Lore: A world beyond pages

All around us are hundreds of people with years of accumulated knowledge and unique life stories. I call these people ‘Human books’. At the same time, there are people around us who want to hear the stories from these human books and glean the knowledge from their life experiences. When people realize this, they will naturally develop an urge to connect with the others and learn more from them. Unfortunately, in our increasingly impersonal and disconnected culture, we do not have a method to discover and connect with those who are interested in sharing their knowledge. I’m proposing a system which can provide a bridge between content experts and people seeking to learn

BUSINESS PERSPECTIVE E-BANKING SYSTEMS IN INDIA

The paper seeks to explore how internet or e-banking has improvised the efficiency and adequacy in the banking sector within a very short span of time, Research Design/Process in Financial Organization, Methods of Data Collection, taking into consideration the trends, challenges of E-banking, the security measures and propound a solution that can root out the fraud in e-banking. I would like to thank my professor Dr. Stephen Onu for all the guidance he is providing me for the completion of the paper. I would also want to thank Professor Prof. John Clark for helping me out with the research with the thesis topic. I would say this paper would never have been possible without them. I shall also thank my friends and family who for being supportive right from the day I have started my research work. And finally, I would like to thank Harrisburg University for providing me with all the resources and guidelines required for the research

PREDICTIVE MODEL FOR CFPB CONSUMER COMPLAINTS

Within the dynamic and highly competitive financial industry, the timely and efficient resolution of customer complaints stands as a central challenge, particularly in the intricate domain of mortgage services. The traditional processes for handling these complaints have long been recognized as laborious and resource-intensive, a situation that financial institutions, including the esteemed Wells Fargo, are keen to improve. Currently, the industry largely relies on basic data analytics for identifying trends in customer complaints. However, this approach has its limitations, especially when dealing with complaints within the mortgage services domain. In response to this challenge, this research advocates the adoption of advanced predictive models as a groundbreaking solution. These models, powered by Random Forests hold the promise of transforming the management of mortgage-related complaints fundamentally. The Random Forests model, known for its capacity to analyze complex, non- linear relationships within data, is poised to revolutionize the prediction of customer complaint resolution outcomes. By analyzing a vast dataset from the Consumer Complaint Database, comprising 3,211,591 complaints spanning a decade, the model aspires whether a mortgage-related complaint will be swiftly resolved or require an extended resolution time. The anticipated outcomes of this endeavor encompass a transformative impact on the mortgage-related complaint resolution landscape. While this research is a pivotal step forward, broader complaint categories, and further refined predictive models could enhance the efficacy of complaint management and resolution processes

NETWORK ANALYTICS FOR THE MIRNA REGULOME AND MIRNA-DISEASE INTERACTIONS

miRNAs are non-coding RNAs of approx. 22 nucleotides in length that inhibit gene expression at the post-transcriptional level. By virtue of this gene regulation mechanism, miRNAs play a critical role in several biological processes and patho-physiological conditions, including cancers. miRNA behavior is a result of a multi-level complex interaction network involving miRNA-mRNA, TF-miRNA-gene, and miRNA-chemical interactions; hence the precise patterns through which a miRNA regulates a certain disease(s) are still elusive. Herein, I have developed an integrative genomics methods/pipeline to (i) build a miRNA regulomics and data analytics repository, (ii) create/model these interactions into networks and use optimization techniques, motif based analyses, network inference strategies and influence diffusion concepts to predict miRNA regulations and its role in diseases, especially related to cancers. By these methods, we are able to determine the regulatory behavior of miRNAs and potential causal miRNAs in specific diseases and potential biomarkers/targets for drug and medicinal therapeutics

A SMART HYBRID ENHANCED RECOMMENDATION AND PERSONALIZATION ALGORITHM USING MACHINE LEARNING

In today’s age of streaming services, the effectiveness and precision of recommendation systems are crucial in improving user satisfaction. This project introduces the Smart Hybrid Enhanced Recommendation and Personalization Algorithm (SHERPA) a cutting-edge machine learning approach aimed at transforming how movie suggestions are made. By combining Term Frequency Inverse Document Frequency (TF-IDF) for content based filtering and Alternating Squares (ALS) with Weighted Regularization for filtering SHERPA offers a sophisticated method for delivering tailored recommendations. The algorithm underwent evaluation using a dataset that included over 50 million ratings from 480,000 Netflix users encompassing 17,000 movie titles. The performance of SHERPA was meticulously compared to traditional hybrid models demonstrating a 70% enhancement in prediction accuracy based on Root Mean Square Error (RMSE) metrics during training, testing and validation phases. These findings highlight SHERPAs capability to understand and cater to users’ subtle preferences representing an advancement in personalized recommendation systems

