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Aggregating the preferences of a group of experts is a recurring problem in several fields, including engineering design; in a nutshell, each expert formulates an ordinal ranking of a set of alternatives and the resulting rankings should be aggregated into a collective one. Many aggregation models have been proposed in the literature, showing strengths and weaknesses, in line with the implications of Arrow's impossibility theorem. Furthermore, the coherence of the collective ranking with respect to the expert rankings may change depending on: (i) the expert rankings themselves and (ii) the aggregation model adopted. This paper assesses this coherence for a variety of aggregation models, through a recent test based on the Kendall's coefficient of concordance (W), and studies the characteristics of those models that are most likely to achieve higher coherence. Interestingly, the so-called Borda count model often provides best coherence, with some exceptions in the case of collective rankings with ties. The description is supported by practical examples.

The manufacturing field encompasses a number of problems in which some experts formulate their rankings of a set of objects, which should be aggregated into a collective judgment. For example, consider the aggregation of (1) the opinions of designers on alternative design concepts, (2) the opinions of reliability/safety engineers on the criticality of a set of failures, (3) the perceptions of a panel of customers on alternative aesthetic features of a product, etc. For these problems, Kendall’s concordance coefficient (W) can be used to express the degree of agreement between experts in a simple and practical way. Unfortunately, this indicator is applicable to complete rankings only, while experts often find it more practical to formulate incomplete rankings, e.g., identifying only the most/less relevant objects and/or deliberately excluding some of them, if they are not sufficiently relevant or well known. This research aims at extending the use of the traditional W to incomplete rankings, preserving its practical meaning and simplicity. In a nutshell, the proposed methodological approach associates a so-called “midrank” to all objects, even the ones that are not easily comparable with the other ones; subsequently, W can be applied to these midranks. The description is supported by several pedagogical examples.

ISO 9001 certifications for quality management and assurance are widespread worldwide. Since their introduction, more than two decades ago, their geographical diffusion has been studied and analyse...

On January 1, 2015, the Republic of Armenia joined the (Russian-led) Eurasian Economic Union (EAEU) and actually refrained from entering into the alternative Association Agreement with the European Union (EU). Nevertheless, despite the prevalence of historic ties with the scientific community of the EAEU member-states and some push towards that direction, Armenian researchers demonstrate a certain scientific autonomy, which is expressed in numerous international scientific collaborations with researchers from many European countries. This paper proposes a bibliometric analysis of the international scientific collaboration between (i) Armenia and EU countries, and (ii) Armenia and EAEU countries, based on the papers indexed by the Web of Science Core Collection database and the Russian Science Citation Index database. Results indicate that the international collaboration with researchers from countries of both blocks gradually grows, displaying similarities and differences. Globally, Armenian researchers seem to collaborate more with researchers from EU countries rather than EAEU countries. Despite this, individual collaborations with Russia continue to prevail over those with other individual European countries, primarily Germany. Finally, it has been noted that “megaprojects” significantly influence the scientific collaborations between Armenian and foreign researchers.

Human–robot collaboration (HRC) is a gradually consolidating paradigm of the modern industry which combines human and robot skills to make production more flexible. Since the effective implementation of HRC requires a careful analysis of different aspects, related both to robots and humans, there is a real need for a structured methodology to support it. A previous work proposed a multi-dimensional framework to analyze several HRC aspects of a collaborative task. However, identifying the configuration that better exploits the HRC potential is not always trivial, especially among multiple alternative solutions. In addition, the priority levels (weights) assigned to the individual sub-dimensions of the framework, which identify specific design strategies, do not appear explicitly. The goal of this paper is to address these gaps, expanding the previous methodology and proposing the introduction of a multiple-criteria decision analysis (MCDA) method (i.e., ELECTRE-II). The inclusion of a MCDA method allows designers to: (i) express importance weights for each sub-dimension of the framework, and (ii) generate a preference ranking through a structured comparison of alternative HRC configurations. The description is supported by a real industrial application in the automotive field, in which four alternative HRC configurations are analyzed by a team of experts providing a holistic analysis.

Peptides are emerging as a new reliable class of therapeutics and, thanks to their lower cost of production, they are becoming established as perfect drug aspirants. Here, we briefly review the phage display method and its contribution to the identification of peptides of interest for the therapeutic market.

