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PathAI Machine Learning Models Reveal Treatment-Induced Changes in the Non-Small Cell Lung Cancer Tumor Microenvironment in Samples from the LCMC3…

January 31, 2021 | Author: admin

BOSTON, Jan. 29, 2021 /PRNewswire-PRWeb/ --PathAI, a global provider of AI-powered technology applied to pathology research, announced that machine learning models were developed and applied on NSCLC samples from the LCMC3 trial by Genentech, a member of the Roche Group, and participating study investigators to identify predictive/prognostic biomarkers in the tumor microenvironment (TME) and perform AI-powered pathologic response assessment. A global summary of the LCMC3 primary analysis will be presented at the World Conference on Lung Cancer Symposium Singapore that will take place from January 28-31, 2021 in an oral presentation by Dr. David Carbone of The Ohio State University ("Clinical/Biomarker Data for Neoadjuvant Atezolizumab in Resectable Stage IB-IIIB NSCLC: Primary Analysis in the LCMC3 Study", January 29, 2021; Session OA06.06).

The LCMC3 study is a single arm trial that enrolled 181 participants with resectable, untreated stage IB to select IIIB NSCLC to investigate the pathologic response to atezolizumab as a neoadjuvant treatment. Biopsies were collected from all study subjects prior to neoadjuvant treatment, and surgical resections were collected after treatment from 159 subjects. Pathologic response is suggested to be associated with survival outcomes and is traditionally assessed upon evaluating the residual tumor following a course of neoadjuvant therapy. A major pathologic response (MPR), described as less than 10% viable tumor cells present in the post neoadjuvant treatment resections, was achieved in 30/144 (21%) subjects eligible for preliminary analysis, and a complete pathologic response, meaning that 0% tumor cells were present after neoadjuvant treatment, was observed in 10/144 (7%) eligible subjects. PathAI's AI-powered quantification of cell and tissue features to characterize the tumor microenvironment and analyze pathologic response is ongoing and those results will be presented at a future meeting.

In preliminary analyses, the PathAI research platform was able to identify and quantify tissue- and cell-level features in digitized whole slide images of hematoxylin and eosin (H&E)- stained biopsies and resections. ML model comparison of the TME composition pre- and post-treatment revealed quantifiable changes in histopathologic features in response to atezolizumab treatment. Furthermore, even in subjects that did not achieve a major pathologic response, these early results suggested that there may be a reduction in tumor tissue after treatment. If confirmed, this result would correlate well with other outcomes from this primary analysis that showed a significant increase in CD3+/PD1+ T cells after atezolizumab treatment, and that the presence of this cell type in the TME before treatment was associated with an observed MPR.

The data presented at WCLC highlight the potential for AI-powered pathology to reveal the architecture of the TME with the granularity necessary to understand the effect of anti-cancer agents and the biology underlying a treatment response. As treatment options become increasingly personalizable, developing robust and accurate quantitative measurements of the TME, and pathologic response to treatment will work toward enabling oncologists to provide patients with appropriate needs.

About PathAI

PathAI is a leading provider of AI-powered research tools and services for pathology. PathAI's platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine and deep learning. Based in Boston, PathAI works with leading life sciences companies and researchers to advance precision medicine. To learn more, visit http://www.pathai.com.

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Isabella Canuso, PathAI, +1 6096821080, isabella.canuso@pathai.com

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Predictions for 2021 – Machine Learning will become Ubiquitous Four Things We Need to Do Now – CXOToday.com

January 31, 2021 | Author: admin

It wasnt too long ago that concepts like communicating with your friends in real-time through text or accessing your bank account information all from a mobile device seemed outside the realm of possibility. Today, thanks in large part to the cloud, these actions are so commonplace, we hardly even think about these incredible processes. And as we enter the golden age of machine learning, we can expect a similar boom of benefits that previously seemed impossible.

Machine learning is already helping companies make better and faster decisions. In healthcare, the use of predictive models created with machine learning is accelerating research and discovery of new drugs and treatment regiments. In other industries, its helping remote villages of Southeast Africa gain access to financial services, and matching individuals experiencing homelessness with housing.

