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STUDY QUESTION Are chromosome abnormalities detected at Day 3 post-fertilization predominantly retained in structures of the blastocyst other than the inner cell mass (ICM), where chromosomally normal cells are preferentially retained? SUMMARY ANSWER In human embryos, aneuploid cells are sequestered away from the ICM, partly to the trophectoderm (TE) but more significantly to the blastocoel fluid within the blastocoel cavity (Bc) and to peripheral cells (PCs) surrounding the blastocyst during Day 3 to Day 5 progression. WHAT IS KNOWN ALREADY A commonly held dogma in all diploid eukaryotes is that two gametes, each with ‘n’ chromosomes (23 in humans), fuse to form a ‘2n’ zygote (46 in humans); a state that remains in perpetuity for all somatic cell divisions. Human embryos, however, display high levels of chromosomal aneuploidy in early stages that reportedly declines from Day 3 (cleavage stage) to Day 5 (blastocyst) post-fertilization. While this observation may be partly because of aneuploid embryonic arrest before blastulation, it could also be due to embryo ‘normalization’ to a euploid state during blastulation. If and how this normalization occurs requires further investigation. STUDY DESIGN, SIZE, DURATION A total of 964 cleavage-stage (Day 3) embryos underwent single-cell biopsy and diagnosis for chromosome constitution. All were maintained in culture, assessing blastulation rate, both for those assessed euploid and aneuploid. Pregnancy rate was assessed for those determined euploid, blastulated and subsequently transferred. For those determined aneuploid and blastulated (174 embryos), ICM (all 174 embryos), TE (all 174), Bc (47 embryos) and PC (38 embryos) were analyzed for chromosome constitution. Specifically, concordance with the original Day 3 diagnosis and determination if any ‘normalized’ to euploid karyotypes within all four structures was assessed. PARTICIPANTS/MATERIALS, SETTING, METHODS All patients (144 couples) were undergoing routine preimplantation genetic testing for aneuploidy in three IVF clinical settings. Cleavage-stage biopsy preceded chromosome analysis by next-generation sequencing. All patients provided informed consent. Additional molecular testing was carried out on blastocyst embryos and was analyzed for up to four embryonic structures (ICM, TE, Bc and PC). MAIN RESULTS AND THE ROLE OF CHANCE Of 463/964 embryos (48%) diagnosed as euploid at Day 3, 70% blastulated (leading to a 59% pregnancy rate) and 30% degenerated. Conversely, of the 501 (52%) diagnosed as aneuploid, 65% degenerated and 35% (174) blastulated, a highly significant difference (P < 0.0001). Of the 174 that blastulated, the ratio of ‘(semi)concordant-aneuploid’ versus ‘normalized-euploid’ versus ‘other-aneuploid’ embryos was, respectively, 39%/57%/3% in the ICM; 49%/48%/3% in the TE; 78%/21%/0% in the PC; and 83%/10%/5% in the Bc. The TE karyotype therefore has a positive predictive value of 86.7% in determining that of the ICM, albeit with marginally higher aneuploid rates of abnormalities (P = .071). Levels of abnormality in Bc/PC were significantly higher (P < 0.0001) versus the ploidy of the ICM and TE and nearly all chromosome abnormalities were (at least partially) concordant with Day 3 diagnoses. LIMITATIONS, REASONS FOR CAUTION The results only pertain to human IVF embryos so extrapolation to the in vivo situation and to other species is not certain. We acknowledge (rather than lineage-specific survival, as we suggest here) the possibility of other mechanisms, such as lineage-specific movement of cells, during blastulation. Ethical considerations, however, make investigating this mechanism difficult on human embryos. WIDER IMPLICATIONS OF THE FINDINGS Mosaic human cleavage-stage embryos can differentiate into a euploid ICM where euploid cell populations predominate. Sequestering of aneuploid cells/nuclei to structures no longer involved in fetal development has important implications for preimplantation and prenatal genetic testing. These results also challenge previous fundamental understandings of mitotic fidelity in early human development and indicate a complex and fluid nature of the human embryonic genome. STUDY FUNDING/COMPETING INTEREST(S) This research was funded by Organon Pharmaceuticals and Merck Serono by grants to W.G.K. W.G.K. is also an employee of AdvaGenix, who could, potentially, indirectly benefit financially from publication of this manuscript. R.C.M. is supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R35GM133747. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. D.K.G. provides paid consultancy services for Care Fertility. TRIAL REGISTRATION NUMBER N/A.

