New Horizons For Research Research Articles

Computing Edge Irregularity Strength of Star and Banana Trees Using Algorithmic Approach

After the Chartrand definition of graph labeling, since 1988 many graph families have been labeled through mathematical techniques. A basic approach in those labelings was to find a pattern among the labels and then prove them using sequences and series formulae. In 2018, Asim applied computer-based algorithms to overcome this limitation and label such families where mathematical solutions were either not available or the solution was not optimum. Asim et al. in 2018 introduced the algorithmic solution in the area of edge irregular labeling for computing a better upper-bound of the complete graph \(es(K_n)\) and a tight upper-bound for the complete \(m\)-ary tree \({es(T}_{m,h})\) using computer-based experiments. Later on, more problems like complete bipartite and circulant graphs were solved using the same technique. Algorithmic solutions opened a new horizon for researchers to customize these algorithms for other types of labeling and for more complex graphs. In this article, to compute edge irregular \(k\)-labeling of star \(S_{m,n}\) and banana tree \({BT}_{m,n}\), new algorithms are designed, and results are obtained by executing them on computers. To validate the results of computer-based experiments with mathematical theorems, inductive reasoning is adopted. Tabulated results are analyzed using the law of double inequality and it is concluded that both families of trees observe the property of edge irregularity strength and are tight for \(\left\lceil \frac{|V|}{2} \right\rceil\)-labeling.

Research on spiritual struggles: A brief snapshot focusing on new horizons

Abstract Many people experience spiritual struggles – experiences of tension, strain, or conflict around religious or spiritual matters. Empirical, psychological research on spiritual struggles has increased greatly in the past several decades. To date, much of the emphasis has been on developing and refining assessment tools and documenting links with emotional distress. Building on several recent reviews of spiritual struggle research (Pargament & Exline 2021; Pargament & Exline 2022) as well as our own recent projects on spiritual struggles, our aim in this article is to look toward the future: What are some promising new horizons in research on spiritual struggles? We will focus on four broad areas: 1) conceptualization, assessment, and methods, 2) connections between struggles and indicators of distress or problems, 3) how struggle might foster growth, and 4) clinical interventions.

Supply Chain Elastic Strain

The introduction of the concepts of shear elastic strain (ε−) and tensile elastic strain (ε+) is a catalyst for new horizons of research into supply chain elasticity. Functional formulas encompassing the metrics of ε− and ε+, their critical point, maximum strain value, and similar parameters are established through rigorous mathematical derivations. The supply chain elasticity of agricultural commodities, including grains, apples, and wheat, are assessed by utilizing the derived formulas. The results show that the metrics of supply chain elastic strain serve as direct metrics of measuring the supply chain’s anti-interference capability, and they also facilitate an objective assessment of the supply chain’s safety and stability. The formula is succinctly derived, and it yields objective outcomes with general applicability, particularly suited for research and application for supply chain elasticity.

Vanishing lung syndrome a rare cause of dwindling of lungs in children with pulmonary tuberculosis

Vanishing lung syndrome (VLS) or idiopathic giant bullous disease is a rare condition characterized by giant emphysematous bullae, classically presenting as a slowly enlarging bulla that compresses normal lung parenchyma and causes mediastinal shift, leading to increasing dyspnea and reduced exercise tolerance. Intermittent sudden worsening of symptoms may be seen because of secondary pneumothorax due to rupture of these bullae. Here we present three cases of vanishing lung syndrome in children due to tuberculosis (TB). Reports on VLS due to TB are bare minimum. In contrast to most of the published case reports, our cases had a moderate to rapid progression, bilateral extensive bullae and isoniazid which has been traditionally thought to be the causative factor was not used in one of our patients. All three are female patients arising new horizons of research regarding whether there is any sex predominance.

