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At the first annual Conference on Machine Intelligence in Medical Imaging (C-MIMI), held in September 2016, a conference session on medical image data and datasets for machine learning identified multiple issues. The common theme from attendees was that everyone participating in medical image evaluation with machine learning is data starved. There is an urgent need to find better ways to collect, annotate, and reuse medical imaging data. Unique domain issues with medical image datasets require further study, development, and dissemination of best practices and standards, and a coordinated effort among medical imaging domain experts, medical imaging informaticists, government and industry data scientists, and interested commercial, academic, and government entities. High-level attributes of reusable medical image datasets suitable to train, test, validate, verify, and regulate ML products should be better described. NIH and other government agencies should promote and, where applicable, enforce, access to medical image datasets. We should improve communication among medical imaging domain experts, medical imaging informaticists, academic clinical and basic science researchers, government and industry data scientists, and interested commercial entities.
The first annual Conference on Machine Intelligence in Medical Imaging (C-MIMI) was held on September 12–13, 2016, in Alexandria, Virginia, under the auspices of the Society for Imaging Informatics in Medicine (SIIM). This paper summarizes a conference session which discussed medical image data and datasets for machine learning. It also reviews unique domain issues with medical image datasets.
The amount and quality of training data are dominant influencers on a machine learning (ML) model's performance. The common theme from all attendees was that everyone participating in medical image evaluation with machine learning is data starved. This is a particularly pressing problem in the new era of deep learning [1]. There is an urgent need to find ways to collect and reuse medical imaging data. Beyond this universal primary sentiment, the session identified a diverse set of challenges, described here.
The Ideal Dataset for Medical Imaging Machine Learning
The ideal medical image dataset for an ML application has adequate data volume, annotation, truth, and reusability. At base, each medical imaging data object contains data elements, metadata, and an identifier. This combination represents an "imaging examination." A collection of data objects or dataset must have enough imaging examinations to answer the question being asked. To maximize algorithm development, both the dataset itself and each imaging examination must be described and labeled accurately. Ground truth, the classification label(s) of each imaging examination, should be as accurate and reproducible as possible. Furthermore, an ideal dataset is Findable, Accessible, Interoperable, and Reusable (FAIR) [2]. In the coming sections, we will describe features of machine learning datasets.
Use Cases
Use case is a computer science term that defines actions or steps performed by an actor and a system to achieve a particular goal [3]. When it comes to medical imaging ML, we tend to think of use cases as clinical questions: Can image texture be used to predict MGMT methylation status of brain tumors [4], or can we distinguish frontal from lateral chest radiographs? [5] Other use cases could be administrative, prioritize work within a queue, or otherwise facilitate machine and/or human workflow.
An ideal use case defines a project which is specific, measurable, and achievable, and has well-defined users and value. Use cases also help to illustrate standards, or the need for standards. Creating a good ML proposal is similar to creating a good research question—it should be carefully designed, and measurable.
Use cases can be made for medical imaging datasets themselves: appropriately annotated datasets that can be used to train, test, validate, and verify machine learning algorithms. The value to industry, academia, and the public is that machine learning algorithms will improve healthcare outcomes and reduce healthcare costs. Customers of these datasets will be industry, academic, and governmental researchers and regulatory bodies. Each customer will have different aims including building machine learning products, gaining new insights from medical images beyond human perception, and understanding how to verify and regulate machine learning products that consume and process medical image data.
Use cases for medical ML datasets vary considerably. Academicians may be satisfied with small, tightly focused datasets to efficiently answer focused questions that result in publications and further funding. In contrast, industry desires data of sufficient volume, variety, and quality to make ML models that work in disparate online production environments. Commercial medical image ML products will need independent verification and potential FDA approval. Verification datasets should include data elements that stress or even break an ML product, to understand its limits, biases, and even potential ethical issues. The larger data science and business analytics communities may federate and mine these datasets for new insights. As the value of these datasets becomes better appreciated, data repositories and data publishing entities, whether public, commercial, or academic, will develop business cases around these datasets. Machines will define their own use cases; over time, this scenario may be the prime originator of new use cases.
Machine learning competitions, such as those hosted on http://kaggle.com, may define distinctive dataset use cases depending on competition goals. Datasets may be close to their raw form, or in other cases transformed into an anonymized feature matrix easily consumed by standard supervised machine learning algorithms. Competitions that use medical image datasets typically transform data: limit to a relevant subset of rows, alter or remove columns, choose an error metric, split the data into train/validation/test sets, and try to identify and mitigate potential sources of data leakage. In the next section, we will shift to describing metadata important to machine learning datasets.
Dataset Specifications—Metadata
Metadata for medical imaging ML include data generated by an imaging modality, prescribed exam codes and description data based on an order, and annotations indicating the content and/or anatomy of a particular image. Table 1 shows examples of commonly available metadata elements. As shown in Table 1, there are a variety of original sources of metadata and associated storage mechanisms. There are a variety of challenges to making metadata easily understood by a computer or algorithm. These challenges arise at both the institutional level and when sharing data between institutions.
Consider the procedure description for an MR study performed to evaluate rectal cancer staging. Today, some centers would consider this an MRI Pelvis Without Contrast, and other centers would have a more specific description such as MRI Rectal Cancer Staging. It is relatively easy for a human reading a radiology report to identify these discrepancies. Furthermore, it is likely that the centers that have more specific study descriptions started with something more generic, so the task of retrieving all studies related to rectal cancer screening from an archive requires institutional knowledge, and takes longer (and costs more) than one might expect.
An additional wrinkle with exchanging data across institutions is study description heterogeneity between institutions. This can be addressed by asking all institutions to utilize institutional knowledge to map local study descriptions to the RadLex playbook [6]. This type of mapping is reasonable for focused use cases, but becomes unwieldy when trying to build larger federated datasets without automated tools [7].
Dataset Specifications—Metadata—DICOM Header
Digital Imaging and Communications in Medicine (DICOM) is the standard file format definition and communication profile for radiological and many other medical images. The DICOM file format contains required and optional metadata fields which describe the patient, exam details, and, in many cases, individual image details. The individual image details described in DICOM metadata typically relate to technical aspects of the image (e.g., rows, columns, modality, manufacturer) rather than an inclusion of a particular organ, or diagnosis. The major benefit of DICOM is that it provides a standard for medical image storage and a set of network operations for transmission and retrieval. In practice, however, data fields may be filled incorrectly or left blank, some with interoperable and others with proprietary data [8]. While DICOM issues usually do not interfere with clinical image viewing, they may cause complex problems when federating datasets. In some instances, de-identifying datasets may result in the removal of metadata that is required for advanced processing. In competitions, occasionally DICOM metadata quirks improve algorithm performance, but are generalizably applicable outside the competition.
Dataset Specifications—Metadata—Private Tags
DICOM allows private data elements, and these are commonly used by individual OEMs and individual healthcare institutions to enable distinctive workflow. Occasionally, these include personal health information (PHI), pathology-related identifiers, or specific research or clinical protocols.
The DICOM standard is rich with specifications that are underutilized by vendors. One such specification is structured reporting (DICOM-SR) [9,10,11]; hopefully, this will come into greater use in the future for storing a particular type of metadata—annotations.