In the short term, were encouraged by the applications of machine learning already benefiting our world. But it has the potential to have an even greater impact on our society. In the future, machine learning will be intertwined and under the hood of almost every application, business process, and end-user experience. However, before this technology becomes so ubiquitous that its almost boring, there are four key barriers to adoption we need to clear first.

Democratizing machine learning

The only way that machine learning will truly scale is if we as an industry make it easier for everyone regardless of their skill level or resources to be able to incorporate this sophisticated technology into applications and business processes.

To achieve this, companies should take advantage of tools that have intelligence directly built into applications that their entire organization can benefit from. Take for example Kabbage, a data and technology company providing small business cash flow solutions, who used artificial intelligence to quickly adapt and help process an unprecedented number of small business loans and unemployment claims caused by COVID-19 while preserving more than 945,000 jobs in America. By folding artificial intelligence into personalization, document processing, enterprise search, contact center intelligence, supply chain or fraud detection, all workers can benefit from machine learning in a frictionless way.

As processes go from being manual to automatic, workers are free to innovate and invent, and companies are empowered to be proactive instead of reactive. And as this technology becomes more intuitive and accessible, it can be applied to nearly every problem imaginablefrom the toughest challenges in the IT department, to the biggest environmental issues in the world.

Upskilling workers

According to the World Economic Forum, the growth of AI could create 58 million net new jobs in the next few years. However, research suggests that there are currently only 300,000 AI engineers worldwide, and AI-related job postings are three times that of job searches with a widening divergence. Given this significant gap, organizations need to recognize that they simply arent going to be able to hire all the data scientists they need as they continue to implement machine learning into their work. Moreover, this pace of innovation will open doors and ultimately create jobs we cant even begin to imagine today.

Thats why companies around the world like Morningstar, Liberty Mutual, DBS Bank, and others are finding innovative ways to encourage their employees to gain new machine learning skills with a fun, interactive hands-on approach. Its critical that organizations should not only direct their efforts towards training the workforce they have with machine learning skills, but also invest in training programs that develop these important skills in the workforce of tomorrow.

Instilling trust in products

With anything new, often people are of two minds either an emerging technology is a panacea and global savior, or it is a destructive force with cataclysmic tendencies. The reality is more often than not, a nuance somewhere in the middle. These disparate perspectives can be reconciled with information, transparency, and trust.

As a first step, leaders in the industry need to help companies and communities learn about machine learning, how it works, where it can be applied, ways to use it responsibly, and understand what it is not.

Second, in order to gain faith in machine learning products, they need to be built by diverse groups of people across gender, race, age, national origin, sexual orientation, disability, culture, and education. We will all benefit from individuals who bring varying backgrounds, ideas, and points of view to inventing new machine learning products.

Third, machine learning services should be rigorously tested, measuring accuracy against third party benchmarks. Benchmarks should be established by academia, as well as governments, and be applied to any machine learning-based service, creating a rubric for reliable results, as well as contextualizing results for use cases.

Regulation of machine learning

Finally, as a society, we need to agree on what parameters should be put in place governing how and when machine learning can be used. With any new technology, there has to be a balance in protecting civil rights while also allowing for continued innovation and practical application of the technology.

Any organization working with machine learning technology should be engaging customers, researchers, academics, and others to best determine the benefits of its machine learning technology with the potential risks. And they should be in active conversation with policymakers, supporting legislation, and creating their own guidelines for the responsible use of machine learning technology. Transparency, open dialogue, and constant evaluation must always be prioritized to ensure that machine learning is applied appropriately and is continuously enhanced.

Whats next

Through machine learning weve already accomplished so much, and yet, its still day one (and we havent even had a cup coffee yet!). If were using machine learning to help endangered orangutans, just imagine how it could be used to help save and preserve our oceans and marine life. If were using this technology to create digital snapshots of the planets forests in real-time, imagine how it could be used to predict and prevent forest fires. If machine learning can be used to help connect small-holder farmers to the people and resources they need to achieve their economic potential, imagine how it could help end world hunger.

To achieve this reality, we as an industry, have a lot of work ahead of us. Im incredibly optimistic that machine learning will help us solve some of the worlds toughest challenges and create amazing end-user experiences weve never even dreamt. Before we know it, machine learning will be as familiar as reaching for our phones.