Soliton solutions of nonlinear stochastic Fitz-Hugh Nagumo equation

This study deals with the stochastic Fitz-Hugh Nagumo (FHN) equation and its multiple soliton solutions. The underlying model has numerous applications in neuroscience that express the pulse behavior of neurons. In general, different kinds of noise affect neurons, e.g., oscillations in the opening and closing of ion stations within cell membranes and the fluctuations of the different conductivities in the system. This fluctuation creates a sequence of stochastic excitation. Various applications are branching Brownian motion process, flame propagation, nuclear reactor theory, autocatalytic chemical reaction, mobility in neurons, population growth in the open environment, and liquid environment. So, need of the hour to consider the FHN equation under the impact of noise. The ϕ6\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\phi ^6$$\\end{document}-model expansion method is used to extract the analytical solutions that give a dynamic attitude of the transmission for the nerve impulses of a nervous system. The different constraint conditions for the existence of these solutions are also discussed. The solutions of this model are represented in hyperbolic, trigonometric, and rational forms. The 2 and 3-dimensional behavior of these solutions are depicted by choosing the different values of parameters. The impact of noise on the physical system is analyzed and its real-world applications are discussed. The spikes in the solutions are controlled through the Borel function. These important results will open a new horizon of research for the young researchers.

Academia-pharmaceutical industry linkage: An academic perspective.

The pharmaceutical sector in Pakistan has grown over a period, however, there are several barriers in the framework governing the growth of the country's pharmaceuticals. The lack of academia-industry linkage (AIL) is among the critical barriers; hence the focus of the study is to find out the reasons for the lack in the above collaboration. Understanding barriers may help their redressal. This qualitative phenomenology-based study has been conducted in the most prominent pharmacy institutes, located in Lahore, Islamabad, Peshawar, Sargodha, and Quetta. Academic participants, with a minimum experience of 10 years and designation of assistant professor or above were recruited with a two-stage selection process, purposive sampling and snowball sampling. The data were collected using semi-structured interviews with academic experts. Thematic content analysis was employed to conclude the data. Analysis of data yielded 8 themes with 18 codes. The main reasons for neglected AIL were explained by a partial or complete lack of industrial research and development activities. Other key factors for the scarcity of AILs were the lack of positive attitude from both industry and academia, applied research in academics, and the research and development of the new molecules in the pharmaceutical industry. Support by the government and the drug regulatory authority of Pakistan in terms of regulatory and academic policies was also perceived to be absent. New horizons in research and development could be opened by providing applied research to industry, including but not limited to new molecule development. Academia-industry linkage could be boosted with government-backed funded projects and policies. Academia should focus on the industrial-demanded applied research.

Exploring the complex interplay: gut microbiome, stress, and leptospirosis.

Leptospirosis, a re-emerging zoonotic disease, remains a significant global health concern, especially amid floods and disasters such as the Kakhovka Dam destruction. As is known, the stress that occurs in the conditions of military conflicts among civilian and military personnel significantly affects susceptibility to infectious diseases and possibly even influences their course. This review aims to explore how the gut microbiome and stress mediators (such as catecholamines and corticosteroids) might impact the leptospirosis disease course. The review opens new horizons for research by elucidating the connections between the gut microbiome, stress, and leptospirosis.

Thermoelectrically Driven Dual-Mechanism Regulation on SERS and Application Potential for Rapid Detection of SARS-CoV-2 Viruses and Microplastics.

Electric-induced surface-enhanced Raman scattering (E-SERS) has been widely studied for its flexible regulation of SERS after the substrate is prepared. However, the enhancement effect is not sufficiently high in the E-SERS technology reported thus far, and no suitable field of application exists. In this study, a highly sensitive thermoelectrically induced SERS substrate, Ag/graphene/ZnO (AGZ), was fabricated using ZnO nanoarrays (NRs), graphene, and Ag nanoparticles (NPs). Applying a temperature gradient to the ZnO NRs enhanced the SERS signals of the probe molecules by a factor of approximately 20. Theoretical and experimental results showed that the thermoelectric potential enables the simultaneous modulation of the Fermi energy level of graphene and the plasma resonance peak of Ag NPs, resulting in a double enhancement in terms of physical and chemical mechanisms. The AGZ substrate was then combined with a mask to create a wearable thermoelectrically enhanced SERS mask for collecting SARS-CoV-2 viruses and microplastics. Its SERS signal can be enhanced by the temperature gradient created between a body heat source (∼37 °C) and a cold environment. The suitability of this method for virus detection was also examined using a reverse transcription-polymerase chain reaction and SARS-CoV-2 virus antigen detection. This work offers new horizons for research of E-SERS, and its application potential for rapid detection of the SARS-CoV-2 virus and microplastics was also studied.