Dataset Specifications—Metadata—Annotations
For this paper, we consider annotations as a special class of metadata that pertain to the diagnoses, or anatomical or pathological regions contained within a particular image (Fig. 1). Challenges with annotations fall into main two categories: interoperability and ground truth.
Computer-based image recognition and analysis require high-quality, annotated datasets that cover the entities described in the use case, including normal cases and those with pathology ranging from very subtle findings to very severe. Well-annotated datasets with representative label distribution are crucial to training accurate, generalizable models. Additionally, due to the large volume of image data required for many ML projects, new annotation tools focused on efficiency and rapid annotation are needed. Keen researchers will focus on producing datasets in a manner that allows their robust use in algorithm development, validation, and certification.
Unfortunately, and not without effort by several parties, there is no universally applied syntax, format, or semantic for radiologic image annotation and markup. Commercial vendors use proprietary annotations and markups, few of which are interoperable. The Annotation and Image Markup (AIM) standard has been successful as a research tool, but has not been widely implemented clinically [12]. DICOM presentation state objects are a competing standard for storing and transmitting annotations, which provides less functionality than AIM. Currently, this means that measurements or regions of interest made in one vendor's workstation will not appear when the images are moved and viewed on a different vendor's viewing platform, and labels may have different meanings or definitions without use of some unified or standardized vocabulary. Annotations overlaid on images may include PHI, clinical or pathology information, arrows, question marks, or other potentially important but not easily discoverable or understandable data.
Robust solutions to segment anatomic structures are now available for many organs, but the process is not standardized. Segmentation annotations are rarely transferable among vendors. Standards to document how a segmentation was performed do not exist, or are proprietary.
Universally accepted methods to annotate ground truth of medical images have not been developed. Where different definitions of ground truth are used, the advantages and disadvantages of labeling methods are yet to be evaluated. The process of ground truth annotation currently includes radiologists' reports, pathology reports, surgical reports, crowdsourced annotation, and clinical follow-up. Depending on the clinical question, clinical follow-up may be from weeks to years.
In practice, medicine is more ambiguous than commonly presented. Many features found in any single image exist on a continuum. Thus, throughout medicine, clusters of findings are arbitrarily grouped into categories, such as "normal," "not quite normal," "suspicious for being abnormal," or "definitely abnormal." Cascades of these types of grading systems interact with each other. For example, mammogram findings are grouped into seven categories, from 0 to 6, depending on the degree of suspicion. Category 4 is suspicious findings that may require biopsy. In turn, pathology description of the biopsy is similarly categorized along a spectrum of multiple categories.
Radiologists' reports are not definitive expressions of ground truth [13,14,15,16]. A retrospective 20-year literature review in 2001 suggested that the level of significant radiology error ranged between 2 and 20% [17]. This is not limited to radiology; a Mayo clinic study comparing clinical diagnoses with postmortem autopsies reported that a major diagnosis was missed clinically in 26% of patients [18].
Even using radiology reports to annotate "normal," or "no disease," is problematic. For example, one study showed that 90% of lung cancers detected on radiographs were visible in retrospect on previous examinations [19]. This startling result did not mean radiologists were terrible. Rather, in some cases, lesions retrospectively noted on original exams were small, indistinct, or otherwise had features of normal structures or incidental findings. Even larger lesions are missed, however; a review of non-small cell lung cancer diagnosed on radiographs showed that 19% of lesions were missed, and the median diameter of missed nodules was 16 mm [20].
Dataset Specifications—Pixel Data
Historically, images used in object recognition ML have relatively small matrix size, to decrease computation time. In contrast, medical images often have very high dimensionality. In clinical practice, radiology image matrices may vary from 64 × 64 for some nuclear medicine exams, to over 4000 × 5000 for some mammogram images. CT and MRI scans, which typically are 512 × 512 and 256 × 256, respectively, for each image, may have well over 1000 images per exam. The number of extracted features may be very large. In order to train a network fully, each algorithm parameter requires at least several pixels to compute features.
Radiographs and fluoroscopic pixels represent 2D information, while CT, MR, PET, and ultrasound pixels represent 3D voxels. Some exams acquire time-dependent, 4D, data. Nuclear medicine has multi-dimensional, multi-frame images. Among many variables, voxel characteristics may vary based on patient characteristics such as size, shape, amount of fat, and patient movement; image acquisition parameters; specific vendor or machine acquisition, reconstruction, noise reduction, smoothing, and compression techniques; signal-to-noise ratio; and voxel size and shape. For CT, voxel value is measured in Hounsfield units, which are calibrated based on tissue characteristics, with water having a value of 0, and air −1000. For virtually all other medical imaging techniques, no standard gray-scale relationship exists. Raw image data may be acquired in forms uninterpretable by human eyes. Raw k-space data from MRI looks to the eye like a starburst. Commonly, k-space data are transformed via Fourier transform into the images one commonly associates with MRI. There is no reason why ML could not do as well, or better, finding textural patterns in k-space data rather than from typical images that humans view. Raw data manipulation on a similar scale occurs in many other types of medical imaging. Raw datasets often are large. Most raw data are deleted at the time of imaging or soon after based on local disk storage capacity, so for practical purposes datasets of multiple cases of raw data are unavailable.
While texture analysis is widely used for ML image analysis, it is rarely specifically evaluated by radiologists, and seldom annotated or documented in their reports. There are no standards for image texture, and no accepted descriptions of typical anatomic object texture [1].
Most image noise is unstructured, but certain machines or settings generate structured noise. Artifacts occur in every setting; some are dramatic enough that they may be mentioned in radiology reports or otherwise annotated, but in many cases radiologists and technologists simply discount them without mention. Artifacts can be specific to modalities, vendors, individual machines, or even unique situations such as imaging device location (e.g., ICU artifacts on ultrasound) or embedded medical appliances.
Dataset Specifications—Post Processing
Post processing includes such things as multi-planar reformats or 3D reconstructions; fusion of images from different modalities, time frames, or acquisition parameters; image filtering; segmentation; physiologic function; and time and/or movement analysis of objects. Some but not all post-processing algorithms have been studied for accuracy, reproducibility, and correlation among different vendors [21]. For example, a comparison of four commercially available semiautomatic packages for carotid artery stenosis measurement on CT angiography showed good correlation among the packages, but variable agreement for exact stenosis [22]. Other algorithms such as CT perfusion have shown large value variability among vendors [23].
Dataset Specifications—Sample Size
Sample size needed to train ML algorithms depends on factors including use case; performance level desired; input features; algorithm type and architecture; number of algorithm parameters; and data quality, including annotation quality, feature distribution, and noise in the training data and extracted features. Larger image matrix size, with more pixels, increases algorithm architecture and requires a larger training sample. The rule of 10 is commonly used, suggesting that a sample size 10 times the number of an algorithm's parameters is a reasonable estimate of sample size needed for training. Research on estimating data sample size to train ML algorithms is ongoing [24–27].
Depending on the question to be answered and the methodology used, training image analysis ML algorithms may require large datasets. Such a large dataset exists for visible light photographs: ImageNet, the dataset for many computer image recognition competitions, has over 14 million categorized images in 21,000 indexed synsets [28]. Many ImageNet photographs are of low resolution and have relatively low dimensionality.