(The author is Swami Sivasubramanian, Vice-President, Amazon Machine Learning, AWS (Amazon Web Services)and the views expressed in the article are his own)

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Predictions for 2021 - Machine Learning will become Ubiquitous Four Things We Need to Do Now - CXOToday.com

Guilty or Not Guilty: Weight of Evidence Machine Learning Times – The Predictive Analytics Times

January 31, 2021 | Author: admin

By: Sam Koslowsky, Senior Analytic Consultant, Harte HanksYou have been invited to serve as a juror in a criminal related case. After hearing testimony, the presiding judge offers a summary of the proceeding. Evaluate the evidence, he declares. Whether it was an eyewitness account, an affidavit, an image, or a recording, it is your responsibility to assess what was heard. Although I cannot tell you how to weigh the evidence, it is your responsibility to select the significant aspects of the case. Consider the value of the information that you have examined, weigh the evidence, and formulate your verdict accordingly. While the concept of weight

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Machine learning-based PRAISE score may aid in the prediction of adverse events following an acute coronary syndrome – 2 Minute Medicine

January 31, 2021 | Author: admin

1. The PRAISE score showed accurate discriminative capabilities for the prediction of all-cause death, acute myocardial infarction, and major bleeding after an acute coronary syndrome.

2. Compared with low risk stratification, a high-risk PRAISE score was associated with a 58.8-times increase in death, 27.7-times increase in myocardial infarction, and a 32.7-times increase in major bleeding events.

Evidence Rating Level: 2 (Good)

Study Rundown: Patients with acute coronary syndrome (ACS) are at an increased risk for ischemic and bleeding events. Although several predictive tools have been developed to predict adverse events, the accuracy of these scores remains modest. It is believed that machine learning may overcome some of the limitations of current analytical approaches. This study aimed to develop and validate a machine learning-based risk stratification model to predict all-cause death, recurrent acute myocardial infarction, and major bleeding after ACS. Four machine learning models were developed to predict the occurrence of each of the three outcomes one year after discharge. According to study results, the PRAISE score showed accurate discriminative abilities for the prediction of all three outcomes, even when externally validated. Specifically, the risk of myocardial infarction was greater than the risk of major bleeding among patients classified by the PRAISE score as being high risk for myocardial infarction. In contrast, the risk of myocardial infarction was lower than the risk of major bleeding among patients classified as being low risk for infarction. This study was limited by the retrospective design of the registries used to compose the derivation cohort. Perhaps, a prospective design could have been chosen to increase the validity of the PRAISE model. Overall, this study showed that a machine learning-based approach may accurately predict the occurrence of adverse events and aid in optimizing care for patients following an ACS.

Click to read the study in The Lancet

Relevant Reading: Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs

In-depth [prospective cohort]: Patients for the derivation cohort were obtained from two registries: the BleeMACS registry (comprising 15 401 patients with ACS at 15 tertiary hospitals in America, Europe, and Asia), and the RENAMI registry (comprising 4425 patients admitted at 12 European hospitals). Altogether, the derivation cohort consisted of 19 826 patients (18 years) with ACS and 1 year follow-up data. The derivation cohort was split into two groups: a training cohort (80%) and an internal validation cohort (20%). To assess the performance of the PRAISE score, an external validation cohort of 3444 adult patients admitted to the hospital with ACS with 2 years of follow-up was used.

Area under the receiver operating characteristic curves (AUCs) of the PRAISE model (training and internal validation cohort) for all three outcomes were similar to the external validation cohort. In the internal validation cohort, AUCs for 1-year all-cause death, 1-year myocardial infarction, and 1-year major bleeding were 0.82 (95% confidence interval [CI], 0.78-0.85), 0.74 (95% CI, 0.70-0.78), and 0.70 (95% CI, 0.66-0.75), respectively. For the external validation cohort, AUCs for 1-year all-cause death, 1-year myocardial infarction, and 1-year major bleeding were 0.92 (95% CI, 0.90-0.93), 0.81 (95% CI, 0.76-0.85), and 0.86 (95% CI, 0.82-0.89), respectively. Compared to the low-risk group, being in the high-risk group increased the risk of death by 58.8 times, myocardial infarction by 27.7 times, and major bleeding events by 32.7 times. While predictors varied based on study outcomes, left ventricular ejection fraction (LVEF), age, hemoglobin level, and statin therapy were important predictors for 1-year all-cause death. Meanwhile, hemoglobin level, age, LVEF, and estimated glomerular filtration rate (EGFR) were important predictors of both 1-year myocardial infarction and major bleeding risk. Findings from this study show that a machine learning-based approach for the identification of predictors of events after an ACS is effective and may help guide clinical decision making.