The immunoglobulin B cell receptor (IgBCR) expressed by chronic lymphocytic leukemia (CLL) B cells plays a pivotal role in tumorigenesis, supporting neoplastic transformation, survival, and expansion of tumor clones. We demonstrated that in the same patient, two or more CLL clones could coexist, recognized by the expression of different variable regions of the heavy chain of IgBCR, composing the antigen-binding site. In this regard, phage display screening could be considered the easier and most advantageous methodology for the identification of small peptide molecules able to mimic the natural antigen of the tumor IgBCRs. These molecules, properly functionalized, could be used as a probe to specifically identify and isolate single CLL subpopulations, for a deeper analysis in terms of drug resistance, phenotype, and gene expression. Furthermore, CLL cells express another surface membrane receptor, the CD5, which is commonly expressed by normal T cells. Piece of evidence supports a possible contribution of CD5 to the selection and maintenance of autoreactivity in B cells and the constitutive expression of CD5 on CLL cells could induce pro-survival stimuli. In this brief research report, we describe a peptide-based single-cell sorting using as bait the IgBCR of tumor cells; in the next step, we performed a quantitative analysis of CD5 expression by qRT-PCR related to the expressed IgBCR. Our approach could open a new perspective for the identification, isolation, and investigation of all subsets of IgBCR-related CLL clones, with particular attention to the more aggressive clones.

Receptor tyrosine kinases (RTKs) regulate critical physiological processes, such as cell growth, survival, motility, and metabolism. Abnormal activation of RTKs and relative downstream signaling is implicated in cancer pathogenesis. Phage display allows the rapid selection of peptide ligands of membrane receptors. These peptides can target in vitro and in vivo tumor cells and represent a novel therapeutic approach for cancer therapy. Further, they are more convenient compared to antibodies, being less expensive and non-immunogenic. In this review, we describe the state-of-the-art of phage display for development of peptide ligands of tyrosine kinase membrane receptors and discuss their potential applications for tumor-targeted therapy.

Cells can communicate through special “messages in the bottle”, which are recorded in the bloodstream inside vesicles, namely exosomes. The exosomes are nanovesicles of 30–100 nm in diameter that carry functionally active biological material, such as proteins, messanger RNA (mRNAs), and micro RNA (miRNAs). Therefore, they are able to transfer specific signals from a parental cell of origin to the surrounding cells in the microenvironment and to distant organs through the circulatory and lymphatic stream. More and more interest is rising for the pathological role of exosomes produced by cancer cells and for their potential use in tumor monitoring and patient follow up. In particular, the exosomes could be an appropriate index of proliferation and cancer cell communication for monitoring the minimal residual disease, which cannot be easily detectable by common diagnostic and monitoring techniques. The lack of unequivocal markers for tumor-derived exosomes calls for new strategies for exosomes profile characterization aimed at the adoption of exosomes as an official tumor biomarker for tumor progression monitoring.

Alzheimer’s disease (AD), a neurodegenerative disease, is linked to a variety of internal and external factors present from the early stages of the disease. There are several risk factors related to the pathogenesis of AD, among these exosomes and microRNAs (miRNAs) are of particular importance. Exosomes are nanocarriers released from many different cell types, including neuronal cells. Through the transfer of bioactive molecules, they play an important role both in the maintenance of physiological and in pathological conditions. Exosomes could be carriers of potential biomarkers useful for the assessment of disease progression and for therapeutic applications. miRNAs are small noncoding endogenous RNA sequences active in the regulation of protein expression, and alteration of miRNA expression can result in a dysregulation of key genes and pathways that contribute to disease development. Indeed, the involvement of exosomal miRNAs has been highlighted in various neurodegenerative diseases, and this opens the possibility that dysregulated exosomal miRNA profiles may influence AD disease. The advances in exosome-related biomarker detection in AD are summarized. Finally, in this review, we highlight the use of exosomal miRNAs as essential biomarkers in preclinical and clinical studies in Alzheimer’s disease, also taking a look at their potential clinical value.

A rather common problem in the manufacturing field includes: (i) a collection of objects to be compared on the basis of the degree of some attribute, (ii) a set of judges that individually express their subjective judgments on these objects, and (iii) a single collective judgment, which is obtained by fusing the previous subjective judgments. The goal of this contribution is to develop a new technique that combines the Thurstone’s Law of Comparative Judgment with an ad hoc response mode based on preference orderings. Apart from being relatively practical and user-friendly, this technique allows to express the collective judgment of objects on a ratio scale and is applicable to a variety of practical contexts in the field of manufacturing. The description of the proposed technique is integrated with the application to a practical case study.