Sequence-based neural networks show significant sensitivity to syntactic structure, but they still perform less well on syntactic tasks than tree-based networks. Such tree-based networks can be provided with a constituency parse, a dependency parse, or both. We evaluate which of these two representational schemes more effectively introduces biases for syntactic structure that increase performance on the subject-verb agreement prediction task. We find that a constituency-based network generalizes more robustly than a dependency-based one, and that combining the two types of structure does not yield further improvement. Finally, we show that the syntactic robustness of sequential models can be substantially improved by fine-tuning on a small amount of constructed data, suggesting that data augmentation is a viable alternative to explicit constituency structure for imparting the syntactic biases that sequential models are lacking., To appear in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL-2020)

Pretrained neural models such as BERT, when fine-tuned to perform natural language inference (NLI), often show high accuracy on standard datasets, but display a surprising lack of sensitivity to word order on controlled challenge sets. We hypothesize that this issue is not primarily caused by the pretrained model's limitations, but rather by the paucity of crowdsourced NLI examples that might convey the importance of syntactic structure at the fine-tuning stage. We explore several methods to augment standard training sets with syntactically informative examples, generated by applying syntactic transformations to sentences from the MNLI corpus. The best-performing augmentation method, subject/object inversion, improved BERT's accuracy on controlled examples that diagnose sensitivity to word order from 0.28 to 0.73, without affecting performance on the MNLI test set. This improvement generalized beyond the particular construction used for data augmentation, suggesting that augmentation causes BERT to recruit abstract syntactic representations., ACL 2020

If the same neural network architecture is trained multiple times on the same dataset, will it make similar linguistic generalizations across runs? To study this question, we fine-tuned 100 instances of BERT on the Multi-genre Natural Language Inference (MNLI) dataset and evaluated them on the HANS dataset, which evaluates syntactic generalization in natural language inference. On the MNLI development set, the behavior of all instances was remarkably consistent, with accuracy ranging between 83.6% and 84.8%. In stark contrast, the same models varied widely in their generalization performance. For example, on the simple case of subject-object swap (e.g., determining that "the doctor visited the lawyer" does not entail "the lawyer visited the doctor"), accuracy ranged from 0.00% to 66.2%. Such variation is likely due to the presence of many local minima that are equally attractive to a low-bias learner such as a neural network; decreasing the variability may therefore require models with stronger inductive biases., Comment: 11 pages, 7 figures; accepted to the 2020 BlackboxNLP workshop

Learners that are exposed to the same training data might generalize differently due to differing inductive biases. In neural network models, inductive biases could in theory arise from any aspect of the model architecture. We investigate which architectural factors affect the generalization behavior of neural sequence-to-sequence models trained on two syntactic tasks, English question formation and English tense reinflection. For both tasks, the training set is consistent with a generalization based on hierarchical structure and a generalization based on linear order. All architectural factors that we investigated qualitatively affected how models generalized, including factors with no clear connection to hierarchical structure. For example, LSTMs and GRUs displayed qualitatively different inductive biases. However, the only factor that consistently contributed a hierarchical bias across tasks was the use of a tree-structured model rather than a model with sequential recurrence, suggesting that human-like syntactic generalization requires architectural syntactic structure., Comment: 12 pages, 10 figures; accepted to TACL

A machine learning system can score well on a given test set by relying on heuristics that are effective for frequent example types but break down in more challenging cases. We study this issue within natural language inference (NLI), the task of determining whether one sentence entails another. We hypothesize that statistical NLI models may adopt three fallible syntactic heuristics: the lexical overlap heuristic, the subsequence heuristic, and the constituent heuristic. To determine whether models have adopted these heuristics, we introduce a controlled evaluation set called HANS (Heuristic Analysis for NLI Systems), which contains many examples where the heuristics fail. We find that models trained on MNLI, including BERT, a state-of-the-art model, perform very poorly on HANS, suggesting that they have indeed adopted these heuristics. We conclude that there is substantial room for improvement in NLI systems, and that the HANS dataset can motivate and measure progress in this area, Comment: Camera-ready for ACL 2019