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2020 2 Minute Medicine, Inc. All rights reserved. No works may be reproduced without expressed written consent from 2 Minute Medicine, Inc. Inquire about licensing here. No article should be construed as medical advice and is not intended as such by the authors or by 2 Minute Medicine, Inc.

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Latest News Why Should Python Be Used in Machine Learning? – Analytics Insight

January 31, 2021 | Author: admin

Machine learning is essentially making a PC to play out a task without expressly programming it. In this day and age, each framework that does well has a machine learning algorithm at its heart. Machine learning is at present probably the most sizzling topics in the business and organizations have been racing to have it consolidated into their products, particularly applications

As indicated by Forbes, Machine learning patents developed at a 34% rate somewhere between 2013 and 2017 and this is simply set to increment later on. Furthermore, Python is the essential programming language utilized for a significant part of the innovative work in Machine Learning. To such an extent that Python is the top programming language for Machine Learning as indicated by Github

Machine learning isnt just utilized in the IT business. Machine learning likewise plays an important role in advertising, banking, transport, and numerous different businesses. This innovation is continually advancing, and subsequently, it is methodically acquiring new fields in which it is an integral part.

Python is a high-level programming language for overall programming. Besides being an open-source programming language, python is an extraordinarily interpreted, object-oriented, and interactive programming language. Python joins surprising power with clear syntax. It has modules, classes, special cases, significant level dynamic data types, and dynamic composing. There are interfaces to numerous system calls and libraries, as well as to different windowing frameworks.

Easy and Fast Data Validation

The job of machine learning is to identify patterns in data. An ML engineer is answerable for harnessing, refining, processing, cleaning, sorting out, and deriving insights from data to create clever algorithms. Python is easy while the topics of linear algebra or calculus can be so perplexing, they require the maximum amount of effort. Python can be executed rapidly which allows ML engineers to approve an idea immediately.

Different Libraries and Frameworks

Python is already very well-known and thus, it has many various libraries and frameworks that can be utilized by engineers. These libraries and frameworks are truly valuable in saving time which makes Python significantly more well-known.

Code Readability

Since machine learning includes an authentic knot of math, now and then very troublesome and unobvious, the readability of the code (also outside libraries) is significant if we need to succeed. Developers should think not about how to write, but rather what to write, all things considered.

Python developers are excited about making code that is not difficult to read. Moreover, this specific language is extremely strict about appropriate spaces. Another of Pythons advantages is its multi-paradigm nature, which again empowers engineers to be more adaptable and approach issues utilizing the simplest way possible.

Low-entry Barrier

There is an overall shortage of software engineers. Python is not difficult to get familiar with a language. Hence, the entry barrier. is low. Whats the significance here? That more data scientists can become experts rapidly and thus, they can engage in ML projects. Python is fundamentally the same as the English language, which makes learning it simpler. Because of its easy phrase structure, you can unhesitatingly work with complex systems.

Portable and Extensible

This is a significant reason why Python is so mainstream in Machine Learning. So many cross-language tasks can be performed effectively on Python due to its portable and extensible nature. There are numerous data scientists who favor utilizing Graphics Processing Units (GPUs) for training their ML models on their own machines and the versatile idea of Python is appropriate for this.

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Mining Automation Market Competitive Research and Technology Outlook 2020 to 2025 The Courier – The Courier

January 31, 2021 | Author: admin

The Mining Automation Market Research Report 2020-2025, offers an in-depth evaluation of each crucial aspect of the Global Mining Automation industry that relates to market size, share, revenue, demand, sales volume, and development in the market. The report analyzes the Mining Automation market over the values, historical pricing structure, and volume trends that make it easy to predict growth momentum and precisely estimate forthcoming opportunities in the Mining Automation Market. The report explores the current outlook in global and key regions (North America, Europe, Asia-Pacific, and Latin America) from the perspective of players, countries (U.S., Canada, Germany, France, U.K., Italy, Russia, China, Japan, South Korea, Taiwan, Southeast Asia, Mexico, and Brazil, etc.), product types, and end industries.