The tumor microenvironment is a dynamic and interactive supporting network of various components, including blood vessels, cytokines, chemokines, and immune cells, which sustain the tumor cell’s survival and growth. Murine models of lymphoma are useful to study tumor biology, the microenvironment, and mechanisms of response to therapy. Lymphomas are heterogeneous hematologic malignancies, and the complex microenvironment from which they arise and their multifaceted genetic basis represents a challenge for the generation and use of an appropriate murine model. So, it is important to choose the correct methodology. Recently, we supported the first evidence on the pro-oncogenic action of IBTK in Myc-driven B cell lymphomagenesis in mice, inhibiting apoptosis in the pre-cancerous stage. We used the transgenic Eμ-myc mouse model of non-Hodgkin’s lymphoma and Ibtk hemizygous mice to evaluate the tumor development of Myc-driven lymphoma. Here, we report that the allelic loss of Ibtk alters the immunophenotype of Myc-driven B cell lymphomas, increasing the rate of pre-B cells and affecting the tumor microenvironment in Eμ-myc mice. In particular, we observed enhanced tumor angiogenesis, increasing pro-angiogenic and lymphangiogenic factors, such as VEGF, MMP-9, CCL2, and VEGFD, and a significant recruitment of tumor-associated macrophages in lymphomas of Ibtk+/- Eμ-myc compared to Ibtk+/+ Eμ-myc mice. In summary, these results indicate that IBTK haploinsufficiency promotes Myc tumor development by modifying the tumor microenvironment.

Research funding is essential to promote the scientific activity of researchers and the dissemination of their results. Simplifying, funding schemes can be classified in two categories—competitive and non-competitive—with several corresponding advantages and shortcomings, which are widely discussed in the scientific literature. The researchers of Politecnico di Torino (i.e., one of the major Italian technical universities) have recently been funded through a non-competitive research funding, consisting of 14k€ for every single researcher in each of the last three years (i.e., from 2017 to 2019), for a total of 42k€. This somewhat unusual initiative—also called “diffused funding” (DF)—represents an important opportunity to investigate the effects of the relatively large allocation of non-competitive funding to single researchers. In this regard, this paper investigates the effects of the DF on the researchers’ scientific output, according to four dimensions of analysis: publishing productivity, publishing diffusion/impact, journal reputation, and international research relations. Preliminary results do not indicate any improvement in the publication output, at least in the short term.

The Failure Mode and Effects Analysis (FMEA) is a powerful tool to design and maintain reliable systems (products, services or manufacturing processes), investigating their potential failure modes ...

Quality Function Deployment (QFD) is a structured tool that supports the design of new products/services, translating customer requirements into technical and process characteristics. The so-called...

Recent studies show that the combined use of Large-Volume Metrology (LVM) systems (e.g., laser trackers, rotary-laser automatic theodolites (R-LATs), photogrammetric cameras, etc.) can lead to a systematic reduction in measurement uncertainty and a better exploitation of the available equipment. Unfortunately, the sensors of a specific LVM system are usually able to localize only specific targets (i.e., active/passive elements positioned in the measurement volume) and not necessarily those related to other systems (e.g., the reflective markers for photogrammetric cameras cannot be used for R-LATs or laser trackers); this represents an obstacle when using combinations of different LVM systems. This paper describes the design of a new modular probe, with different typologies of targets and integrated sensors, which allows to simplify the measurement process. The probe is versatile as the number of targets, their typology and spatial position can be customized depending on the combination of LVM systems in use. A detailed analysis of the technical and functional characteristics of the probe is followed by the presentation of a mathematical/statistical model for the real-time probe localization. Description is supported by realistic application examples.

A decision-making problem diffused in various practical contexts is that of aggregating multi-agent judgements into a consensus ordering, in the case the agents' importance is expressed through a set of weights. A crucial point in this aggregation is that the consensus ordering well reflects the input data, i.e., agents' judgements and importance. The scientific literature encompasses several aggregation techniques, even if it does not include a versatile tool for a quantitative assessment and comparison of their performance. The aim of this paper is introducing a new indicator (p), which allows to verify the degree of consistency between consensus ordering and input data. This indicator is simple, intuitive and independent from the aggregation technique in use; for this reason, it can be applied to a variety of practical contexts and used to compare the results obtained through different aggregation techniques, when applied to a specific problem. The description is supported by various application examples.

Cardiac myxomas are the most common benign cardiac tumor. We investigated the immunohistochemical properties of 11 surgically excised cardiac myxomas, in order to analyze the correlation between macrophages and mast cell populations and clinical parameters. CD68+/CD163−/iNOS− (M0) cells represent the most abundant macrophage phenotype; however, CD68+/CD163+ cells (M2) were also frequent. CD68+/iNOS+ (M1) elements were rare. Mast cells, defined as a population of c-kit (CD117)+ and/or tryptase+ cells were also detected. Statistical analysis showed significant correlations between c-kit (CD117)+ and tryptase, CD68 and erythrocyte sedimentation rate (ESR), ESR and red blood cell count (RBC), and prothrombin time and platelet count. The inverse correlation between RBCs in peripheral blood and ESR suggested that anemia associated with chronic inflammatory disease is a noncasual event in patients suffering from cardiac myxoma. Mechanical hemolysis may be only a minor component of anemia, according to the lack of correlation between echographic surface and RBCs. Moreover, tumor size did not correlate with ESR, showing that inflammatory state may depend from both tumor cells population and inflammatory infiltrate. In the future, modulation of macrophage polarization in cardiac myxomas might represent important therapeutic target.