In contrast, most publically available medical image datasets have tens or hundreds of cases, and datasets with more than 5000 well-annotated cases are rare. In the USA, individual healthcare institutions may have 103 up to rarely 107 of an exam type. These common radiology exam types, for example, chest radiographs, unenhanced brain CTs, mammograms, and abdominal CTs, are often high-dimensional data due to variations in pathology, technique, radiology interpretation, patient population, and clinical setting.
Complete imaging examinations are high-dimensional spaces, and datasets of these examinations provide relatively sparse available data. This is challenging for any method that requires statistical significance, where the needed sample size often grows exponentially with dimensionality. In high-dimensional data, many objects appear to be sparse and dissimilar, which confounds common data organization and search strategies based on detecting areas where objects form groups with similar properties. In addition to absolute sample size, class imbalance affects ML training. This is relevant with medical data if real-world datasets contain only rare target class examples of specific pathology, particularly when that pathology has dramatic clinical consequences and should not be missed.
For tightly focused use cases and algorithms with relatively few parameters, however, sample sizes as small as hundreds of cases may be adequate for training [4]. Because of this, much current academic medical image analysis ML research occurs this way.
The required number of unique, original exams can be decreased with hybrid approaches using augmentation and/or pre-training with selected features. Augmentation uses techniques to modify the dataset while keeping the key features the algorithm needs. For images, this commonly involves rotating, mirroring, or adjusting contrast or grayscale of images or parts of images such as a mass or other pathology, to generate new images from originals. For radiology examinations, algorithms may be pre-trained on other image datasets, even non-medical ones, in a process known as transfer learning [5, 29].
Medical Image Dataset Specifications—Regulatory and Business
In the USA, HIPAA mandates that unless specifically authorized by the patient to release patient-identifiable data, all PHI must be removed. HIPAA specifies 18 different identifiers that must be removed, including "full-face photographs and any comparable images." Depending on the body part imaged, 3D reconstruction of radiology exams into parts of a patient's image is possible. On the other hand, de-identification of datasets may result in the removal of metadata that is required for advanced processing.
The NIH requires applicants/grantees for most studies to submit a plan to share their final research data, and encourages all applicants to include a plan to address data sharing or to state why data sharing is not possible [10, 30]. Datasets may be shared by permitting access to a specific source or by sharing datasets through NIH data repositories [31]. Despite these requirements, applicable medical image datasets may not be readily available. C-MIMI participants universally felt that NIH should enforce adherence to data sharing regulations.
Though radiology societies express interest to develop medical image dataset production, storage, and management infrastructure, there is not yet a viable business case for them given the expense and resource requirements to build and maintain.
The FDA's Medical Device Development Tools (MDDT) program is a way for the FDA to qualify tools that medical device sponsors can use in the development and evaluation of medical devices. Qualification means that the FDA has evaluated the tool and concurs with available supporting evidence that the tool produces scientifically plausible measurements and works as intended within the specified context of use [32]. The FDA may be receptive to data submission to FDA for incorporation into the biomarker MDDT pilot, and/or submit tools to manage datasets appropriate for ML.
For individual healthcare enterprises, patient privacy, business case, and logistical issues are barriers to releasing or otherwise using medical images. As these institutions realize the value of those data, and the potential value of participating in ML model development, some of them are starting to pursue business relationships to expose data to data science businesses outside their firewalls. These same issues add complexity to any proposed large, federated, commercially or publically available medical image datasets with exams acquired from disparate healthcare institutions. Other countries with more centralized image storage, interoperable medical image management, and different regulatory and legal environments may provide lower barriers to data access.
Because of HIPAA and legal requirements on data privacy, as well as intellectual property issues, academic and other healthcare settings are starting to host, test, and do research with commercial algorithms inside their firewalls. This concept of bringing algorithms to the data, rather than data to the algorithm, is rapidly gaining favor. It allows these settings to keep control over their data, and still permit industry to move forward. One consideration with this approach is if institutions should keep back some of the data to use for testing, validation, and verification and, if so, how it is managed.
Who owns radiology data is not legally defined in most states. HIPAA does not specify, and most states have no legislation regarding medical data ownership [33]. Obtaining patient consent for secondary reuse of clinical data is often difficult and impractical.
Medical Image Dataset Specifications—Cataloging and Discovery
Widely used standards to catalog and discover medical image datasets do not exist, nor does a framework to catalog datasets specific to ML. Currently, mechanics of dataset discovery, collection, curation, access, and use are typically one-off solutions related to a specific research project. Medical multimedia metadata are often dirty and inconsistent. Some require high-level-domain expertise to understand, and others may require institutional knowledge unique to the originating site. Table 2 describes high-level metadata needed to catalog and discover medical image datasets. Many of these metadata are semantic. For example, under image type, if the modality is MRI, further data ideally would include details such as machine vendor, machine strength, model number, coil details, and contrast type and amount.
Recently, the scientific data community has proposed the FAIR guiding principles to support reuse of scholarly data [2, 34]. These guiding principles—Findability, Accessibility, Interoperability, and Reusability—should be no different for medical imaging ML datasets and are summarized in Table 3. Additionally, there is good reason to suggesting that the FAIR principles should apply not only to ML datasets but also to tools, algorithms, and workflows created for ML.
The dominant influence on a machine learning (ML) model's performance is often the amount and quality of training data. Attendees of the inaugural C-MIMI expressed the common theme that everyone participating in medical image evaluation with ML is data starved. There is an urgent need to find ways to collect, annotate, discover, and, ideally, reuse adequate amounts of medical imaging data.
Action items, and priority research topics, for this field of study include the following:
Describe, via a whitepaper, the high-level attributes of reusable medical image datasets suitable to train, test, validate, verify, and regulate ML products [35]
Describe common categories of use cases for medical image datasets, and understand unique dataset attributes applicable to each
Describe the metadata, framework, and standards needed to catalog and discover datasets of medical images appropriate for ML.
Understand and describe business cases and models for medical image datasets
Work with NIH and other government agencies to promote and, where applicable, enforce, access to medical image datasets
Improve communication among medical imaging domain experts, medical imaging informaticists, government and industry data scientists, and interested commercial entities
At the second annual Conference on Machine Intelligence in Medical Imaging (C-MIMI) meeting, to be held on September 26–27, 2017, at Johns Hopkins in Baltimore, Maryland, and at the SIIM Annual Meeting on June 1–3, 2017, in Pittsburgh, Pennsylvania, these action items will be reviewed further, as well as continuing the discussion on medical image datasets for ML.
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This work is supported in part by the Intramural Research Program of the National Institutes of Health, Clinical Center. The opinions expressed herein are those of the authors and do not necessarily represent those of the National Institutes of Health or the Department of Health and Human Services.
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Kohli, M.D., Summers, R.M. & Geis, J. Medical Image Data and Datasets in the Era of Machine Learning—Whitepaper from the 2016 C-MIMI Meeting Dataset Session. J Digit Imaging 30, 392–399 (2017). https://doi.org/10.1007/s10278-017-9976-3
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- Machine learning
- Medical imaging
- Imaging informatics
- Medical data
- Radiology
- Medical image datasets


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CloudWatchin the AWS services search box at the top of the page and select CloudWatch.
