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Early-stage ideation is a critical step in the design process. Mind maps are a popular tool for generating design concepts and in general for hierarchically organizing design insights. We explore an application for high-level concept synthesis in early stage design, which is typically difficult due to the broad space of options in early stages (e.g., as compared to parametric automation tools which are typically applicable in concept refinement stages or detail design). However, developing a useful mind map often demands a considerable time investment from a diverse design team. To facilitate the process of creating mind maps, we present an approach to crowdsourcing both concepts and binning of said concepts, using a mix of human evaluators and machine learning. The resulting computer-aided mind map has a significantly higher average concept novelty, and no significant difference in average feasibility (quantity can be set independently) as manually generated mind maps, includes distinct concepts, and reduces cost in terms of the designers’ time. This approach has the potential to make early-stage ideation faster, scalable and parallelizable, while creating alternative approaches to searching for a breadth and diversity of ideas. Emerging research explores the use of machine learning and other advanced computational techniques to amplify the mind mapping process. This work demonstrates the use of the both the EM-SVD, and HDBSCAN algorithms in an inferential clustering approach to reduce the number of one-to-one comparisons required in forming clusters of concepts. Crowdsourced human effort assists the process for both concept generation and clustering in the mind map. This process provides a viable approach to augment ideation methods, reduces the workload on a design team, and thus provides an efficient and useful machine learning based clustering approach.

Killer cell immunoglobulin like receptors (KIRs) have a principal role in regulating the effector functions of NK cells, particularly in viral infections. The major ligands for KIRs are human leukocyte antigen (HLA) class I molecules. The aim of this study is to investigate the possible association of KIR genes, their known HLA ligands and compound KIR–HLA genotypes with hepatitis B virus (HBV) infection. Our study group consisted of 202 Iranian HBV-infected patients (52 spontaneously recovered, 50 asymptomatic carriers, 50 chronic sufferers and 50with liver cirrhosis) and 100 ethnic-matched healthy control subjects. KIR and HLA genotyping was performed by a polymerase chain reaction–sequence-specific primer (PCR–SSP). The frequencies of the KIR2DL5A, KIR2DS1, and KIR3DS1 genes were significantly elevated in recovered individuals when compared with both control and patient groups. Also, KIR2DL5, and KIR3DP1 full were escalated in recovered individuals in comparison with patient groups. In addition, HLA-Bw4 ligand and HLA-A Bw4 were highly frequent in recovered individuals compared with healthy controls. Furthermore, the KIR3DS1 + HLA-Bw4, KIR3DS1 + HLA-Bw4 Iso80 , and KIR3DS1 + HLA-A Bw4 genotypes were significantly more common in recovered individuals than both healthy control and patient groups. Interestingly, AA genotype had less frequency and Bx had higher frequency in recovered individuals compared with both healthy control and patient groups. Our findings suggest a potential impact of the NK cells’ activating phenotype that leads to the HBV clearance in infected individuals.

System architecture and modularity decisions are inherent to preliminary concept design. Prior modularity research has considered minimizing interactions between modules and increasing the commonality among modular product variants. Effective approaches include function structure partitioning guidelines, affinity analysis, or matrix clustering algorithms. We consider here designs with field constraints, such as situations when elements cannot be placed in certain regions such as a high-temperature field, a high-pressure field, a high magnetic field, etc. which place constraints on modularity choices. Practical design guidelines are developed here for modularity considering field constraints. Two types of guidelines are proposed, field separation and concept generation. The field separation guidelines propose zonal boundaries within which system modules need be confined. The concept generation guidelines propose how to violate the field constraints through new concepts. Moving functionality from one side of a field boundary to the other is nontrivial and involves new concept generation for the modules to function at the higher or lower field values. The guidelines are defined and illustrated via multiple common examples as well as two extended case studies. We demonstrate the approach using field boundaries on an electric motor controller and on a medical contrast injector, and also use of fields to generated novel concepts. The guidelines support for modularity concept and embodiment decisions.

Toll-like receptors (TLRs) are inevitable elements for immunity development and antibody production. TLRs are in close interaction with Bruton's tyrosine kinase which has been found mutated and malfunctioned in the prototype antibody deficiency disease named X-linked agammaglobulinemia (XLA). TLRs' ability was evaluated to induce transcription of TLR-negative regulators, including suppressor of cytokine signaling 1 (SOCS1), interleukin-1 receptor-associated kinase 3 (IRAK-M), tumor necrosis factor alpha-induced protein 3 (TNFAIP3, A20), and Ring finger protein 216 (RNF216), and Tumor necrosis factor-α (TNF-α) and Interferon-α (IFN-α) production via Lipopolysaccharides (LPS) and CpG-A oligodeoxynucleotides (CpG-A ODN). Measured by TaqMan real-time polymerase chain reaction (PCR), meaningfully increased transcripts of SOCS1 and RNF216 were found in XLA peripheral blood mononuclear cells (PBMCs). Also, TLR inductions of XLA have led to similar downregulations in the regulator's transcription which was different from that in healthy donors. Cytokine measurement by enzyme-linked immunosorbent assay (ELISA) revealed a significant lower TNF-α production both before and after LPS. By selected molecules in this study, TLRs' potential defectiveness range expands TLRs expression, downstream signaling, and cytokine production. The results show new potential elements that could play a part in TLRs defect and pathogenesis of agammaglobulinemia as well.