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Global Major Players in Mining Automation Market are:Caterpillar, Volvo Group, Sandvik, Komatsu, ABB, Atlas Copco, Rockwell, Hitachi, Micromine, Hexagon, Trimble, Mine Site Technologies, Remote Control Technologies, and Other.

Most important types of Mining Automation covered in this report are:Underground Mining Automation

Surface Mining Automation

Most widely used downstream fields of Mining Automation market covered in this report are:Metal Mining

Mineral Mining

Coal Mining

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Influence of the Mining Automation Market report:Comprehensive assessment of all opportunities and risks in the Mining Automation Market.Mining Automation Market recent innovations and major events.A detailed study of business strategies for the growth of the Mining Automation Market market-leading players.Conclusive study about the growth plot of Mining Automation Market for forthcoming years.In-depth understanding of Mining Automation Market, market-particular drivers, constraints, and major micro markets.Favorable impression inside vital technological and market latest trends striking the Mining Automation Market.

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What are the market factors that are explained in the report?

-Key Strategic Developments: The study also includes the key strategic developments of the market, comprising R&D, new product launch, M&A, agreements, collaborations, partnerships, joint ventures, and regional growth of the leading competitors operating in the market on a global and regional scale.

-Key Market Features: The report evaluated key market features, including revenue, price, capacity, capacity utilization rate, gross, production, production rate, consumption, import/export, supply/demand, cost, market share, CAGR, and gross margin. In addition, the study offers a comprehensive study of the key market dynamics and their latest trends, along with pertinent market segments and sub-segments.

-Analytical Tools: The Global Mining Automation Market report includes the accurately studied and assessed data of the key industry players and their scope in the market by means of a number of analytical tools. The analytical tools such as Porters five forces analysis, SWOT analysis, feasibility study, and investment return analysis have been used to analyze the growth of the key players operating in the market.

The research includes historic data from 2015 to 2020 and forecasts until 2025 which makes the reports an invaluable resource for industry executives, marketing, sales and product managers, consultants, analysts, and other people looking for key industry data in readily accessible documents with clearly presented tables and graphs.

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Bio Based Construction Polymer Market | Scope,Demand by Regions, Key Vendors landscape, And Growth Forecast | SK Chemicals, BASF SE, Evonik Industries…

January 31, 2021 | Author: admin

The Bio Based Construction Polymer Marketreport mainly encompasses fundamental dynamics of the market which include drivers, restraints, opportunities and challenges faced by the industry.It provides valuable insights with an emphasis on global market including some of the major players.The report puts a light on the market structures, driving forces, scope, and competitive landscape for your business whichhelps ineffortless decision-making process.

The report displays the systematic investigation of current scenario of the market, which covers several market dynamics. The principal areas of market analysis such as market definition, competitive analysis,market segmentation, and research methodology are studied very vigilantly and precisely throughout the report.

Market Definition & Scope:

Bio based construction polymer market will reach an estimated valuation of USD 38.36 billion by 2027 from USD 17.51 billion in 2019, while registering this growth at a rate of 10.30% for the forecast period of 2020 to 2027. Data Bridge Market Research report on bio based construction polymer market provides analysis and insights regarding the various factors expected to be prevalent throughout the forecasted period while providing their impacts on the markets growth.Increasing awareness regarding environmental impacts of petroleum-based construction polymers will help impact the bio based construction polymer market growth in the forecast period.

Competitors Analysis:CompetitorsProfiles Includes: Overview, Product & Services Offerings, Financials,New Developments and Innovation

The major players covered in the bio based construction polymer market report are SK Chemicals, BASF SE, Evonik Industries, NatureWorks LLC, Tate & Lyle, Hiusan Biosciences, Kaneka Corporation, BEWiSynbra Group, Metabolix, Mitsubishi Gas Chemical Company Inc., Bio-On, Toyobo Co. Ltd., DuPont de Nemours Inc., Teijin Limited and PolyOne Corporation among other domestic and global players. Market share data is available for global, North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America separately. DBMR analysts understand competitive strengths and provide competitive analysis for each competitor separately.