- Click Logs in the menu.
- Click your log group named /aws/lambda/ask-custom-AlexaSalesforceDemo-default.
- Click the log stream with the most recent Last Event Time. This should be the top item.
- From here, you see individual log statements from each invocation of your Lambda function. The error messages visible here may give you guidance to specific areas of the skill that may need to be reconfigured or adjusted.
- If you make changes to any of the code files, such as
skill-sample-nodejs-salesforce/lambda/custom/constants.js, don't forget to run the "ask deploy" command to push your changes back out to Lambda.
Once you prove the basic skill flow works, try to change your voice code too. If at any point you aren't sure what else you can ask, just say "Help."
Congratulations! You've successfully built and tested a private Alexa skill that is connected to a Salesforce org.
With the abilities you've learned here, you probably want to show this off to more users—maybe even the whole office! In order to do that, you publish the private skill and then grant permissions to an Alexa for Business account in order to distribute it to other users.
Alexa for Business is an AWS service that lets customers use Alexa to voice-enable their workplace by providing the tools needed to manage Alexa devices, skills, and users at scale. Through these tools, your private skill can be enabled by an organization and distributed to the organization's enrolled users.
For more instructions on how to publish your private skill and sign up for Alexa for Business, click here.
You now have an example of a skill that uses account linking with a Salesforce account. This lets you make sure that the skill can only be accessed by an individual with permission. You also have an example voice code flow, which the user must know when the skill is invoked.
Use this project as a building block to try new things and find ways to make everyone around you more productive in the workplace. We can't wait to see what new and innovative skills you come up with.


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ALL Power Labs
= an incubator for open source energy experiments and distributed manufacturing solutions.
URL = http://www.gekgasifier.com
"We work to generate physical tools and information resources for people exploring alt energy through DIY innovation and online collaboration.
We believe that a bottom up, participatory ecology in energy is just as possible as it has been in computing. And we expect the impact of such creative self-determination in energy, will be no less transforming than has been in digital realms.
The ALL Power Labs team is an unusual combination of junkyard fabricators and university trained scientists and engineers. Imagine a mash up of the Bay Area California art/tech underground with Phd techies from Stanford and MIT. The result is a powerful combination of technical ability and physical know how for building real things in the real world.
We are a group not enamored with designy concepts and dead-end demonstration projects. Rather, we focus on that which can be effectively built and deployed, immediately and in volume, with broad impact and relevance.
Four years after our founding we've grown to 25 full time employees, and support full engineering, design for manufacturing, and production manufacturing capabilities. Our facility is located in Berkeley California. You are welcome to visit next time you are in town."
More Information
For additional info on the APL team, see: http://www.gekgasifier.com/team.


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View raw data
David Parsons has 1 location.
149 Jefferson AvenueDetroit, MIUSA
• Privacy Policy •
Rules and Regulations • • Terms and Conditions •
A project of NYPL Labs and the The Miriam and Ira D. Wallach Division of Art, Prints and Photographs.
The New York Public Library
© The New York Public Library, Astor, Lennox, and Tilden Foundation 2015


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600,000 Syrians Have Returned Home So Far in 2017
But don't celebrate yet.
While the Syrian civil war is far from over, conditions have improved in some areas, enough so that displaced Syrians are returning home in large numbers.
So far in 2017, 600,000 Syrians have returned to their homes, according to the United Nations.
The displaced men, women, and children are returning to their places of origin primarily to protect their homes and assets and because the economic situation had appeared to improve, according to interviews conducted by the UN. Other reasons for returning include cultural barriers that made it hard to integrate in the places they were temporarily staying, perceived safety in their places of origin, and a lack of economic opportunity in other regions.
Take Action: Stand With Refugees
Most people returned to Aleppo, the site of a brutal showdown between the Syrian regime and rebel forces last year.
The majority of those who have returned have access to food, but less than half have access to water and health services because infrastructure has been destroyed during the conflict.
The lack of infrastructure is one reason why the UN cautions against celebration. Another reason is that as people are returning, even more people are getting displaced.
So far in 2017, an estimated 808,661 people have been displaced, essentially cancelling out any overall return to normalcy.
The Syrian civil war has produced an estimated 5 million refugees and caused another 6 million to be internally displaced. Overall, more than 13 million people need humanitarian aid.
Read More: This Syrian Refugee Became a Doctor After Studying in Four Countries
"The conflict in Syria may be complex, but ensuring people are protected and supported is our imperative as humanitarians, and as human beings," said UN humanitarian chief Stephen O'Brien in a statement. "None of us should stand silent while civilians suffer and while fear tactics and the denial of food, water, medical supplies, and other forms of aid are used as methods of war."


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Isaiah 58:8 NLT
"Then your salvation will come like the dawn, and your wounds will quickly heal. Your godliness will lead you forward, and the glory of the Lord will protect you from behind."
Series: The Book of Isaiah
Hurts are inevitable. Even nice people, even people who love us could hurt our feelings. In marriage, if you are hurt by the actions of each other do not expect the other person to bring healing or to apologize. While it is natural to expect so, most often it is the contrary that happens. Granted, even if the other person apologizes, it may not necessarily get off the bitterness from your heart. Eventually, this root of bitterness may cause you to surface up those past hurts in a fight. This only implies, it never helps to bring healing by the words of a person.
Fortunately, the word of God offers the remedy. Isaiah 53 says – It was our sorrows, that were laid upon Jesus; our sorrows weighed Jesus down. Jesus walked forward, carrying the cross that was burdened with all of our wounds, all of our pains, all of our tears…. These multiplied His sufferings. Through this instance, it is comforting to know that only Jesus, has the authority and the power to ease or alleviate us from our grief and distress, to liberate us from bitterness, anger issues and emotions of trauma that accompany painful memories.
You might be finding it difficult to resolve these issues or to navigate the grief process. Albeit, will you surrender your heart to Jesus? This is what the bible says, when you experience salvation, your wounds will suddenly heal; not gradually but suddenly!
"Father, I pray for every person who desires a touch this morning. I pray over every wound that is caused because of sin. Every wound caused because of negligent, greedy, cruel and ignorant people. I pray these wounds will quickly heal. I pray let there be an acceleration of this healing in their hearts and there will be so much godliness imparted to them. You died so that we may be made whole. Your word says that your godliness will lead us forward and the glory of your presence will protect us from behind. Let each one of us experience Your healing and the abundance of Your godliness. No weapon formed against them will prosper. Amen."
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Exquisite Eggplant Caviar
by Kate Heyhoe
Yield: 1-1/2 cups
Variations of eggplant caviar can be found from Russia to Greece. The seasonings change according to local. I make this version different every time, adjusting the nuts and herbs to whatever I have on hand. It should be tart and lemony, slightly salty, and a bit crunchy from the nuts.