International audience; Active ionospheric experiments using high-power, high-frequency transmitters, “heaters”, to study plasma processes in the ionosphere and magnetosphere continue to provide new insights into understanding plasma and geophysical proceses. This review describes the heating facilities, past and present, and discusses scientific results from these facilities and associated space missions. Phenomena that have been observed with these facilities are reviewed along with theoretical explanations that have been proposed or are commonly accepted. Gaps or uncertainties in understanding of heating-initiated phenomena are discussed together with proposed science questions to be addressed in the future. Suggestions for improvements and additions to existing facilities are presented including important satellite missions which are necessary to answer the outstanding questions in this field.

In [9], two new kinds of topologies called the open-point topology and the bi-point-open topology on C(X), the set of all real-valued continuous functions on a Tychonoff space X, have been introduced and their separation and countability properties have been studied. In the present paper, we study the submetrizability and cardinal functions such as extent, cellularity, weight, pseudocharacter, character and tightness of the spaces C(X) equipped with the open-point and bi-point-open topologies.

In this chapter, we do a brief study of the compact subsets of C(X, Y) with respect to the uniform, fine and graph topologies, where Y is a metric space and prove the Stone-Weierstrass approximation theorem in detail.

In this chapter, we study the cardinal functions on the space C(X) equipped with the uniform, fine and graph topologies. We are primarily interested in five cardinal functions which correspond to the well-known countability properties.

In this chapter, we study the connectedness and some related algebraic properties of the uniform, fine and graph topologies on the space C(X, Y), the set of all continuous functions from a Tychonoff space X to a normed linear space \((Y,||\cdot ||)\). We show that these function spaces are in general not connected and in that case we determine the components and path components of these spaces.

In this chapter, we study various topological properties of the uniform, fine and graph topologies on the space C(X, Y), the set of all continuous functions from a Tychonoff space X to a metric space Y. In particular, we study the metrizability, first countability and various completeness properties of the uniform, fine and graph topologies on C(X, Y).

In the definition of a set-open topology on C ( X ) , the set of all real-valued continuous functions on a Tychonoff space X , we use a certain family of subsets of X and open subsets of R . But instead of using this traditional way to define topologies on C ( X ) , in this paper, we adopt a different approach to define two interesting topologies on C ( X ) . We call them the open-point and the bi-point-open topologies and study the separation and countability properties of these topologies.

The documenting of incidents that affect any employee or work location of your company is an essential part of your security department. Your SOC should have the vital role of capturing all incident report (IR) documentation or phone calls in a centralized incident reporting database that can be utilized by the entire security organization to research past issues, continue documenting further incidents, and conduct analysis. This chapter is not going to tell you the proper ways to write an IR. There are many other books and training materials out there dedicated solely to the purpose of proper IR writing that teach the critical information collection of the who, what, when, where, why, and how of an incident. We recommend that you invest in a couple of them and utilize that training information to properly develop your SOC staff skills. This chapter will provide guidance on how your SOC can be the primary call center for reporting of incidents and collection station for all incidents that have taken place that affect your company.

While many of you who currently have a security operations center of one kind or another may be tempted to skip ahead, confident that your current incarnation is sufficient for your needs, we encourage you to take additional time and walk through these first chapters and challenge your assumptions. You may, for instance, be convinced that since you already have a facility that you can focus on operations and improvement. From hard experience, we’ve learned that a business case is not done once approval for a project or function is in place. As your company evolves through acquisition and change in leadership, you will need to justify all that you do and in some cases change those functions to better fit your new environment. In some cases this will require a downsizing, but expansion is also likely. Regardless, the answer can only be discovered if you challenge your assumptions and evaluate the new environment as if you had just taken over the security leadership role.