Advancing Pharmaceutical Dry Milling by Process Analytics and Robustness Testing

The objectives of this work were to implement on-line dynamic image analysis and to introduce a novel at-line flowability analyzer in pharmaceutical dry milling. We used a pilot-scale conical mill and flowability of a placebo granulate was monitored using a powder avalanching analyzer. Experiments were designed and evaluated by means of response surface methodology in conjunction with robustness testing. The process parameters impeller speed and screen size significantly affected the particle size distribution and flow rate of the milled granules. Feeder speed did not affect the particle size, but displayed a statistically significant influence on the flow responses. Robustness testing was able to capture the effect of noise factors on the responses and showed clear differences between different lots of the placebo granulate in addition to temperature-dependent changes in flow behavior. Thus, on-line dynamic image analysis and at-line flowability characterization, together as complementary process analytical tools, provided valuable information. The combined analysis was of particular interest for testing the process and noise factors so that future process development can profit from this advancement in dry millin

Enhancing resilience to climate change through prospective strategies for climate-resilient agriculture to improve crop yield and food security

It is important to highlight that agriculture is one of the sectors that will be directly affected by climate change scenarios in recent years. There are a number of processes such as drought, floods, temperature, salinity etc along with other forms of biotic factors posing significant impacts on crop yields of various crops due to their fluctuating scenario in the environment. Espousal of smart technologies and practices like smart crop and variety selection, efficient climate-based cropping system, agricultural water management (AWM), balanced fertilization, contingency planning, recarbonization of soils, no-till system, integrated farming system, site specific nutrient management etc are being advised to exercise in many regions for climate-resistant agriculture. These approaches minimize soil disruption and energy usages, enhance soil health and alleviate greenhouse gas discharges, minimize unproductive losses and improve efficiency of land and water use result in greater crop production with reduced fertilizer usage. As a part of this strategy, weather stations and mini-weather lookouts are set up at the village stage to register relevant weather observations like temperature, rainfall, wind speed and relative humidity etc to furnish customized agro-advisories to farmers, which reduce detrimental consequences attributed to the climate. A climate smart approach integrates farmer’s practices with related technologies, plans, institutes, policies and financial packages. So, initiating the choice of site-specific crops, development of customized technologies and tools, diversification of crops, improvement of climate-resistant crop varieties, syndication of forecasting tools and proper management of resources at the community level can effectively enhance climate resilience in agriculture

Recent advances in genetic manipulation of crops: A promising approach to address the global food and industrial applications

Continuous increase in world’s population demands high food production, which has become a major challenge to the humanity. When there is sufficient amount of nutritious food to all the people there will be no problem of food scarcity. So, to increase the food production, many countries are adopting strategies of genetic engineering to enhance the crop yield. Recombinant DNA technology can be a viable source to develop genetically modified crops with enhanced resistance and improved yields to fight against malnutrition and food scarcity. With this technology, selected traits can be inserted into the plant genome, unlike traditional plant breeding, where many characters of two different crops will be combined which may lead to genetic modification at an extensive level. Present review focuses on the methods of plant transformation and outlines the scope of genetic transformation for improved crop production by transferring selected genes for biotic and abiotic stress tolerance. In addition, current study also provides information about various genetically modified crops produced worldwide and their commercialization towards various biotechnological products like GM livestock, GM microorganisms, vaccines and industrial products like bio-plastic produced from the transgenic plants

DEVELOPMENT OF ZOLMITRIPTAN MOUTH DISSOLVING FILMS: FORMULATION VARIABLES, MECHANICAL PROPERTIES, AND IN VITRO DRUG RELEASE STUDIES

Objective: The objective of the present investigation is to prepare zolmitriptan (ZOL) mouth dissolving films (MDFs) and to investigate the influence of formulation variables on physicomechanical, chemical, and drug release properties of the prepared MDFs. Methods: The MDFs were prepared by solvent casting technique using wet film applicator. The impact of hydroxypropyl methylcellulose of different viscosity grades (hydroxy propyl methyl cellulose [HPMC] E3, E5, and E15), plasticizers (glycerol and polyethylene glycol [PEG]-400), and solubilizing agents (polyvinyl pyrrolidone [PVP K30] and sodium lauryl sulfate [SLS]) on physicomechanical, chemical, and drug release properties were evaluated. The MDFs were also characterized by Fourier-transform infrared spectroscopy, differential scanning calorimetry, and X-ray diffractometry studies. Results: The MDFs prepared were transparent and smooth and showed no recrystallization. The tensile strength of the MDFs increased significantly with an increase in polymer viscosities, and about a 2.63-fold increase in tensile strength was observed for HPMC E15 MDFs compared to E3, whereas an increase in film thickness resulted in brittle MDFs with low tensile strength. Similar results were observed with percent elongation and folding endurance of the MDFs. In vitro, drug release studies indicate that higher film thickness and polymer viscosities delayed the MDF disintegration and, in turn, the ZOL release. Addition of PVP K30 and SLS to HPMC E3 formulations resulted in 1.66- and 1.53-fold increase in ZOL release rates. Conclusion: Overall, F7 formulation showed quicker disintegration (within 11 s) and ZOL release rates (within 180 s) along with good physicomechanical properties. These results indicated that the disintegration and drug release of ZOL can be enhanced to a greater extent by optimizing formulation variables in MDFs