1 eggplant
1/4 cup finely chopped green bell pepper
1/3 cup minced red onion
1/4 cup minced parsley
1 clove garlic, minced
1/2 teaspoon salt
fresh ground black pepper to taste
1 tablespoon extra virgin olive oil
3 tablespoons fresh lemon juice
1/2 cup toasted pine nuts, coarsely chopped
1. Prick the eggplant with a fork on all sides to allow steam to escape (if you don't prick it, the eggplant will explode). Microwave on high, uncovered, until the eggplant collapses and is soft when pierced throughout, about 10 minutes. Let rest until cool enough to handle. (Or, prick the eggplant and roast on a baking sheet at 375 degrees F until soft, 45 to 60 minutes.)
2. Scrape the eggplant flesh out with your fingers or a fork, discarding the skin. Coarsely chop the flesh and place in a mixing bowl.
3. Mix in the bell pepper, red onion, cilantro, garlic, salt, pepper, olive oil, and lemon juice. Stir in the pine nuts about 15 minutes before serving (they'll soften over a longer period and not be as crunchy, but their flavor is still fine.) Taste before serving—you'll likely need to refresh the flavors with an extra squirt of lemon juice, and perhaps a dash of salt and pepper. Serve with bagel chips or other crackers, toasted breads, or crudites.
Exquisite Eggplant Caviar
Lone Star Caviar
Mediterranean Black Olive Caviar
December Kate's Global Kitchen
December 5:
Wine &
Cheese-Spread Party
Fred McMillin's Wine Picks
Creamy Gouda-Horseradish Spread
My Blue Heaven Spread
Gift Ideas:
Screwpull Lever Model LX and Stand
KitchenAid Little Ultra Power Food Processor
December 12:
Bengal Lancers Beef Curry Cubes
Saffron Basmati Rice
Cranberry-Golden Raisin Chutney
Minty Raita-Style Cole Slaw
Gift Suggestion:
Wusthof-Trident Mezzaluna
December 19:
Weekend Salmon Gravlax
...and Last Minute Gift Suggestions
December 26:
Festive but Faux Caviars
Exquisite Eggplant Caviar
Lone Star Caviar
Mediterranean Black Olive Caviar
Holiday Recipe Headquarters
Copyright © 1998, Kate Heyhoe. All rights reserved.
Current Kate's Global Kitchen
Kate's Global Kitchen Archive
This page created 1998 and modified November 2006.


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Damian Dudek, researcher at the Phononic and Photonic Nanostructures Group at ICN, has won a Special Art Award in the 7th edition of the Raith Micrograph Award competition.
Dr Damian Dudek, researcher at ICN's Phononic and Photonic Nanostructures Group, has been awarded one of seven Special Art Awards in the 2010 edition of the Raith Micrograph Award. The competition honours images that reflect "uniqueness of nanostructure". Dr Dudek won for an SEM image entitled "Time space bending on nanoimprinted polymer".


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STOMP it anytime, anywhere.
Download the new STOMP app today.
Submitted by Stomper David, Anonymous
This story was submitted via Stomp App contribution. This story was submitted via WhatsApp. Click here to join our WhatsApp group.
This story was submitted via Stomp App contribution.
This story was submitted via WhatsApp. Click here to join our WhatsApp group.
A vehicle fire broke out along Killiney Road at about 6pm on Thursday (Sep 13).
Stomper David was walking past the area at about 6.30pm when he witnessed the incident.
In a video taken by him, a black car parked by the roadside is seen engulfed in flames accompanied with black smoke, before it was extinguished by the Singapore Civil Defence Force (SCDF).
Two fire engines are also seen at the scene.
(Story continues below)
David said: "I didn't see how the fire started, it was already like that when I passed by.
"No one seems to be inside the car because I didn't see the SCDF extracting anyone from it, and I didn't see an ambulance as well."
Another Stomper had also taken a photo of the fire as her car was stopped at a traffic junction.
In response to a Stomp query, SCDF said that it had responded to a vehicle fire incident along Killiney Road at about 6.15pm on Thursday.
The fire was extinguished by SCDF using a water jet and two compressed air foam backpacks.
There were no reported injuries and the cause of fire is under investigation.


text: Jun 18, 2018 Unfragile Thyself - Researched things 🔍, resized a ring ⛏, and more... Revue Hi, I hope all is well. I'm glad you're here. This week I researched things to buy, reviewed price hi Unfragile Thyself June 18 · Issue #4 · View online Brief reflections on five experiences Hi,I hope all is well. I'm glad you're here.This week I researched things to buy, reviewed price histories, met with a jeweler, thought about midpoint dips, and celebrated Father's Day. Wirecutter 🔍 To get ready for our move to Kuwait, we have things to buy. I appreciate reliable, durable, and enjoyable things. To find them, I turn to Wirecutter. Its research, credibility, and consideration of different buyers make it an excellent source to figure out what to buy. Camelcamelcamel 📈 After I research what to buy, I think about when to buy. Prices drop and rise throughout the year. 1-year price history of a carry-on suitcase To get a price history, automatic tracking of price changes, and a notification alerting me that the current price matches my desired price, I use Camelcamelcamel. White gold ⛏ Knowing Kuwaiti law prohibits me from spending the night with Tatiana if I am not married to her, I thought I had better get my wedding ring back on my finger. A few months ago it had finally become too small to wear, so I took it to a jeweler this week to get resized. My size 9 wedding ring resized to 11.5 Fortunately, my wedding ring is white gold. A titanium ring, which I had considered buying, cannot be resized. Midpoints 😫 Dan Pink in When, has me thinking about midpoints. In the things we do, we like to start strong and finish strong, but in between those two points our effort and enthusiasm tend to fade. We cannot eliminate this midpoint dip, but knowing that it's going to come can help mitigate some of its harms. Father's Day 🕺 I am so grateful that I could spend Father's Day with my family here in Austin. Kathy, Tom, Tod, Gabriel, and Tatiana We spent the day cheering for teams in the World Cup, went for a walk through Stage Coach Park, enjoyed a fantastic bbq at Freedmen's (favorite brisket in all of Austin) and ice cream at Amy's. Watch your bobber! ~Tod Did you enjoy this issue? If you don't want these updates anymore, please unsubscribe here. Powered by Revue Kuwait


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The project, owned by Electrica del Valle de Mexico, a subsidiary of France's EDF Energies Nouvelle, and backed by an $80.66 million direct Ex-Im Bank loan, is one of the first large US wind technology sale in Latin America, according to bank chairman Fred Hochberg.
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4% difference with PAL<>NTSC when dubbing - alugha facts day #23
Katharina FinkenIf you translate a video into another language you have to look for the standards. The European standards (PAL/SECAM) differ with the USA ones (NTSC). The playback speed in particular is important. nnBehind door 23 of our advents calendar we like to go into details of this for you. nnSee more about us on https://alugha.comnInstall the FREE Extensionnfor Chrome here: http://goo.gl/XIFaoUnfor Safari here: http://goo.gl/gxV88Anfor Firefox here: http://goo.gl/OEvBnBnnOr our FREE app for Android: http://goo.gl/woDT4l
LicenseDefault YouTube License


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Regular price
This beautiful Dainty Rainbow Moonstone Marquise Silver Engagement Ring has a beautiful Vintage-inspired look with a brilliant Marquise-cut Rainbow moonstone set in a protective filigree mounting. We are happy to create this beautiful engagement ring for you in a variety of ring sizes and finish options!