In many practical contexts, it is often required to classify some objects of interest into predetermined unordered quality categories. This operation—referred to as quality classification problem—has received considerable attention in many fields of research, such as Analytical Chemistry, Materials Science, Medicine, Manufacturing, Quality Engineering/Management, Decision Analysis. Assuming that multiple agents perform subjective assignments of categories to the objects of interest, a further problem is that of fusing these assignments into global classifications. To this purpose, the mode and the weighted mode are very practical measures, as long as agents are equi-important or their (different) importance is expressed in the form of a set of weights. Unfortunately, these measures are not appropriate for quality classification problems where the agents’ importance is expressed in the form of a rank ordering (hierarchy). The aim of this article is to present a new method, which addresses the latter quality classification problem in a relatively simple and practical way. The peculiarity of this method is that the different importance of agents determines a different priority in considering their assignments and not a different weight of these assignments. A detailed description of the new method is supported by a realistic example in the Analytical Chemistry field.

Quality function deployment (QFD) is a consolidated management tool for supporting the design of new products/services and the relevant production/supply processes, starting from the so-called voice of the customer (VoC). QFD includes several operative phases, ranging from the VoC collection to the definition of the technical features of production/supply processes. The first phase entails the construction of the so-called house of quality (HoQ), i.e., a planning matrix, which translates the customer requirements (CRs) into measurable engineering characteristics (ECs) of the product/service. One of the main goals of this phase is the definition of relationships between CRs and ECs, and the prioritization of these ECs, taking account of (i) their relationships with CRs and (ii) the importance of the related CRs. Given that data are collected from customers through questionnaires or interviews, both of these inputs are based on linguistic/ordinal scales. In the traditional approach, represented by the independent scoring method (ISM), ordinal data are arbitrarily enriched with cardinal properties. The current scientific literature encompasses a number of alternative approaches but, even for most of them, cardinal properties are mistakenly attributed to data collected on ordinal scales. This paper proposes a method based on a consolidated ME-MCDM (multi expert / multiple criteria decision making) technique, which is able to perform the EC prioritization without incurring in the aforementioned issue. This method is able to aggregate data evaluated on ordinal scales, overcoming controversial assumptions of data cardinality and avoiding any arbitrary and/or artificial “scalarization” of the data. On the other hand, its application is relatively simple and intuitional, compared to other proposed approaches alternative to the ISM, which often are conceptually complicated and difficult to implement. Furthermore, the proposed method can be effectively used when both CR importances and relationship matrix coefficients are rated on different ordinal scales and, being easily automatable, it can be effortlessly integrated into existing QFD software applications. In the paper, after a general description of the theoretical principle of the method, several application examples are presented and discussed.

Part 15: Collaborative Decision-Making in Value Creation Networks; International audience; Collaborative Human-Robot workcells introduce robot-assisted operations in small-volume production or assembly processes, where conventional automation is noncompetitive. Unfortunately, the collaborative work of humans and robots sharing the same work area and/or working on the same assembly operation may pose unprecedented problems and failure risks. Failure Mode, Effects and Criticality Analysis (FMECA) is a popular tool to design reliable processes, which investigates the potential failure modes from the perspective of severity, occurrence and detection. The traditional FMECA approach requires the assessment of failure modes to be carried out collectively by a group of experts. Nevertheless, in the field of Human-Robot collaboration, experts are often unlikely to agree in their judgements, due to the almost inexistent historical records. Additionally, the traditional approach is not appropriate for decentralized production/assembly processes.The paper revisits the traditional approach and integrates it with the ZMII-technique – i.e., a recent aggregation technique developed by the authors – which overcomes some limitations, including but not limited to: (i) arbitrary categorization and questionable aggregation of the expert judgments, (ii) disregarding the variability in these judgments, and (iii) disregarding the result uncertainty. The description is supported by a real-life application example.