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Bio Based Construction Polymer Market report covers the different market scenarios that have direct impact on the growth of the market. The report is structured with the meticulous efforts of an innovative, enthusiastic, knowledgeable and experienced team of analysts, researchers, industry experts, and forecasters. In the end, the report makes some important proposal of the new project of Bio Based Construction Polymer industry before evaluating its feasibility.

Report includes analysis on:

Key Market Development:

The report provides in-depth information about profitable showing markets and analyzes the markets for the global Bio Based Construction Polymer market. It provides full information about new product launches, current developments, and investments in the global market. The report delivers an complete evaluation of market shares, strategies, products, and manufacturing capabilities of the top players in the global market.

For Any Enquiry or Specific Requirement Speak to Our Analyst @https://www.databridgemarketresearch.com/speak-to-analyst/?dbmr=global-bio-based-construction-polymer-market

This Bio Based Construction Polymer report provides Scope of the market where it identifies industry trends, determines brand awareness and influence, provides industry insights and offers competitive intelligence. Bio Based Construction Polymer Market report includes noteworthy information alongside future conjecture and point by point market scanning on a worldwide, regional and local level for the industry.

Key Pointers in Table of Content:

Chapter 1. Research Objective1.1 Objective,Definition & Scope1.2 Methodology1.2.1 Primary Research1.2.2 Secondary Research1.2.3 Market Forecast Estimation & Approach1.2.4 Assumptions & Assessments1.3 Insights and Growth Relevancy Mapping1.4 Data mining & efficiency

Chapter 2. Executive Summary2.1 Bio Based Construction Polymer Market Overview2.2 Interconnectivity & Related markets2.3 Bio Based Construction Polymer Market Business Segmentation2.4 Bio Based Construction Polymer Market Geographic Segmentation2.5 Competition Outlook2.6 Key Statistics

Chapter 3. Strategic Analysis3.1 Bio Based Construction Polymer Market Revenue Opportunities3.2 Cost Optimization3.3 Covid19 aftermath Analyst view

Chapter 4. Market Dynamics4.1 DROC4.1.1 Drivers4.1.2 Restraints4.1.3 Opportunities4.1.4 Challenges4.2 PEST Analysis4.2.1 Political4.2.2 Economic4.2.3 Social4.2.4 Technological4.3 Market Impacting Trends4.4 Porters 5-force Analysis

Chapter 5. Segmentation & Statistics5.1 Segmentation Overview5.2 Demand Forecast & Market SizingContinued..

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Caprylic Acid Market | Present Scenario, Key Vendors, Industry Share, and Growth Forecast up to 2027 | Vigon International Inc., IOI, Forchem Oyj KSU…

January 31, 2021 | Author: admin

The Caprylic Acid Marketreport mainly encompasses fundamental dynamics of the market which include drivers, restraints, opportunities and challenges faced by the industry.It provides valuable insights with an emphasis on global market including some of the major players.The report puts a light on the market structures, driving forces, scope, and competitive landscape for your business whichhelps ineffortless decision-making process.

Market Definition & Scope:

Caprylic acid market will reach an estimated valuation of USD 7.72 million by 2027 from USD 3.82 million in 2019, while registering this growth at a rate of 9.20% for the forecast period of 2020 to 2027. Data Bridge Market Research report on caprylic acid market provides analysis and insights regarding the various factors expected to be prevalent throughout the forecasted period while providing their impacts on the markets growth.Rising health concerns, associated with rising demand for nutrition and dietary supplements will help impact the caprylic acid market growth in the forecast period.

Competitors Analysis:CompetitorsProfiles Includes: Overview, Product & Services Offerings, Financials,New Developments and Innovation

The major players covered in the caprylic acid market report are Vigon International Inc., IOI, Forchem Oyj, Oleon NV., Arizona Chemicals, Kuala Lumpur Kepong Berhad, Interfat, Oxiteno, MeadWestVaco, Wilmar International Ltd., Felda, Spectrum Chemical Manufacturing Corp and CREMER OLEO GmBH & Co. KG among other domestic and global players. Market share data is available for global, North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America separately. DBMR analysts understand competitive strengths and provide competitive analysis for each competitor separately.