The dainty design of this Sterling Silver filigree engagement ring is both comfortable and easy to wear. This filigree ring holds a marquise-cut Rainbow Moonstone that measures 6 mm x 3 mm (approximately .25 carats) and is clear with few visible flaws and bright flashes in blue and blue-green. Because the low-set mounting protects the stone by encasing it in a filigree crown, this ring is perfect people who work with their hands. The ring tapers gracefully from 7 mm in width to a 1.5 mm (approximately .1 inch) wide band that has been carefully curved for wearing comfort.
Legend has it that the creation of the Marquise cut is credited to King Louis XV of France, who commissioned his court jeweler to create a diamond cut to reflect the beautiful shape of the mouth of his friend and long-time mistress, the Marquise Madame de Pompadour, in the 1750's. Because of their long, narrow shape, marquise cuts are often credited for making a finger appear longer and more slender. This historical cut, once worn by the French Court, has seen a resurgence in popularity in both new and vintage jewelry.


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From Sauneman to Forrest, I listened to another favorite radio station of mine, 98.3 WWHP out of Farmer City, Illinois. Their music could best be classified as Americana, and, of course, I get those farm reports, always great to have while driving through all that Illinois farmland. I turned it off however, before I got out of range as they were playing nothing but a steel drum concert which I didn't like so well.
Normally, I take Il-47 all the way to I-74 in Mahomet, Illinois, near Champaign, and then that to Indianapolis. However, my last time through Indianapolis, I-65 and I-70 were under construction and I got caught in a huge traffic jam taking the bypass. I decided to take US-24 east to I-65 and that to Indianapolis to avoid it. It started to rain in Dwight and continued the whole way until I got east of Indy.
In Watseka, Illinois, I saw a sign for The Full Bull BBQ and Saloon, a place I might have to check out sometime.
Gas was $3.29 in Indiana. Stopped at Kentland, Indiana, at a McDonald's and saw that they had Bears cups with the purchase of a large-size meal. You'd think being Indiana, the cups would have been Colts.
At 1:34 PM, I saw a convoy of four cop cars with flashing lights escorting a truck with something big under a tarp. I have to wonder what that was all about. About 25 miles north of Lebanan, Indiana, I saw a bad accident in the northbound lanes and a huge backup on I-65.
Home for Thanksgiving. --RoadDog


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Microsoft has been at the fulcrum of digitizing productivity on devices like desktop PCs and now the company is hell-bent on taking the productivity experience to your smart devices across all platforms. The company has made its much eagerly awaited announcement of taking Office suite to Android and iOS ecosystem, which enables the company to broaden its user-base functioning out of smartphone and tablets.
"Today, we unveiled Office for iPad® – specifically Word, PowerPoint and Excel. But this isn't simply Office on another device. We thought a lot about what people want to do when they're on their tablet, iPad functionality, and touch-first when we were building Office for iPad. We reimagined Office on the iPad, while retaining what people love about Office," as per John Case, corporate vice president – Marketing, Microsoft Office on Microsoft's blog.
What this basically means that Apple iPad with the added repertoire in the form of Microsoft Office, can stake its claim to become front-runner tablet for content generation purpose. You get all the basic Office suites: Word, Excel and PowerPoint among others that work just like your PC version with all the latest features, options and up-to-date versions. The company has notified that Office for iPad works on iOS 7 and above versions which clearly implies the vast product-line up support. You can download the Office Suite for iPad from App store.
Another major development to take place from Office point of view is the decision to offer free Office Mobile app for Android devices. Office alternatives like KingSoft have served the users admirably over the year but with Office Mobile making its much vaunted appearance on Google Play store, Microsoft has made the right moves. You can download the Microsoft Office Mobile from Play store. This app is compatible with devices running on Android 4.0 Ice Cream Sandwich and above.


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Liz Marlow
VP, Business Development
17111 Kenton Drive, Suite 103
Cornelius, NC 28031
Office: 704-896-9622
Cell: 704-560-7534
AlphaGraphics Lake Norman is a locally owned and operated marketing communications company.
We are experts in creating and producing custom solutions that help you communicate with impact. Our passion is helping you get results. Whether you need Printing Services, Marketing Services or Custom Signage, we have a solution for you:
designs that capture your vision and promote your brand
brochures, flyers & other marketing collateral that excites people about your products & services
eye-catching graphics for your vehicles, windows, walls and floors
attention-grabbing trade show exhibits, signs, banners and flags
digital and direct marketing solutions that get your phones ringing
business printing that showcases your brand on stationery and business cards
forms, manuals, labels, packaging and much, much more ……
Jennifer Szakaly
Care Manager
6135 Park South Drive
Suite 510
Charlotte, NC 28210
Main: 704-945-7170
Fax: 877-513-6075
Cell: 704-492-0554
I opened the Charlotte-based geriatric care management and counseling firm, Caregiving Corner, in 2005 to assist caregivers of older adults in navigating the long-term care system and to arm them with the knowledge they need to make informed decisions when dealing with a crisis caregiving situation. As a gerontologist and nationally certified geriatric care manager, I understand the social and psychological complexities of caregiving. I have experience working with other senior care providers, so my knowledge of the aging services network in the Charlotte, NC area is extensive. Because of my expertise, I am also frequently asked to provide training to corporations who employ Baby Boomers who are juggling caregiving and careers, marketing seminars to aging-related businesses on media relations, and various types of speaking and educational events.
Specialties: Assessments, referral & placement services, family mediation, care plan development, VA benefits application assistance, Mediation application assistance, service coordination, monitoring of long-distance caregiving situations, and crisis intervention.
Sherre DeMao
CEO - Strategy Maestro
7210 Hunters Bluff Drive
Denver, NC 28037
Main: 704.483.2941
Cell: 704.231.3847
Sherre' is passionate about inspiring new thinking to empower positive change. As an author, writer and international speaker, she inspires leaders and individuals around the globe through her nationally acclaimed books, contributing articles, monthly columns, and weekly Monday Motivation blog and email communication. Her first book, Me, Myself & Inc. A Synergized World, An Energized Business, Living Your Ultimate Life, changed the way running a business and life as an entrepreneur was viewed and approached. Her book, 50 Marketing Secrets of Growth Companies in Down Economic Times, was cited as a book " … referred to time and time again." Her next book, The Profitability Quotient," is due out in pre-publication copies by late 2017.
As CEO/Strategy Maestro of BizGrowth Inc., Sherre' brings more than 30 years of best practices and validated operational and marketing success to entrepreneurial enterprises. Her work as a growth strategy consultant, CMO or COO on-call helps build companies of value and worth, and business owners enjoy prosperity and satisfaction.
If you are seeking to scale your business and build a company of value to ultimately cash in for all your hard work and efforts, you need to have Sherre' as a part of your advisory team.
Debi Thomas
Interior Design
16847 B Birkdale Commons Parkway
Huntersville, NC 28078
Main: 704-517-2030
Debi Thomas Designs provides stunning and original turn key designs for any room in your home. Services include color selection, space planning, and materials selection for new construction, remodeling, or 'makeovers'. Tailored window treatments and bedding are designed by Debi Thomas, an award-winning interior designer with over twenty years of experience in the industry, fabricated by highly skilled tailors, and professionally installed in your home. Exclusive accessories, designer fabrics, wall coverings and area rugs, as well as bench-made custom upholstery are selected to compliment your style and respect your budget.