МЕТОДИКА ОЦЕНКИ И УПРАВЛЕНИЕ РАЗВИТИЕМ СОЦИАЛЬНО-ЭКОНОМИЧЕСКИХ МЕЗОСИСТЕМ

The article is focused on the consideration of the concept of mesosism in the context of management by socio-economic development. It also provides a methodology for assessing and managing the development of socioeconomic mesosystems. The article proposes a number of methods that will allow assessing the level of development of socio-economic systems for further development of measures to improve their management efficiency. Systemic economics considers the concept of “mesoeconomics” mainly in the context of the economic sphere, focusing on the regional dimension [Kleiner 2006]. At the same time, it is advisable to expand the conceptual framework to include the following aspects in the field of mesoeconomics research: – Industry clusters and ecosystems – groups of interconnected enterprises and organizations united by a single industry specialization, common technologies and markets; – Local economic systems – autonomous territorial entities with their own resources, production base and infrastructure, but interacting with the external environment; – Global value chains – networks of interconnected enterprises and organizations engaged in joint activities for the production and distribution of goods and services on a global scale. The development of the theoretical foundations of mesoeconomics will allow not only to study, but also to manage those objects, contributing to an increase in the efficiency of the economic system as a whole. It will require the involvement of an interdisciplinary approach combining methods of systems analysis, economics, sociology and other sciences. Thus, mesoobjects take the modern economy beyond the neoclassical paradigm, opening up new horizons for research and practical application. The system economy, expanded on the basis of the proposed concepts, serves as a promising theoretical basis for building mesoeconomical models and developing effective management mechanisms.

Salivary microbial diversity – an investigation on possible biomarkers for polycystic ovarian syndrome from eastern India

Introduction and aim. Polycystic ovarian syndrome (PCOS) is one of the major reproductive health issues, thought to be multifactorial, needs serious attention as a dual burden (health and economic) mainly for developing countries like India, due to its rapid rise (30%) in the last couple of years. Therefore, widespread and liberal screening for this disorder towards prognosis, diagnosis and intervention seems to be an urgent area of research. In this background, the present study attempts to unravel the association of salivary microbial diversity and PCOS. Material and methods. To achieve the purpose 100 clinically diagnosed PCOS individuals and 110 age matched non-PCOS participants from Bengalee Hindu caste population, West Bengal, India was considered. Obtained salivary samples were identified with 16S rDNA amplification and microbial diversity were determined by Alu I restriction enzyme digestion. Results. The present study revealed an explicit pattern of DNA fragment lengths varied between 200 bp and 225 bp in PCOs in comparison to the non-PCOS group. Conclusion. The cardinal feature of the present study as the first attempt from India envisaged, utilization of salivary microbial diversity as an additional potential and economizing biomarker for PCOS that stimulate new horizon of research in 21st century’s anthropology – the anthropology of microbes.

