective is to discuss the impact of brand authenticity and brand community towards brand trust and SME growth in case of users of Mitra Bukalapak applications. This study uses bootstraping methods as the framework of theory analysis. In data collection, the study is using purposive sampling methtods to 362 community members of Mitra Bukalapak users. The result of this study found that brand consistency, brand customer orientation, brand community has a positive impact on brand trust, and brand trust has a positive impact on SME growth. Therefore, the study will contribute to current knowledge in the tech industry to build the brand and provide information on the impact of brand value development for the SME owners.

Training Generations of Clinician Educators: Applying the Novel Clinician Educator Milestones to Faculty Development

Training Generations of Clinician Educators: Applying the Novel Clinician Educator Milestones to Faculty Development

Islamic Stock Market Performance Pre-COVID-19: Empirical Evidence from Jakarta Islamic Index

Islamic stock market has experienced massive growth globally, including in Indonesia. This study aims to investigate the predicting factors of the Indonesian Islamic stock market that presents by the stock price of the Jakarta Islamic Index (JII). Adopted the Augmented Distributed Lag (ARDL) approach, this study uses monthly data from January 2007 to February 2020. This study uses five macroeconomic variables, namely consumer price index, exchange rate, crude oil price, world gold price, and Dow Jones Islamic Index (DJIM), to determine the JII's stock price. As a result, the JII's price volatility is significantly driven by the macroeconomic variables simultaneously. Importantly, this study reports that world gold price and DJIM return to become the most crucial factors influencing the ' 'JII's stock price volatility in short and long-run investment periods. This study has passed robustness checks by conducting three out of sample periods, namely 25%, 50%, and 75% out of sample. The 75% and 50% out of sample data revealed an identical result. Thus, this study suggests that the investor evaluates the crude oil price and world gold price fluctuation to predict the price of JII. This study offers practical implications for policymakers and practitioners and recommendations for future research.

Definition of the induction time for CO2 and CH4 hydrate via evaluation of the heat released during the process and the gas consumption rate.

The induction period is defined as the time required to obtain a detectable quantity of hydrates during their natural or artificial production. This period includes the initial nucleation phase and part of the following massive growth phase. Several methods were thought to measure its length: the most adopted are the visual observation of the process and the direct measure of the temperature increase. However, these techniques are not always feasible and their accuracy is often low. This work deals with the definition of the induction time by considering the heat produced during the process, which is proportional to the temperature but significantly less affected by the stochastic nature of the process. In order to prove the feasibility of the process, the results were then compared with what obtained by considering the gas consumption rate to measure the induction time. The proposed method was validated for methane hydrates. The same confirmation was not possible for carbon dioxide hydrates, due to the high solubility in water of this species and the consequent overestimation of the gas consumption during the process.

Recommendation System with Biclustering

The massive growth of online commercial data has raised the request for an automatic recommender system to benefit both users and merchants. One of the most frequently used recommendation methods is collaborative filtering, but its accuracy is limited by the sparsity of the rating dataset. Most existing collaborative filtering methods consider all features when calculating user/item similarity and ignore much local information. In collaborative filtering, selecting neighbors and determining users' similarities are the most important parts. For the selection of better neighbors, this study proposes a novel biclustering method based on modified fuzzy adaptive resonance theory. To reflect the similarity between users, a new measure that considers the effect of the number of users' common items is proposed. Specifically, the proposed novel biclustering method is first adopted to obtain local similarity and local prediction. Second, item-based collaborative filtering is used to generate global predictions. Finally, the two resultant predictions are fused to obtain a final one. Experiment results demonstrate that the proposed method outperforms state-of-the-art models in terms of several aspects on three benchmark datasets.

Blockchain and artificial intelligence-empowered smart agriculture framework for maximizing human life expectancy

The massive population growth and rising environmental issues raise several challenges in the agriculture sector, such as agricultural land scarcity, overuse of pesticides, and global food demand. To meet global food demand, farmer uses large quantities of pesticides to enhance crop quality and quantity. However, consuming food from pesticide crops reduces human life expectancy. To overcome the aforementioned issue and improve human life expectancy, we proposed a blockchain and artificial intelligence (AI)-empowered smart agriculture framework to predict pesticide crop’s beyond the threshold. The blockchain is integrated to confront the data manipulation attack, where the crop that uses minimum pesticides is securely stored inside the blockchain’s immutable ledger. Finally, the proposed framework is evaluated with performance metrics, such as accuracy, blockchain scalability, and latency. The result shows that the proposed framework outperforms in terms of accuracy, scalability, and latency compared to the baseline approaches.