Petra Weiser
Author, Speaker, Women's Advocate
116 Single Oak Drive
Troutman, NC 28166
Main: (704) 467-2909
I'm your blunt reminder that women were and are defined by men as being dickless. The exclusion factor—not having a penis—shows that women are consistently and purposely denied access to equal opportunities and equal pay, as well as equal treatment and recognition. My goal is to motivate women into action, because women tend to be more passive when fighting for their own rights. We must be the change if we expect change.
I raise awareness about women's struggles through my memoir DICKOTOMY (which showcases some of the Ricks and Dicks in my life), as well as through public speaking events, and through the DICKLESS brand itself, as the "in-your-face" public service announcement that women are not ashamed of being just that: DICKLESS.
Kelly Jimenez
Outreach Educator
Supporting Cap Tel- Captioned Telephones
Charlotte, NC
Main: 704-635-1754
OEI raises awareness of programs that provide free Captioned Telephone service to individuals with hearing loss. If you or someone you care about has trouble hearing over the phone, we can help. We work with you to make sure anyone with hearing loss can feel comfortable and confident talking on the telephone. With programs to provide a free Captioned Telephone, we bring captioning to you! OEI works extensively with Audiologists, Veterans Service Officers and Hearing Health Professionals to provide individuals with the support and equipment they need to feel confident talking over the phone – all at no cost!
Karen D. Moravus
Branch Sales Manager/ NMLS #447961
16930 W. Catawba Ave., Suite 200
Cornelius, NC 28021
Main: 704-918-6000
Fairway Independent Mortgage is a nationally ranked, residential mortgage lender committed to providing the best rates for our customers while remaining dedicated to the highest level of service demonstrated through consistent, informative communication with clients and their real estate partners. Our goal is to act as a trusted advisor, providing highly personalized service and guiding our clients through every step of the loan process. It's all designed to exceed expectations, guarantee satisfaction, and earn trust. We strive to streamline the mortgage process for our clients and make it stress free for all parties involved. (Fairway Independent Mortgage Corporation is licensed in all 50 states and has headquarters in Madison, WI, and Carrollton, TX.)
GiGi Sampson
Business Service Professional
1785 Laurel Hill Drive
Lincolnton, NC 28092
Office: 704.240.3153
Cell: 704.692.7351
I am passionate about facilitating the growth and success of entrepreneurs and small businesses! By delivering accounting, project management and secretarial services via a virtual venue, I help my clients stay focused on growing their businesses, instead of on the necessary but time and energy draining tasks such as bookkeeping, sales tax reporting, reconciling bank accounts, etc. Together we set up and streamline systems and processes to stay on track with projects, prospects, new clients and business opportunities. Clients have the services they need, available as they need them, at a reasonable cost.
Becca Mangini
6001 Gateway Center Dr, Ste 105
Concord, NC 28031
Cell: 803-445-5289
I am passionate about helping people who are making the jump to home ownership, upgrading/downsizing, or relocating to their next adventure. I know that a home purchase or sale can be the biggest financial move of a person's life and my consultative approach to listing and purchasing truly helps to focus on each client's needs, wants and desires to create their unique "best experience." My goal is to make the process as seamless and pleasurable as possible by being flexible, attentive, and a true master of connections for my clients in the real estate space.
Elizabeth Colen
Nutrition, Diet and Health Specialist
Ms. Fit One Lifestyle
Phone: 704-980-0250
Instagram /Twitter: @MsFitOne
YouTube: Elizabeth Colen
Elizabeth Colen is a Health Specialist who helps people create radical breakthroughs in their health and wellness. Elizabeth has a deeper understanding of weight issues because of her own weight loss story of losing over 115 pounds. She has maintained that weight loss for more that 10 years. She focuses on you while you focus on everything else. Elizabeth will work with you to create a customized holistic comprehensive health plan that will give you more energy, more focus and more clarity so that you can be more focused on your business and be more productive in your day to day life. Living a healthy lifestyle is more than physical it's being healthy mind, body and spirit. Your well-being is a lifestyle not a fad
Kasandra Brew Blum
Property Manager
P.O. Box 119, Huntersville, NC 28070
Neighborhood Property Management is a full service residential property management company. I am passionate about managing my clients rental homes to ensure their investment remains an investment. The services provided to my clients include tenant placement, rent collection, routine interior/exterior inspections, eviction filings, financial reporting and maintenance. I believe in providing quality service to each client and customer to build and retain professional and trusting relationships.
Kara K. Carpenter
Business Relationship Manager
18809 West Catawba Avenue.Suite 204
Cornelius, NC 28031
Main: 704.603.7705
Omnia Construction Group is a licensed General Contractor specializing in residential remodels, additions and custom homes in the Lake Norman area. At Omnia, our primary goal is to consistently exceed our client's expectations throughout the remodeling process. We achieve that through constant communication and collaboration with the project team, which includes our clients, designers and trade partners.
At Omnia, we recognize that not every project is a good fit for every contractor. Therefore, we place significant emphasis on listening to and learning about the needs and goals of our clients, and making sure that we can successfully achieve their vision.
My specialty is personal insurance and enjoy working with my clients listening to their insurance needs and finding effective solutions to protect their financial assets. NFP Insurance also has resources for commercial, life, health and group coverages.
Hollie Sims
Vice President
18809 W. Catawba Ave
Ste 204A
Cornelius, NC 28031
Main: 980-829-6676
Cell: 704-577-4860
On Point Flooring is your local source for quality flooring products and installation services. Our more than 20 years of experience provides you with confidence in the work and assurance in the end results.
On Point Flooring is a mobile flooring showroom with hundreds of samples to choose from:
VINYL TILE (including custom showers & backsplashes)
**No Charge, convenient in-home consultations.
Monica Able
Pinnacle Financial Partners
271 Copperfield Blvd NE
Concord, NC 28025
Phone: 980.359.1160
Fax: 704-723-4846
Mobile: 704-577-5518
Our mission is to create an enhanced level of trust for our clients built on accountability. We anticipate our clients' needs, and by understanding their visions for financial success, exceed their expectations.
I have over 20 years of banking experience and I specialize in assisting business owners that are challenged with managing their business and personal finances while trying to focus on increasing profitability, decreasing debt and growing their business.
I sincerely believe that people bank with people. We all do business with someone because we choose to, not because we have to. We can always find others doing the same thing or selling the same product. It's the personal connection that makes a difference. I want to take the time to make a personal connection with each client I serve. We foster an environment that allows me the opportunity to develop a personal connection with those I serve
As a Chair on Business Sorority's Philanthropy committee, Kristine cares deeply about making a difference for those in need. She is currently going back to school to get her cosmetology license and plans to focus on servicing seniors as well as individuals with disabilities. Throughout her past experience working with seniors and those with disabilities, she has seen a great need for specialized care for these individuals. Kristine loves to make people feel beautiful. But more than anything, she strongly desires making them feel loved. Accessibility, consideration of needs, and genuine conversation will be just a few of Kristine's specialties as a cosmetologist. Look out for her once she is official in December of 2020!