Influence of Pre-sowing Seed Treatments with Botanical and Organics on Yield Attributing Traits and Seedling Parameters of Cluster Bean (Cyamopsis tetragonoloba L) Variety: RGC1066

The current global scenario firmly emphasizes the need to enhance eco-friendly agriculture practices for sustainable agriculture. Chemical agriculture has made an adverse impact of the health care of not only soil but also the beneficial soil microbial communities and the plants cultivated in these soil. This eventually has led to a high demand of botanical and organic produce by the present day health conscious society and periodic attempts are being made by farmers all over the world to depollute. Application of heavy doses of chemical fertilizers and pesticides are being used by the farmers to get a better yield of various agricultural crops. These chemical fertilizers and pesticides decrease soil fertility and cause health problems to the consumers. The new approaches to the use of botanical and organic amendments in farming have proven to be effective means of improving soil structure, enhancing soil fertility and increasing crop yields. Botanical and organics play vital roles in increasing soil fertility and increasing yield. The study was designed to check the response of botanical and organics on yield and seedling quality parameters such as field emergence percent, plant height (30, 60, 90 DAS), days to 50% flowering, number branches per plant, number of pods per plant, number of clusters per plant, days to maturity, seed yield per plant, seed yield per plot, harvest index, germination percentage, speed of germination, root length, shoot length, seedling length, seedling dry weight, seedling fresh weight, seedling growth rate, root: shoot ratio, seed metabolic efficiency, mobilization efficiency, vigour index-I, vigour index-II, electrical conductivity. For this experiment the seeds of RGC1066 variety collected from department of genetics and plant breeding, Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj during 2021-2022, to find out the influence of pre-sowing seed treatments with botanical and organics, seeds treated with panchagavya, beejamruth, jeevamruth, neem leaf extract and vermiwash at different concentrations viz 2, 3, 5, and 10% for 12hours along with control (no treatment). It is found that all treatments showed improved performance than untreated seeds, but it was observed that seeds treated with panchagavya@10% for 12 hours performed better in comparison to other treatments. This study can be helpful to reach new horizons of research in the field of sustainable agriculture, natural resource conservation and seed technology to overcome the germination problem and improve crop growth and yield eventually.

CSR reporting in Arab countries: the emergence of three genres

PurposeThis paper aims to explain how companies in the region of Arab countries respond to the institutional diffusion of a new communication genre like corporate social responsibility (CSR) reports.Design/methodology/approachAnalysis of the features, content and language of CSR reports published by listed companies in the region, to classify the genres of these reports and infer results about ways of companies’ interaction with newly institutionalized genre.FindingsThree distinct genres are identified: “sustainability reports genre,” “professional CSR report genre” and “light CSR report genre.” When companies interact with institutionally diffused genres, they either adopt them and re-enforce their distinctiveness, mix them with elements from other genres so their distinctiveness will be diluted, or produce the old and established genres under the new name so the new genre will lose its distinctiveness.Originality/valueThe proposed classification of CSR report genres and ways of companies’ interaction with new genres are original and open new horizons for research in social and environmental accounting and corporate communication fields.

A Study on Big Data Analytics Tools

In this digital era, the emerging trends and technologies such as Internet of things and cloud computing really deals with huge and huge volume of data [1]. [3]Big Data Analytics has been gaining much focus of attention lately as researchers from industry and academia are trying to effectively extract and employ all possible knowledge from the overwhelming amount of data generated and received. Study of these massive data requires many levels to extract knowledge for decision making. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques [2]. Such huge data has to be studied and handled to extract knowledge from these datasets. Hence Big Data analysis is a current research area that mainly explore the potential impact of big data challenges, various tools used for big data analysis. This article deals with big data at numerous levels and opens a new horizon for researchers.

Solving Two-Person Zero-Sum Stochastic Games With Incomplete Information Using Learning Automata With Artificial Barriers.