COVID-19, global health and climate change: Causes and convergences

Despite massive global economic growth and advances in science and medicine with spectacular aggregate and individual improvements in health and life expectancy over the past century, the world has now become severely unstable in multiple domains – biological, sociological, political, ecological, economic, and health care. These pervasive instabilities are organically interactive within a complex world system that has reached crisis status at local, global, and planetary levels. Lying at the heart of this complex crisis are long-neglected disparities in health and well-being within and between countries, the refusal to face how these and climate change have arisen, and how economic considerations have fuelled the trend towards entropy (gradual decline of the planet into disorder). The critical point we have reached, starkly highlighted by the emergence of the COVID-19 pandemic pari passu with ongoing climate change and planetary degradation, reminds us of our global interconnectedness with each other and with nature. Comprehending and acknowledging the myriad, humanly constructed forces in each of these domains influencing all aspects of life, are the first steps towards effectively facing challenges to our health, our humanity (collectivity as humans) and our planet. Overcoming denial, acknowledging the magnitude and complexity of these challenges, prescient vision and dedicated action capable of fostering the cooperation for overcoming obstacles are now vital to seeking peaceful pathways towards more equitable and sustainable lives. South Africa is a microcosm of the world, with its local threats and challenges mirroring the global. Significance: Instabilities that pervade the world, highlighted by the COVID-19 pandemic, are especially significant for South Africa, where they manifest most starkly because of its apartheid legacy, its relative success economically on the African continent, and the implications of ongoing widening disparities and antagonism amongst South Africa’s diverse people. Belief in moving towards narrowing wide disparities through decolonisation and reversion to an ‘idyllic African heritage’ via a transformation that includes widespread corruption, and the ANC government’s perverse erosion of lives today and in the future through ‘state capture’, intensifies rather than ameliorates our predicament in an era when cooperation and a clear vision of current threats and future possibilities are desperately needed. In an accompanying article, potential pathways towards a better future are offered through suggested shifts in paradigms of thought and action.

Assessment of Nutritional Status and Dietary Practices Among School-Going Adolescents in Rural and Urban Area: A Comparative Study

The nutritional status of adolescents is of utmost importance as this stage of life accounts for the massive growth and maturation of the human body. Substandard nutritional status during adolescence is a significant determinant of health outcomes later in life. Objectives: To assess and compare the nutritional status and dietary habits of school-going adolescents in rural and urban areas. Methods: A cross-sectional study was conducted to assess the nutritional status of adolescents from different schools in rural and urban areas. A total of 100 participants were selected through the non-probability sampling technique. Participants were assessed using a standardized questionnaire that included a food frequency questionnaire (FFQ), socio-demographic, nutritional knowledge and eating habits. Data was then entered and analyzed using SPSS version 24.0. Among 100 participants, 50 were male, and 50 were female. All-inclusive participants were between 14-17 years of age. Results: In rural areas, 40% of the students were underweight, whereas, in urban areas, only 26% were underweight. However, the percentage of normal body mass index was equal. The prevalence of the overweight category was two times greater in urban areas, 16%, compared to 8% in the rural area. Mostly urban area students consumed more junk rather than natural foods and homemade foods, which were more common among rural students. Comparatively, rural students were more undernourished and leaner. Conclusion: Nutritional status of students from both areas was different from each other by a considerable margin but collectively was insufficient and poor.

Implementasi Strategi Branding Guna Memperkuat Brand Image dan Brand Value CV Mandiri Kopi

A business certainly must have a strong branding strategy in order to realize the vision and mission of a business. In the midst of an increasingly massive market growth and development, of course this has an impact on the increasing number and development of various businesses in the community, including the coffee business. The coffee business is growing well from upstream to downstream. More and more similar businesses make the competition tougher and of course a good branding strategy is needed. The strengthening of brand value and brand image in terms of can strengthen the purchase intention by consumers. This community service program is expected to be able to provide assistance to the coffee business of CV Mandiri Kopi so that it can strengthen the brand and is expected to increase coffee sales.
 Keywords: brand value, brand image, and purchase intention.

Hybrid-attention based Feature-reconstructive Adversarial Hashing Networks for Cross-modal Retrieval

With the massive growth of data of various modal types, people no longer use a single modal retrieval method, but a cross-modal retrieval method when performing retrieval tasks. Such methods often need to store data efficiently while maintaining the characteristics of fast query. Because the hashing learning method can represent the original high-dimensional data through a simple and compact binary hash code, which can greatly compress the data size and facilitate data storage and mutual retrieval, the cross-modal hashing retrieval has gradually become a hot topic in recent years. However, how to bridge the gap between modalities to improve the retrieval performance further is still a challenging problem. In order to solve this problem, we propose a Hybrid-attention based Feature-reconstructive Adversarial Hashing (HFAH) networks for cross-modal retrieval. First, a label semantic guidance module is introduced to guide the extraction process of text features and image features through the learning of labels, so as to fully maintain the semantic similarity between different modal data. Then, the hybrid-attention module is introduced to make the extracted data contain richer semantic information. Finally, the feature reconstruction network is used to make the relevant degree between similar cross-modal data pairs higher than that between dissimilar data pairs. Related experiments on two benchmark datasets confirm to us that HFAH performs better than several existing cross- modal retrieval methods.

Semantic-aware multi-task learning for image aesthetic quality assessment

In recent years, image aesthetic quality assessment has attracted considerable attention due to the massive growth of digital images in social platforms and the Internet. However, automatically assessing aesthetic quality of an image is a challenging task, because image aesthetic is affected by various factors, and the criteria for judging the aesthetic of images with diverse semantic information are different. To this end, a Semantic-Aware Multi-task convolution neural network (SAM-CNN) for evaluating image aesthetic quality is proposed in this paper. The network can fuse intermediate features of different layers at different scales in CNN to obtain a more comprehensive and accurate aesthetic expression, under the joint supervision of image aesthetic quality assessment task and semantic classification task in a multi-task learning manner. Besides, by applying the attention mechanism, semantic information with a large receptive field extracted from deep layers is utilised to guide the network to focus on the key parts of features to be fused, to improve the effectiveness of feature fusion. Experimental results on the AVA dataset and Photo.net dataset demonstrate the effectiveness and superiority of the proposed SAM-CNN.