Identification of epitopes recognized by tumour B cells could provide insights into the molecular mechanisms of B cell tumorigenesis through aberrant B cell receptor (BCR) signalling. Here, we analysed the structure of eleven peptides binders of BCRs expressed in Chronic Lymphocytic Leukemia (CLL) patients in order to identify the chemical features required for cross-reactive binding to different CLL clonotypes. Four cross-reactive (CR) and seven no-cross-reactive (NCR) peptides were analysed by means of GRID molecular interaction fields, ligand-based pharmacophore and 3D-QSAR approaches. Based on pharmacophore model, two peptides were generated by specific amino acids substitutions of the parental NCR peptides; these new peptides resumed the common chemical features of CR peptides and bound the CLL BCR clonotypes recognized by CR peptides and parental NCR peptides. Thus, our computational approach guided the pharmacophore modelling of CR peptides. In perspective, peptide binders of CLL BCR clonotypes could represent a powerful tool for computational modelling of epitopes recognized by tumour B cells clones.

The authors recently presented a technique (denominated “ZM”) to fuse multiple (subjective) preference rankings of some objects of interest—in manufacturing applications—into a common unidimensional ratio scale Franceschini and Maisano J Intell Manuf, 2019. Although this technique can be applied to a variety of decision-making problems in the manufacturing field, it is limited by a response mode requiring the formulation of complete preference rankings, i.e., rankings that include all objects. Unfortunately, this model is unsuitable for some practical contexts—such as decision-making problems characterized by a relatively large number of objects and field surveys—where respondents can barely identify the more/less preferred objects, without realistically being able to construct complete preference rankings. The purpose of this paper is to develop a new technique (denominated “ZMII”) which also “tolerates” incomplete preference rankings, e.g., rankings with the more/less preferred objects only. This technique borrows the underlying postulates from the Thurstone’s Law of Comparative Judgment and uses the Generalized Least Squares method to obtain a ratio scaling of the objects of interest, with a relevant uncertainty estimation. Preliminary results show the effectiveness of the new technique even for relatively incomplete preference rankings. Description is supported by an application example concerning the design of a coach-bus seat.

The problem of collective decision by design teams has received considerable attention in the scientific literature of engineering design. A much debated problem is that in which multiple designers formulate their individual preference rankings of different design alternatives and these rankings should be aggregated into a collective one. This paper focuses the attention on three basic research questions: (1) “How can the degree of concordance of designer rankings be measured?”, (2) “For a given set of designer rankings, which aggregation model provides the most coherent solution?”, and (3) “To what extent is the collective ranking influenced by the aggregation model in use?”. The aim of this paper is to present a novel approach that addresses the above questions in a relatively simple and agile way. A detailed description of the methodology is supported by a practical application to a real-life case study.

A relatively diffused quality decision problem is that of classifying some objects of interest into predetermined nominal categories. This problem is particularly interesting in the case: (i) multi...

In the last decade, a growing number of studies focused on the qualitative/quantitative analysis of bibliometric-database errors. Most of these studies relied on the identification and (manual) examination of relatively limited samples of errors. Using an automated procedure, we collected a large corpus of more than 10,000 errors in the two multidisciplinary databases Scopus and Web of Science (WoS), mainly including articles in the Engineering-Manufacturing field. Based on the manual examination of a portion (of about 10%) of these errors, this paper provides a preliminary analysis and classification, identifying similarities and differences between Scopus and WoS. The analysis reveals interesting results, such as: (i) although Scopus seems more accurate than WoS, it tends to forget to index more papers, causing the loss of the relevant citations given/obtained, (ii) both databases have relatively serious problems in managing the so-called Online-First articles, and (iii) lack of correlation between databases, regarding the distribution of the errors in several error categories. The description is supported by practical examples concerning a variety of errors in the Scopus and WoS databases.

Like most sports, alpine skiing has international regulations – its regulations specifically designed by the FIS, that is, the Fédération Internationale de Ski or International Ski Federation– aimed at coordinating competitions and rating athletes. FIS points, as they are called, represent the core of the rating system, as they facilitate the rating of athletes involved in competitions for each of the five alpine skiing disciplines, that is, slalom, giant slalom, super-G, downhill, and combined. The objective of this article is to analyse the current rating system, giving special attention to the FIS points’ construction and updating system and focusing on the potential weaknesses. Two major weaknesses emerge from this analysis: (1) the questionable update process of the FIS points, based on the average of the best two results obtained in a discipline of interest, and (2) the lack of a general rating of athletes based on their eclecticism, that is, the ability to obtain good results in as many different disciplines as possible. The second part of the article presents some proposals for sorting out the above weaknesses. The description therein is supported by several practical examples, based on real and hypothetical data.