Learning automata (LA) with artificially absorbing barriers was a completely new horizon of research in the 1980s (Oommen, 1986). These new machines yielded properties that were previously unknown. More recently, absorbing barriers have been introduced in continuous estimator algorithms so that the proofs could follow a martingale property, as opposed to monotonicity (Zhang et al., 2014), (Zhang et al., 2015). However, the applications of LA with artificial barriers are almost nonexistent. In that regard, this article is pioneering in that it provides effective and accurate solutions to an extremely complex application domain, namely that of solving two-person zero-sum stochastic games that are provided with incomplete information. LA have been previously used (Sastry et al., 1994) to design algorithms capable of converging to the game's Nash equilibrium under limited information. Those algorithms have focused on the case where the saddle point of the game exists in a pure strategy. However, the majority of the LA algorithms used for games are absorbing in the probability simplex space, and thus, they converge to an exclusive choice of a single action. These LA are thus unable to converge to other mixed Nash equilibria when the game possesses no saddle point for a pure strategy. The pioneering contribution of this article is that we propose an LA solution that is able to converge to an optimal mixed Nash equilibrium even though there may be no saddle point when a pure strategy is invoked. The scheme, being of the linear reward-inaction ( LR-I ) paradigm, is in and of itself, absorbing. However, by incorporating artificial barriers, we prevent it from being "stuck" or getting absorbed in pure strategies. Unlike the linear reward- ϵ penalty ( LR-ϵP ) scheme proposed by Lakshmivarahan and Narendra almost four decades ago, our new scheme achieves the same goal with much less parameter tuning and in a more elegant manner. This article includes the nontrial proofs of the theoretical results characterizing our scheme and also contains experimental verification that confirms our theoretical findings.

A review of ancestrality and admixture in Latin America and the caribbean focusing on native American and African descendant populations.

Genomics can reveal essential features about the demographic evolution of a population that may not be apparent from historical elements. In recent years, there has been a significant increase in the number of studies applying genomic epidemiological approaches to understand the genetic structure and diversity of human populations in the context of demographic history and for implementing precision medicine. These efforts have traditionally been applied predominantly to populations of European origin. More recently, initiatives in the United States and Africa are including more diverse populations, establishing new horizons for research in human populations with African and/or Native ancestries. Still, even in the most recent projects, the under-representation of genomic data from Latin America and the Caribbean (LAC) is remarkable. In addition, because the region presents the most recent global miscegenation, genomics data from LAC may add relevant information to understand population admixture better. Admixture in LAC started during the colonial period, in the 15th century, with intense miscegenation between European settlers, mainly from Portugal and Spain, with local indigenous and sub-Saharan Africans brought through the slave trade. Since, there are descendants of formerly enslaved and Native American populations in the LAC territory; they are considered vulnerable populations because of their history and current living conditions. In this context, studying LAC Native American and African descendant populations is important for several reasons. First, studying human populations from different origins makes it possible to understand the diversity of the human genome better. Second, it also has an immediate application to these populations, such as empowering communities with the knowledge of their ancestral origins. Furthermore, because knowledge of the population genomic structure is an essential requirement for implementing genomic medicine and precision health practices, population genomics studies may ensure that these communities have access to genomic information for risk assessment, prevention, and the delivery of optimized treatment; thus, helping to reduce inequalities in the Western Hemisphere. Hoping to set the stage for future studies, we review different aspects related to genetic and genomic research in vulnerable populations from LAC countries.

A Survey on Big Data Analytics: Challenges, Open Research Issues and Tools

Internet of Things and cloud computing, a huge repository of terabytes of data is generated each day from modern information systems and digital technologies. For decision making, analysis of these massive data requires a lot of efforts at multiple levels to extract knowledge. Therefore, big data analysis is a current area of research and development. The basic objective of this paper is to explore the potential impact of big data challenges, open research issues, and various tools associated with it. As a result, this article provides a platform to explore big data at numerous stages. Based on the challenges and open research issues, it opens a new horizon for researchers to develop the solution additionally. Keywords: Big data analytics; Hadoop; Massive data; Structured data; Unstructured Data