Regulatory B cells (Bregs) are immune-modulating cells that affect the immune system by producing cytokines or cellular interactions. These cells have immunomodulatory effects on the immune system by cytokine production. The abnormalities in Bregs could be involved in various disorders such as autoimmunity, chronic infectious disease, malignancies, allergies, and primary immunodeficiencies are immune-related scenarios. Ongoing investigation could disclose the biology and the exact phenotype of these cells and also the assigned mechanisms of action of each subset, as a result, potential therapeutic strategies for treating immune-related anomalies. In this review, we collect the findings of human and mouse Bregs and the therapeutic efforts to change the pathogenicity of these cells in diverse disease.

Selective immunoglobulin A deficiency (SIgAD) is the most prevalent type of primary immunodeficiency disorder. The phenotypic feature of SIgAD is related to a defect in B lymphocyte differentiation into plasma cell-producing immunoglobulin A (IgA). In this review, we summarize the recent advances in this regard. Genetic (including major histocompatibility complex [MHC] and non-MHC genes), immunologic (including B and T lymphocyte subsets abnormality), cytokines/chemokines and their related receptors, apoptosis and microbiota defects are reviewed. The mechanisms leading to SIgAD are most likely multifactorial and it can be speculated that several pathways controlling B cells functions or regulating epigenetic of the IGHA gene encoding constant region of IgA heavy chain and long-term survival of IgA switched memory B cells and plasma cells may be defective in different SIgAD patients.

The innate immune response drives early events in Mycobacterium tuberculosis infection. Since human genetic variation is an important determinant in the outcome of infection with M. tuberculosis, we typed polymorphisms in the innate immune molecules, such as natural-resistance-associated macrophage protein 1 (NRAMP1), Vitamin D receptor (VDR), Tumor necrosis factor alpha (TNF-α), intercellular adhesion molecule1 (ICAM-1), Toll-like receptor 2 (TLR2) and Toll-like receptor 4 (TLR4) in a case-control study of pulmonary tuberculosis in Iranian population. We conducted an association study and included 96 patients and 122 matched healthy individuals. We used single ARMS-PCR technique to simultaneously genotype fourteen polymorphisms in this survey. Among all fourteen polymorphisms that were examined, three polymorphisms were significantly different between case and control groups. The TNF -308A polymorphism showed significant increase in allele and genotype frequencies among patients compared to control individuals [-308A allele: 19.3 vs. 9.4%, GA genotype: 28.1 vs. 17.2%, AA genotype: 5.2 vs. 0.8%; Corrected P (Pc)

T helper 9 (TH9) cells are considered as newly classified helper T cells that have an important role in the regulation of immune responses. Since these cells preferentially produce IL-9, these cells are termed TH9 cells. Recently, the role of TH9 and its signature cytokine (IL-9) has been investigated in a wide range of diseases, including autoimmunity, allergy, infections, cancer and immunodeficiency. Herein, we review the most recent data concerning TH9 cells and IL-9 as well as their roles in disease. These insights suggest that TH9 cells are a future target for therapeutic intervention.

Common variable immunodeficiency (CVID), a clinically symptomatic primary immunodeficiency disease (PID), is characterized by hypogammaglobulinemia leading to recurrent infections and various complications. Recently, some defects in the signaling of TLRs have been identified in CVID patients which led us to investigate the expression of TLR4 and 9 negative regulatory molecules and their upregulation status following their activation. Using TaqMan real-time PCR, SOCS1, TNFAIP3, RFN216, and IRAK-M transcripts among peripheral blood mononuclear cells (PBMCs) were measured with/without TLR4 and 9 activations. TLR4 and 9 were activated by lipopolysaccharide (LPS) and unmethylated CpG-oligodeoxynucleotide (CpG-ODN), respectively. Production of IFN-α and TNF-α cytokines, as a part of the functional response of mentioned TLRs, was also measured using ELISA. Deficient transcripts of IRAK-M and TNFAIP3 in unstimulated PBMCs and lower production of TNF-α and IFN-α after treatments were observed. Upregulation of RFN216 and TNFAIP3 after TLR9 activation was abnormal compared to healthy individuals. Significant correlations were found between abnormal IRAK-M and TNFAIP3 transcripts, and lymphadenopathy and inflammatory scenarios in patients, respectively. It seems that the transcriptional status of some negative regulatory molecules is disturbed in CVID patients, and this could be caused by the underlying pathogenesis of CVID and could involve complications like autoimmunity and inflammatory responses.