Omitted citations--i.e., missing links between a cited paper and the corresponding citing papers--are a consequence of several bibliometric-database errors. To reduce these errors, databases may undertake two actions: (1) improving the control of the (new) papers to be indexed, i.e., limiting the introduction of "new" dirty data, and (2) detecting and correcting errors in the papers already indexed by the database, i.e., cleaning "old" dirty data. The latter action is probably more complicated, as it requires the application of suitable error-detection procedures to a huge amount of data. Based on an extensive sample of scientific papers in the Engineering-Manufacturing field, this study focuses on old dirty data in the Scopus and WoS databases. To this purpose, a recent automated algorithm for estimating the omitted-citation rate of databases is applied to the same sample of papers, but in three different-time sessions. A database's ability to clean the old dirty data is evaluated considering the variations in the omitted-citation rate from session to session. The major outcomes of this study are that: (1) both databases slowly correct old omitted citations, and (2) a small portion of initially corrected citations can surprisingly come off from databases over time.

Recent studies have shown that the Scopus bibliometric database is probably less accurate than one thinks. As a further evidence of this fact, this paper presents a structured collection of several weird typologies of database errors, which can therefore be classified as horrors . Some of them concern the incorrect indexing of so-called Online-First paper, duplicate publications, and the missing/incorrect indexing of references. A crucial point is that most of these errors could probably be avoided by adopting some basic data checking systems. Although this paper does not provide a quantitative and systematic analysis (which will be provided in a future publication), it can be easily understood that these errors can have serious consequences such as: (i) making it difficult or even impossible to retrieve some documents, and (ii) distorting bibliometric indicators/metrics relating to journals, individual scientists or research institutions. Our attention is focused on the Scopus database, although preliminary data show that the Web of Science database is far from being free from these errors. The tone of the paper is deliberately provocative, in order to emphasize the seriousness of these errors.

Chronic lymphocytic leukemia (CLL) is a B-lymphoproliferative disease, which consists of the abnormal proliferation of CD19/CD5/CD20/CD23 positive lymphocytes in blood and lymphoid organs, such as bone marrow, lymph nodes and spleen. The neoplastic transformation and expansion of tumor B cells are commonly recognized as antigen-driven processes, mediated by the interaction of antigens with the B cell receptor (BCR) expressed on the surface of B-lymphocytes. The survival and progression of CLL cells largely depend on the direct interaction of CLL cells with receptors of accessory cells of tumor microenvironment. Recently, much interest has been focused on the role of tumor release of small extracellular vesicles (EVs), named exosomes, which incorporate a wide range of biologically active molecules, particularly microRNAs and proteins, which sustain the tumor growth. Here, we will review the role of CLL-derived exosomes as diagnostic and prognostic biomarkers of the disease.

The balance between cell survival and cell death represents an essential part of human tissue homeostasis, while altered apoptosis contributes to several pathologies and can affect the treatment efficacy. Impaired apoptosis is one of the main cancer hallmarks and some types of lymphomas harbor mutations that directly affect key regulators of cell death (such as BCL-2 family members). The development of novel techniques in the field of immunology and new animal models has greatly accelerated our understanding of oncogenic mechanisms in MYC-associated lymphomas. Mouse models are a powerful tool to reveal multiple genes implicated in the genesis of lymphoma and are extensively used to clarify the molecular mechanism of lymphoma, validating the gene function. Key features of MYC-induced apoptosis will be discussed here along with more recent studies on MYC direct and indirect interactors, including their cooperative action in lymphomagenesis. We review our current knowledge about the role of MYC-induced apoptosis in B-cell malignancies, discussing the transcriptional regulation network of MYC and regulatory feedback action of miRs during MYC-driven lymphomagenesis. More importantly, the finding of new modulators of apoptosis now enabling researchers to translate the discoveries that have been made in the laboratory into clinical practice to positively impact human health.

This chapter introduces the problem of constructing a quality management system, i.e., a system aimed at suitably driving and controlling an organization. To this purpose, it is essential to (1) identify the most characteristic processes of the organization of interest; and (2) monitor and evaluate them regularly. This demonstrates the important role played by indicators even at a “normative” level.

Although the focus of the monograph is on indicators, this chapter “takes a step back”, (re)analysing the concept of measurement in the broadest sense. Precisely, the first part of the chapter recalls the historical evolution of this concept, focusing on physical measurements and their unification. Subsequently, the attention shifts on the theory of measurement by Stevens and several other measurement theorists, who had the great merit of extending the concept of measurement beyond physical quantities, identifying important properties, implications, and (mis)uses. Particular attention is paid to the concept of meaningfulness of statements using measurement scales.

The present chapter discusses a core problem of quality management for organizations: establishing and maintaining a performance measurement system. Flowing from the mission and strategic planning of one organization, a performance measurement system is supposed to include the data to collect, analyze, report and, finally, use to make sound business decisions.