Tammy Rojas
Head Creative Chic
Huntersville, NC
Office: 704-274-9978
Cell: 917-992-4573
Tammy Rojas, head creative chic at redhot marketing & design, has never had to ask the question "what do I want to do with my life?" The answer was always there - design beautiful things and make people happy, of course! She has been doing just that for over 25 years, for companies such as Not Fade Away Graphics, ToysRUs and dressbarn. Eager to "never work in a cubicle again", Tammy left NY in 2008 and redhot marketing & design was born! She loves partnering with her clients to help them achieve their marketing and design goals in the most creative way possible.
Branding | Print Design | Web Design | Social Media | Public Relations
Wendy Becker
9935 D Rea Rd # 107
Charlotte, NC 28277
Main: 980-354-1123
Our priority in The Sandbox is to come alongside families whose children have cancer or a life altering illness and make sure they know that they are not alone on this journey. We have just launched a new approach to how we do that, and it's designed to ensure that we are serving families in the best possible way. It's called our CARRE program, because The Sandbox Cares About Real Relationships Empathetically. Through this model, we are aiming to customize the services we offer families to be sure it's exactly what they need.
Jenni Miehle
Mooresville, NC
Cell: 704-995-7753
As a freelance graphic designer and "grammar nerd," my specialty is informational documents - things like reports, training manuals, workbooks, forms, etc. I help small to medium size businesses (and nonprofits) look professional and communicate effectively by designing materials that are well-organized, visually appealing, and consistent with their brand.
Mary Lou Winn
Office Manager
18809 W. Catawba Avenue, Suite 102
Cornelius, NC 28031
Main: 704-409-1875
Cell: 704-277-3648
Viking Merger & Acquisitions' business sales process has evolved over the years into what it is today: a streamlined system that helps business owners successfully complete the sale of their business and earn top dollar in the process. Since 1996 Viking has sold over 500 businesses, averaging 96% of the asking price and is among the top 2% of M&A brokers in the nation.
If you are ready to sell your business, or at least ready to discuss the idea and get a feel for what your business might be worth, please contact us to schedule a free consultation. During our no-cost, no-obligation introductory consultation, we'll talk with you to learn more about your business and its unique attributes. We tell you about what we do, how we do it, what it costs, and what you can expect in the process—and of course, everything we discuss is completely confidential. Afterward, we'll perform a complimentary valuation, showing your business' range of value and will do pre-screening with a lender to ensure it meets current lending guidelines.


text:
The Queen of Kind
At home with Lisa Lampanelli
Most people who have heard of Lisa Lampanelli know her as a comedian with a penchant for insults and crude jokes, earning her the moniker "The Queen of Mean." Watching some of her past routines on YouTube, I wondered, should I prepare myself to be offended? Not a chance, it turns out. After being greeted with a big hug and warm hello, I learned that this dynamic comedian-turned-storyteller doesn't have a mean bone in her body. And she never did. "I'm a mush," she tells me with a wide smile. She just happened to build a successful career excelling as a celebrity roaster and telling off-color, un-PC jokes. Nowadays Lampanelli isn't insulting anyone—instead she's searching out ways to help others, and if it makes them laugh too, all the better.
"I have always been a storyteller," says Lampanelli. Her recent off-Broadway play Stuffed resonated with audiences, and her latest work—Lisa Lampanelli's Losin' It—will have its worldwide debut at the Fairfield Theatre Company on November 3. During the 90-minute show, Lampanelli and her cast of professional actors, storytellers, and other surprise guests describe what they've been through and how they maintain sanity while they're "losing it" over weight and body-image issues. It's poignant, but also funny. "It's not that I don't want to make people laugh anymore—it's that I want to see if I can help them feel better," explains Lampanelli. A large portion of the show's proceeds will benefit the Center for Family Justice, where Lampanelli's sister, Nancy Lessard of Shelton, is a board member. Lampanelli is a strong supporter of the work they do there providing critical support to people who have been victims of violence and domestic abuse.
"I am so grateful and lucky to say I have never been hurt or abused," she says. "But you can be damn well sure I want to help in any way I can to help prevent others from being hurt—or help when they are," she says.
It's no surprise that Lampanelli is supporting a local nonprofit like the Center, as she is a die-hard Nutmegger. Born in Trumbull, college and life took her away from her home state, but now she's returned—for good. "My heart is in Connecticut in the form of my family and dearest friends," says Lampanelli. She chose to live in Fairfield because she thinks it's a great town—"there's a theater for performing and music right in town!" she exclaims. Her three-story grey-shingled beach house, flooded with light and steps from the shore, boasts views of the Sound and the Penfield lighthouse. But you won't catch her swimming or sunbathing. "I love being here, but I am not an outside gal," she chuckles. Her home, cheery and warm in its beachy colors of aqua and sand, tells the story of her life. Shelves and walls with framed bulletin boards are adorned with cards, pictures, tchotchkes, even vintage purses that belonged to her 89-year-old mother Gloria.
Her walls also talk. In the bathroom, there is a wall stencil that reads, "Whenever I Get Sad, I Stop Being Sad and Start Being Awesome." Mantras aside, there are many things that inspire her, and her energy for them is contagious. "Peggy from Mad Men is my spirit animal," gushes Lampanelli. She even wears a name necklace that spells "Peggy." "People may see it and think Peggy is my long-lost lesbian lover, but she isn't. It's Peggy, the most bad-ass female character ever to appear in a TV series." Lin-Manuel Miranda's Hamilton is also a passion of Lampanelli's, and the musical score sits on her piano. "I was so honored to attend the opening night performance," she says. "One of the best nights of my life."
Twice divorced, Lampanelli is completely content with her status as her pup Parker's constant companion. She credits her eight-year-old rescued Yorkie/Chihuahua mix—who is named for Sarah Jessica Parker "because they weigh about the same," jokes Lampanelli—with changing her whole outlook on life. "I was living in the city and about to get married, and wasn't even looking for a dog." But she went by a dog adoption event on the Upper West Side, took one look at Parker and knew she had to have him. "It might sound silly but Parker truly opened me up to being really loved and needed, and to slowing down," she explains.
The last few years have heralded so many changes for Lampanelli. Her father became ill and passed away, and she spent more time in Connecticut with her siblings. "Sometimes these life-changing events split families. In our case it made us even closer," she says. Her most widely publicized change was her life-affirming decision to have gastric sleeve surgery, and she subsequently lost over 100 pounds, maintaining that weight loss for more than six years. She says a day doesn't go by that she doesn't think about her weight and her calorie intake. "I obsess about food all the time, and I work with a coach to figure out what to eat, and what not to, and I take a gazillion vitamins a day," she says.
Because she knows she is not alone in her struggles with body image and weight, Lampanelli, along with healing arts practitioner Anna Brooke, have created The Lamp and the Vamp, a company that offers workshops around the country about issues particular to people working on themselves. Their first is a one-day workshop on eating, self-image, and weight called "Love Your Body, Feed Your Soul: From Starving & Stuffed to Fulfilled & Enough," which will debut at the The Liphe Balance Center in Wilton on Saturday, November 10. n
Go to LisaLampanelli.com or follow @LisaLampanelli on Facebook and Instagram to hear more about her upcoming performances.