Quantum Power Flow: Revolutionizing Power Systems Analysis

This research investigates the transformative potential of Quantum Power Flow (QPF) in power systems analysis. Leveraging quantum computing principles, the study explores quantum algorithms for power flow simulations to enhance computational efficiency andsolution accuracy. The Quantum Power Flow method is introduced, addressing challenges arising from the growing complexity of power systems, especially with increased renewable energy integration. The mathematical foundation of the Quantum Power Flow method is detailed, emphasizing quantum parallelism and computational advantages. Experimental validation, simulations, and research case studies collectively establish the practical viability and versatility of the proposed quantum approach. A 5 and 3-bus power system case study illustrates its applicability.Acknowledging current quantum computing challenges, including error susceptibility, the study highlights ongoing advancements and error correction mechanisms' potential to overcome limitations. The research concludes by discussing broader implications of quantum power system analysis and outlining future research avenues. In summary, this research comprehensively explores Quantum Power Flow, offering theoretical insights and practical demonstrations. As quantum computing evolves, this study contributes to the paradigm shift in power system analysis, opening new horizons for research and application..

A Survey on Big Data Analytics: Challenges, Open Research Issues and Tools

Abstract: A huge repository of terabytes of data is generated each day from modern information systems and digital technologies such as Internet of Things and cloud computing. Analysis of these massive data requires a lot of efforts at multiple levels to extract knowledge for decision making. Therefore, big data analysis is a current area of research and development. The basic objective of this paper is to explore the potential impact of big data challenges, open research issues, and various tools associated with it. As a result, this article provides a platform to explore big data at numerous stages. Additionally, it opens a new horizon for researchers to develop the solution, based on the challenges and open research issues.

Plant growth-promoting rhizobacteria: a potential bio-asset for restoration of degraded soil and crop productivity with sustainable emerging techniques.

The rapid expansion of degraded soil puts pressure on agricultural crop yield while also increasing the likelihood of food scarcity in the near future at the global level. The degraded soil does not suit plants growth owing to the alteration in biogeochemical cycles of nutrients, soil microbial diversity, soil organic matter, and increasing concentration of heavy metals and organic chemicals. Therefore, it is imperative that a solution should be found for such emerging issues in order to establish a sustainable future. In this context, the importance of plant growth-promoting rhizobacteria (PGPR) for their ability to reduce plant stress has been recognized. A direct and indirect mechanism in plant growth promotion is facilitated by PGPR via phytostimulation, biofertilizers, and biocontrol activities. However, plant stress mediated by deteriorated soil at the field level is not entirely addressed by the implementation of PGPR at the field level. Thus, emerging methods such as CRISPR and nanotechnological approaches along with PGPR could manage degraded soil effectively. In the pursuit of the critical gaps in this respect, the present review discusses the recent advancement in PGPR action when used along with nanomaterials and CRISPR, impacting plant growth under degraded soil, thereby opening a new horizon for researchers in this field to mitigate the challenges of degraded soil.

Polysaccharide-Peptide from Trametes versicolor: The Potential Medicine for Colorectal Cancer Treatment.

The incidence and mortality of colorectal cancer have shown an upward trend in the past decade. Therefore, the prevention, diagnosis, and treatment of colorectal cancer still need our continuous attention. Finding compounds with strong anticancer activity and low toxicity is a good strategy for colorectal cancer (CRC) therapy. Trametes versicolor is a traditional Chinese medicinal mushroom with a long history of being used to regulate immunity and prevent cancer. Its extractions were demonstrated with strong cell growth inhibitory activity on human colorectal tumor cells, while the anticancer activity of them is not acted through a direct cytotoxic effect. However, the intricacy and high molecular weight make mechanistic research difficult, which restricts their further application as a medication in clinical cancer treatment. Recent research has discovered a small molecule polysaccharide peptide derived from Trametes versicolor that has a distinct structure after decades of Trametes versicolor investigation. Uncertain molecular weight and a complex composition are problems that have been solved through studies on its structure, and it was demonstrated to have strong anti-proliferation activity on colorectal cancer in vitro and in vivo via interaction with EGFR signaling pathway. It opens up new horizons for research in this field, and these low molecular weight polysaccharide peptides provide a new insight of regulation of colorectal cancer proliferation and have great potential as drugs in the treatment of colorectal cancer.