The goal of the present chapter is to introduce the reader to some criticalities concerned with indicators, which are treated in an organic way in the rest of the book. For the purpose of example, the attention is focused on several popular indicators: the HDI (Human Development Indicator), some air-quality indicators (AQI, ATMO and IQA) and the scoring indicators used for the Olympic decathlon. These indicators are analysed individually, emphasizing their qualities and drawbacks. Additionally, this chapter mentions some indicator properties that are formalized in detail in Chaps. 3 and 4.

Indicators are helpful tools to represent (complex) processes, supporting evaluations and decisions. Unfortunately, selecting “good” indicators is not so trivial for at least two reasons: (i) there are not organic methods to support this activity and (ii) the success of this activity may depend on the complexity of the process of interest and the experience/intuition of users. The aim of the present chapter is to provide a taxonomy of some desirable properties of indicators, trying to answer several research questions, such as: “How many indicators should be used for representing a certain process?”, “Is there an optimal set of indicators?”, and “Can we aggregate/fuse multiple (sub)indicators into a single one?”. Description is accompanied by many pedagogical examples and an operational procedure to support the construction of indicators.

Secretome of primary cultures is an accessible source of biological markers compared to more complex and less decipherable mixtures such as serum or plasma. The protonation state (PS) of secretome reflects the metabolism of cells and can be used for cancer early detection. Here, we demonstrate a superhydrophobic organic electrochemical device that measures PS in a drop of secretome derived from liquid biopsies. Using data from the sensor and principal component analysis (PCA), we developed algorithms able to efficiently discriminate tumour patients from non-tumour patients. We then validated the results using mass spectrometry and biochemical analysis of samples. For the 36 patients across three independent cohorts, the method identified tumour patients with high sensitivity and identification as high as 100% (no false positives) with declared subjects at-risk, for sporadic cancer onset, by intermediate values of PS. This assay could impact on cancer risk management, individual’s diagnosis and/or help clarify risk in healthy populations., Diagnostics: Proton state of secreted proteins in blood helps identify cancer A blood test that measures whether molecules secreted by cells contain titratable proton atoms can accurately discriminate between patients who have cancer and those who don’t. Titratable species may in turn influence the protonation state of a solution, i.e. the number of protons added to and the net charge of that solution. A team led by Natalia Malara from University Magna Graecia in Catanzaro, Italy and Enzo Di Fabrizio from the King Abdullah University of Science and Technology in Thuwal, Saudi Arabia, Francesco Gentile from the University Federico II in Naples, Italy, and Nicola Coppedè from the Institute of Materials for Electronics and Magnetism in Parma, Italy, created an eletrochemical device that can detect faulty metabolism by quantifying the proportion of secreted proteins with and without extra protons—an indicator of abnormal cell division, proliferation and invasion. The researchers tested the device on blood samples from patients with solid tumors and healthy controls. The method identified cancer patients with a high degree of accuracy. If the findings are confirmed in larger trials, the test could help with the screening, diagnosis and management of cancer.

The role of macrophages in the growth and the progression of tumors has been extensively studied in recent years. A large body of data demonstrates that macrophage polarization plays an essential role in the growth and progression of brain tumors, such as gliomas, meningiomas, and medulloblastomas. The brain neoplasm cells have the ability to influence the polarization state of the tumor associated macrophages. In turn, innate immunity cells have a decisive role through regulation of the acquired immune response, but also through humoral cross-talking with cancer cells in the tumor microenvironment. Neoangiogenesis, which is an essential element in glial tumor progression, is even regulated by the tumor associated macrophages, whose activity is linked to other factors, such as hypoxia. In addition, macrophages play a decisive role in establishing the entry into the bloodstream of cancer cells. As is well known, the latter phenomenon is also present in brain tumors, even if they only rarely metastasize. Looking ahead in the future, we can imagine that characterizing the relationships between tumor and tumor associated macrophage, as well as the study of circulating tumor cells, could give us useful tools in prognostic evaluation and therapy. More generally, the study of innate immunity in brain tumors can boost the development of new forms of immunotherapy.

Recent studies show that the combined use of Large-Volume Metrology (LVM) systems can lead to a systematic reduction in measurement uncertainty and a better exploitation of the available equipment. This is actually possible using a recently developed modular probe, which is equipped with different typologies of targets and integrated inertial sensors. The goal of this paper is to present a new mathematical/statistical model for the real-time localization of this probe. This model is efficient, as it is based on a system of linearized equations, and effective, as the equations are weighed with respect to their uncertainty contribution.