Past work has demonstrated that simulating an extraordinary user scenario could have an impact on increasing designer empathy and creativity. It is likely, however, that an individual’s background could make a difference on how such simulated scenarios influence designers and how well the design method works. In this paper, we study the impact of demography and personal connection of the participants to any given simulated scenario versus their response to different empathic simulation workshops. With a variety of design tools and techniques available, understanding such influencing factors could help designers decide on the appropriate design tool for effective ideation. In this study, we investigated the effect of 81 (49 female and 32 male) users from three different workshops that simulated three different extraordinary user scenarios. Results of the study show that personal connection to a population being simulated significantly affects the impact a simulated scenario has on evoking creativity and empathy. And, for the given set of participants, gender did not show significant impact on the participants’ response.

Analogy-making has been deemed one of the core cognitive mechanisms which play a role in human creative thinking activities such as design and art. Designers can make use of analogies in various stages of design including ideation, planning and evaluation. However, human analogy-making is limited by experience and reliance of human memory on superficial attributes rather than relational or causal structure during analogy retrieval. In this regard, different design-by-analogy tools have been developed to assist designers in analogical reasoning. Analogical reasoning tools can be viewed as either based on hand-coded structured knowledge or natural-language-based design-by-analogy tools. The former are naturally limited in extent and scope to that which was hand coded [1]. Alternatively, natural language analogical reasoning can leverage the abundantly available textual resources. Current text-based analogy research for design have relied on analogies between individual word meanings. This leaves open consideration of the relational structure of the language where the relational similarity of texts can indicate a significant analogy. In this article, we develop four computational models of analogy that capture relational structure of the text. This includes spatial representation of semantics, multi-level deep neural reasoning, graph matching based model and transformation-based model. The models are then combined together into an ensemble model to achieve acceptable level of analogical accuracy for the end-user. The underlying design-related knowledge upon which analogies were drawn includes engineering ontologies, function hierarchy and raw patent texts. Instantiating this analogical reasoning model in design concept analogy retrieval system, we show this approach can help retrieve meaningful analogies from the World Intellectual Property Organization (WIPO) patent repository. We demonstrate this for a particular design problem.

Modularity is an approach to manage the design of complex systems by partitioning and assigning elements of a concept to simpler subsystems according to a planned architecture. Functional-flow heuristics suggest possible modules that have been demonstrated in past products, but using them still leaves it to the designer to choose which heuristics make sense in a certain architecture. This constitutes an opportunity for a designer to take other constraints and objectives into account. With large complex systems, the number of alternative groupings of elements into modular chunks becomes exponentially large and some form of automation would be beneficial to accomplish this task. Clustering algorithms using the design structure matrix (DSM) representation search the space of alternative relative positioning of elements and present one ideal outcome ordering which “optimizes” a modularity metric. Beyond the problems of lack of interactive exploration around the optimized result, such approaches also partition the elements in an unconstrained manner. Yet, typical complex products are subject to constraints which invalidate the unconstrained optimization. Such architectural partitioning constraints include those associated with external force fields including electric, magnetic, or pressure fields that constrain some functions to perform or not perform in different regions of the field. There are also supplier constraints where some components cannot be easily provided with others. Overall, it is difficult to simply embed all objectives of modular thinking into one metric to optimize. We develop a new type of interactive clustering algorithm approach considering multiple objectives and partitioning constraints. Partitioning options are offered to a designer interactively as a sequence of clustering choices between elements in the architecture. A designer can incorporate constraints that determine the compatibility or incompatibility of elements by choosing among alternative groupings progressively. Our aim is to combine computational capability of clustering algorithms with the flexibility of manual approaches. Through applying these algorithms to a MRI machine injector, we demonstrate the benefits of interactive cooperation between a designer and modularity algorithms, where constraints can be naturally considered.

Product modularity has been the subject of considerable research and debate in last decade. Various metrics have been proposed in design community to measure the level of modularity and various procedures have been developed to search for ideal modular architectures. These procedures are based on either manual heuristics or computer clustering algorithms. Both approaches are aimed at finding more ideal architectures by optimizing a definition of modularity. However, different desirable criteria are often in conflict with each other and improving one criteria is not feasible without a compromising effect on another. Here, we propose a procedure to find non-dominated optimal architectures where our criteria of interest are intra-cluster and extra-cluster costs. We demonstrate an approach where a designer can consider the architecture that minimizes total cost of interactions, but also allows visualization of the trade-off in increased and decreased costs when considering nearby architectures with more or less modules. An alternative approach has been to consider granularity and hierarchical clustering schemes. We also show through an example that cost optimal architectures for any choice of number of modules are not necessarily obtainable via dividing or aggregating modules, and restricting to hierarchical clustering algorithms produces non-optimal solutions at different numbers of modules.Copyright © 2015 by ASME