Download Free PDF Sample Report with Statistical info @https://www.databridgemarketresearch.com/request-a-sample/?dbmr=global-caprylic-acid-market

Caprylic Acid Market report covers the different market scenarios that have direct impact on the growth of the market. The report is structured with the meticulous efforts of an innovative, enthusiastic, knowledgeable and experienced team of analysts, researchers, industry experts, and forecasters. In the end, the report makes some important proposal of the new project of Caprylic Acid industry before evaluating its feasibility.

Report includes analysis on:

Key Market Development:

The report provides in-depth information about profitable showing markets and analyzes the markets for the global Caprylic Acid market. It provides full information about new product launches, current developments, and investments in the global market. The report delivers an complete evaluation of market shares, strategies, products, and manufacturing capabilities of the top players in the global market.

For Any Enquiry or Specific Requirement Speak to Our Analyst @https://www.databridgemarketresearch.com/speak-to-analyst/?dbmr=global-caprylic-acid-market

This Caprylic Acid report provides Scope of the market where it identifies industry trends, determines brand awareness and influence, provides industry insights and offers competitive intelligence. Caprylic Acid Market report includes noteworthy information alongside future conjecture and point by point market scanning on a worldwide, regional and local level for the industry.

Key Pointers in Table of Content:

Chapter 2. Executive Summary2.1 Caprylic Acid Market Overview2.2 Interconnectivity & Related markets2.3 Caprylic Acid Market Business Segmentation2.4 Caprylic Acid Market Geographic Segmentation2.5 Competition Outlook2.6 Key Statistics

Chapter 3. Strategic Analysis3.1 Caprylic Acid Market Revenue Opportunities3.2 Cost Optimization3.3 Covid19 aftermath Analyst view

Chapter 5. Segmentation & Statistics5.1 Segmentation Overview5.2 Demand Forecast & Market SizingContinued..

Get Full Table of Contents with Charts, Figures & Tables @ https://www.databridgemarketresearch.com/toc/?dbmr=global-caprylic-acid-market

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Caprylic Acid Market | Present Scenario, Key Vendors, Industry Share, and Growth Forecast up to 2027 | Vigon International Inc., IOI, Forchem Oyj KSU...

Apple goes after Facebook, Google with its pro-privacy PR move | NewsBytes – NewsBytes

January 31, 2021 | Author: admin

Apple CEO Tim Cook made a commitment to privacy while speaking at the Computers, Privacy, and Data Protection conference.

Calling it one of the top issues of the century, Cook asserted that privacy should be assigned the same weight as climate change.

Cook's statements were cleverly coordinated with Apple releasing a document taking a jab at its competitors' privacy policies.

Apple has clearly used the opportunity to go for Facebook and Google's jugular since their very business models are predicated on profiting off user data.

Cook's carefully orchestrated pro-privacy speech has been well coordinated with the official document aimed at educating the public of the privacy pitfalls associated with the company's Big Tech rivals.

There could be a tech war brewing on the horizon.

Cook took the opportunity to distance Apple from the data mining and other predatory privacy practices of the rest of its Big Tech brethren.

He was particularly against the "broad-brush categorization" of being lumped in with the likes of Facebook and Google, whose very business models involve making money off user data.

The Apple CEO encouraged people to think deeper and understand their business model.

However, exhorting people to think deeper could backfire for Apple.

Because that will also make them come across instances of Apple lobbying the US government to weaken a forced labor bill, which would prevent it from manufacturing iPhones using Uighur concentration camp detainees.

While Apple might not be entirely like its Big Tech peers, it still finds other ways to be evil.

While Cook waxes eloquent on Apple's commitment to privacy, the company has a checkered past on that count.

On one hand, Apple refused the FBI's request to unlock an iPhone belonging to a perpetrator of the San Bernardino terrorist attack, but then it was also caught secretly recording and listening in on customers in another instance, where it was forced to issue an apology.