This chapter is about how your company should work with your national account vendor or local site vendors and how they work with your SOC. Many larger companies will work with one primary security integrator that will manage their account nationally and/or globally by using local branches or subcontractors to support your company locations. Regardless of how many vendors you use for security installations and service work, you should work with your supply chain and each of your selected vendors to create a company requirements document to go along with your service level agreement or master services agreement for your vendors to understand your expectations for new installations and service work and how they relate to your SOC. This document is just as important to the vendor as it is to your company because their local branches need to be given a copy of the document for them to read and adhere to. The requirements document is important because it is primarily for the local vendors benefit to help ensure they meet your expectations and properly complete their work in relation to your SOC. This writing will focus on one primary national account with a vendor that provides services to each location using their local branches.

Every company has a unique process for creating, reviewing, and approving/denying business cases. The path of creating or improving a SOC is long and challenging. We take for granted that you wish to be successful in the endeavor. If this is true, then in order to have the best chance at success, you must first understand your company. You must understand how it makes money and what it is willing to spend money on. Your best chance at finding this out is to get to know the finance group. Find someone willing to talk about what they do and be prepared to ask good follow-up questions.

In this chapter, we write about the responsibility of presenting to your SOC staff the importance of their duties when they arrive for their first day of work. This will include your mission statement, an introduction to their role as a security console operator (SCO), and why their job is important. We will provide a template SCO job description: staffing schedule, discuss their supervisory authority, and summarize the responsibility of the SOC staff. We will cover the basic duties you need to determine what they will do and discuss what they can do. For the sake of this writing, going forward, we will assume that your SOC is UL certified and requires two SCOs per shift.

The purpose of your SOCs post orders and site procedures is to establish an orderly and productive procedural response to all nonemergency, security, fire, and life safety events affecting and reported to your company. Additionally, the post orders must outline the duties required by your SCOs on a regular basis. The post orders you create or have in place must be followed as written unless ordered to do so by authorized personnel. In this chapter, we will provide some of the basics that must be written into your post orders for you to ensure that you are providing your staff with the most detailed procedures and up-to-date information. Not everything can be written down and SCOs will need to adapt to many different situations that are regularly presented to them. But if a task becomes a regular habit then it should be documented on how to complete the task and who it should be reported to for follow up.

Security awareness is a part of a good security program. It says so in many books and it is true. But why is it true? Most regulations that cover security have some requirement for security awareness training at least annually. Some companies make their own and others buy videos from companies and show them. Some companies have a quiz at the end of the training to make sure employees were paying attention. But what is the actual goal? Is it to check off a box for an auditor by showing them your 100% completion of training? Is it even to get all the employees in your company to remember at least 80% of the security policy one day a year?

As stated earlier, the primary goal of the SOC is to observe and report, then communicate and coordinate. Communication is essential to the success of your SOC. If your applicants do not have good speaking or writing capabilities, then they should not be hired. Your SCO’s primary responsibility is communicating about events and updating those that are in positions of responsibility by sending notifications to ensure that they are aware of the status of the incident. Remember, SCOs should not be placed in a position that they are making decisions about what to, they should be following their post orders that instruct them to take steps such as dispatching security officers, law enforcement, fire department, and/or emergency medical technicians. There are several different forms of communication your SCOs will be using in your SOC to include telephones, cell or mobile phones, handheld radios, pagers, fax machines, email, intercoms, overhead building paging system, perhaps different forms of instant messaging software, and a mass notification alert system. One thing we do not recommend is video communications because that is a distraction from other duties such as alarm monitoring and writing reports. We know some company’s love to have video webcams at everyone’s desk for face-to-face communication but in the case of the SOC all you are doing is taking your SCO’s eyes off their VMS or IDS monitors so they can look at a webcam. Does not make sense. Another reason for not adding webcams into your SOC is the sensitive nature of what you do at times, your SOC might have a posting of a terminated employee hanging on a poster board and that might be visible in the background. You cannot have customers video conferencing into your SOC and run the risk of them seeing something confidential that they should not. The following will help you plan for how your SOC will communicate to your company.

Your SOC will be monitoring alarms through your PACS through network servers, a burglar alarm system through alarm signal receivers or in some cases your SOC may use both systems side by side depending upon the monitoring requirement. Your staff is responsible for assessing and responding to those alarm signals they electronically receive through the various systems your SOC utilizes to secure the perimeter of critical areas within your company’s locations. The purpose of this chapter is to provide a basic guideline for handling the alarms your SOC will monitor.

It may be possible to successfully run a SOC and even a security department without any partners in the business and community, but it is a lot easier getting positive work done with the other company departments and community groups working with your SOC rather than against without them. Developing strategic partnerships takes time and often a large amount of patience. Seek counsel from your peers within the industry because you will never cease to learn from others who are doing things a different way.

Traditionally, a corporate security department doesn’t spend a lot of time thinking about customer service. Most focus on regulatory compliance, access control, loss prevention, and so on. In the last 15 years, some companies have moved toward centralization and the inevitable outcome of a shared services organization. Security departments may or may not be included in that group, but since the only constant in business anymore is change, it may only be a matter a time before you find yourself in that position. In this chapter, we are going to try and convince you that regardless of where you currently report or how your company is structured, you should care about customer service.

Your central station post orders and procedures provide the information and standards to your operators who need to know or have on hand to quickly refer to when to perform their duties. Training your operators is when they learn to utilize the post orders and procedures information that is available to them and necessary to perform their duties. You will need to determine how long to train them for, create a schedule for their training to ensure they see all the shifts, what they need to accomplish the training objectives and create an individual training checklist. Training should be never ending for your central station. As the manager of your SOC, you should always continue to create or present new and challenging training classes or tasks to conduct while they work for your staff. That additional level of training allows them to grow as professionals and understand their job that much more. In this chapter, we will cover the different ways to accomplish this goal.

The primary purpose of a SOC is to aid in the protection of assets of a given company. These assets include but are not limited to material, intellectual property, and people. As long as the primary mission is not negatively impacted, the SOC can perform many other tangential and even completely unrelated tasks.

You’ve done it. Congratulations. You wrote an impressive business case, designed a SOC that was just right for your company and then you hired good people and trained them into a cohesive SOC that has become the security nerve center of your corporation. Regulators and auditors love you because you have all the data on all of the controls they care about most at your fingertips. Time to relax and just enjoy your good standing, right?

Video surveillance should be just as necessary to your SOC as access control. They work best together but video can also work without a PACS alarm system due to motion alarms within video systems. With video, you can “see” what is happening on site. With an alarm in your PACS all you know is that your SOC has received a door held open alarm. By looking at the camera pointed at the door the alarm came in you can see why the door is held open by playing back the video from the last 30 seconds or more and make a quick determination whether it was an actionable alarm that requires dispatch of response. Most likely your SOC staff will see an employee who held the door open too long or that the door did not shut all the way after an employee entered or exited that doorway. Without video, all you know is that there is a door held open alarm, which might mean a burglar has propped that door open while they begin to haul your company’s property out of the building.

International audience; We present supertagging-based models for Tree Adjoining Grammar parsing that use neural network architectures and dense vector representation of supertags (elementary trees) to achieve state-of-the-art performance in unlabeled and labeled attachment scores. The shift-reduce parsing model eschews lexical information entirely , and uses only the 1-best supertags to parse a sentence, providing further support for the claim that supertagging is " almost parsing. " We demonstrate that the embedding vector representations the parser induces for supertags possess linguistically interpretable structure, supporting analogies between grammatical structures like those familiar from recent work in distri-butional semantics. This dense representation of supertags overcomes the drawbacks for statistical models of TAG as compared to CCG parsing, raising the possibility that TAG is a viable alternative for NLP tasks that require the assignment of richer structural descriptions to sentences.

We were involved in a merger at one company where the new CEO stated that if you couldn’t measure it, you shouldn’t be doing it. At the time, that was not a comforting message for a corporate security department. It was 2000, and we tried to benchmark with other companies, but what we found was that few had any metrics and the few that existed were a bit anemic. Metrics are more commonplace today than they were in 2000, but for a traditional security department, it was an odd concept to consider.