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Apple goes after Facebook, Google with its pro-privacy PR move | NewsBytes - NewsBytes

Algae Oil Market | Scope,Demand by Regions, Key Vendors landscape, And Growth Forecast | Diversified Energy Corporation, Algix LLC, Cellana Inc. KSU…

January 31, 2021 | Author: admin

The Algae Oil Marketreport mainly encompasses fundamental dynamics of the market which include drivers, restraints, opportunities and challenges faced by the industry.It provides valuable insights with an emphasis on global market including some of the major players.The report puts a light on the market structures, driving forces, scope, and competitive landscape for your business whichhelps ineffortless decision-making process.

Market Definition & Scope:

Algae are microscopic plants which are produced from marine algae, which is extracted and then refined. They are found in all types of aquatic environments such as marine, freshwater, and brackish water. Algae oil is rich in docosahexaenoic acid & omega 3 fatty acids.Algae oil market is expected to gain market growth in the forecast period of 2020 to 2027. Data Bridge Market Research analyses the market to account 2.3 billion by 2027 growing with the CAGR of 4.40% in the above-mentioned forecast period. Increasing demand for dietary supplements due to rising awareness among working professionals towards weight management is a major factor escalating the market growth.

Competitors Analysis:CompetitorsProfiles Includes: Overview, Product & Services Offerings, Financials,New Developments and Innovation

The major players covered in algae oil market report are Diversified Energy Corporation, Algix LLC, Cellana Inc., DIC CORPORATION, DSM, Cyanotech Corporation Cellana Inc, Cargill, Incorporated., BIOPROCESS ALGAE, LLC., Alltech., Lonza. Luna Business Advantage Ltd., Seaweed Energy Solutions AS, Algae Floating Systems Inc., RAE, among other domestic and global players. Market share data is available for global, North America, Europe, Asia-Pacific (APAC), Middle East and Africa (MEA) and South America separately. DBMR analysts understand competitive strengths and provide competitive analysis for each competitor separately.

Download Free PDF Sample Report with Statistical info @https://www.databridgemarketresearch.com/request-a-sample/?dbmr=global-algae-oil-market

Algae Oil Market report covers the different market scenarios that have direct impact on the growth of the market. The report is structured with the meticulous efforts of an innovative, enthusiastic, knowledgeable and experienced team of analysts, researchers, industry experts, and forecasters. In the end, the report makes some important proposal of the new project of Algae Oil industry before evaluating its feasibility.

Report includes analysis on:

Key Market Development:

The report provides in-depth information about profitable showing markets and analyzes the markets for the global Algae Oil market. It provides full information about new product launches, current developments, and investments in the global market. The report delivers an complete evaluation of market shares, strategies, products, and manufacturing capabilities of the top players in the global market.

For Any Enquiry or Specific Requirement Speak to Our Analyst @https://www.databridgemarketresearch.com/speak-to-analyst/?dbmr=global-algae-oil-market

This Algae Oil report provides Scope of the market where it identifies industry trends, determines brand awareness and influence, provides industry insights and offers competitive intelligence. Algae Oil Market report includes noteworthy information alongside future conjecture and point by point market scanning on a worldwide, regional and local level for the industry.

Key Pointers in Table of Content:

Chapter 2. Executive Summary2.1 Algae Oil Market Overview2.2 Interconnectivity & Related markets2.3 Algae Oil Market Business Segmentation2.4 Algae Oil Market Geographic Segmentation2.5 Competition Outlook2.6 Key Statistics

Chapter 3. Strategic Analysis3.1 Algae Oil Market Revenue Opportunities3.2 Cost Optimization3.3 Covid19 aftermath Analyst view

Chapter 5. Segmentation & Statistics5.1 Segmentation Overview5.2 Demand Forecast & Market SizingContinued..

Get Full Table of Contents with Charts, Figures & Tables @ https://www.databridgemarketresearch.com/toc/?dbmr=global-algae-oil-market

About Us:

Data Bridge Market Research

Tel: +18883872818

corporatesales@databridgemarketresearch.com

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Algae Oil Market | Scope,Demand by Regions, Key Vendors landscape, And Growth Forecast | Diversified Energy Corporation, Algix LLC, Cellana Inc. KSU...

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Apple goes after Facebook, Google with its pro-privacy PR move | NewsBytes – NewsBytes

Algae Oil Market | Scope,Demand by Regions, Key Vendors landscape, And Growth Forecast | Diversified Energy Corporation, Algix LLC, Cellana Inc. KSU…

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