Designing quality-inspection procedures may be difficult for short-run manufacturing processes, due to poor effectiveness of the classical statistical process control (SPC) techniques for these processes. This paper proposes a practical methodology to guide quality designers in selecting the more effective and economically convenient inspection procedures. First, the process of interest is decomposed into a number of steps, in which specific defects can occur. Next, several parameters related to inspection effectiveness and cost are combined into a probabilistic model. The more effective and economically convenient inspection procedures can finally be determined using two specific synthetic indicators. A case study concerning a short-run production of hardness testing machines is presented and discussed.

Quality function deployment (QFD) is a useful tool to improve the design/development process of products and services. The initial phases of the QFD process—that is, those concerning the collection and analysis of the so-called voice of the customer—are..

The focus of this paper is on the prioritization of customer requirements (CRs) in the quality function deployment (QFD) process. There are numerous techniques for this task, which are based on different types of judgements (e.g., in the form of preference orderings, relative importance ratings, paired comparisons), generally collected by questionnaires/interviews. Unfortunately, many of these techniques violate some properties of the scales on which judgements are defined and/or are not flexible and user-friendly for respondents. This paper introduces a prioritization technique based on a recent algorithm—denominated as generalized Yager’s algorithm—aimed at fusing the preference orderings by multiple respondents into a single ordering. This technique can be applied even when (1) some CRs are tied or omitted in the individual preference orderings, and (2) respondents have a hierarchical importance ranking. Also, the procedure is automatable and relatively robust and provides a solution which is consistent with the preference orderings. The description is supported by a realistic application example, concerning the prioritization of QFD’s CRs in the design of an aircraft seat.

The article entitled, "Multi-Target Modular probe for Large-Volume Metrology" submitted in Recent Patents on Engineering (RPENG) by Dr. Domenico A. Maisano has been withdrawn from the journal in accordance with BSP Editorial Policies.

Chordoid meningioma (CM) is a rare subtype of meningioma, which represents only 0.5% of all meningiomas. It is classified as Grade II according to the World Health Organization classification because of its tendency to relapse. Pathological and clinical characteristics have been studied in order to forecast the future evolution of the lesions. However, information about infiltration of macrophagic elements and mast cells is very scarce. The authors analyzed the immunohistochemical patterns of three cases and a relapse of CM, in order to verify whether infiltrating macrophages are in a polarized state and what would be the proportion between such elements and mastocytes. Results suggest that macrophages in CMs are mainly in a non-polarized or M2 state and their abundance might be associated with a major potential of relapse; additionally, there is an inverse correlation between the number of mast cells and macrophages. Further studies are requested in order to confirm these intriguing data.

For nearly a decade, several national exercises have been implemented for assessing the Italian research performance, from the viewpoint of universities and other research institutions. The penultimate one – i.e., the VQR 2004–2010, which adopted a hybrid evaluation approach based on bibliometric analysis and peer review – suffered heavy criticism at a national and international level. The architecture of the subsequent exercise – i.e., the VQR 2011–2014, still in progress – is partly similar to that of the previous one, except for a few presumed improvements. Nevertheless, this other exercise is suffering heavy criticism too. This paper presents a structured discussion of the VQR 2011–2014, collecting and organizing some critical arguments so far emerged, and developing them in detail. Some of the major vulnerabilities of the VQR 2011–2014 are: (1) the fact that evaluations cover a relatively small fraction of the scientific publications produced by the researchers involved in the evaluation, (2) incorrect and anachronistic use of the journal metrics (i.e., ISI Impact Factor and similar ones) for assessing individual papers, and (3) conceptually misleading criteria for normalizing and aggregating the bibliometric indicators in use.

DOI--i.e., Digital Object Identifier--is a character string, which univocally identifies entities that are object of intellectual property. In bibliometrics, DOIs are used for univocally identifying scientific papers. The aim of this short communication is to raise the reader's awareness of bibliometric database errors in DOI indexing, in particular, the incorrect assignment of a single DOI to multiple papers. This error is quite interesting since DOI is commonly regarded as an effective means to identify scientific articles unambiguously. For the purpose of example, a short list of DOIs, which have been wrongly assigned by the Scopus database to multiple papers, is shown. Although being relatively rare, DOI indexing errors should be considered by bibliometricians when querying bibliometric databases by DOI.

Last decades witness an increasing interest in Large-Scale/Large-Volume Dimensional Metrology (LSDM). Many fields of application, ranging from construction to shipbuilding and aerospace, have shown more and more accurate and versatile systems for geometric control and tolerancing. Especially in the last ten years, optical technology has registered a fundamental step forward both in terms of metrological performances, versatility and convenience of use. This is further demonstrated by the current large diffusion of laser tracker and photogrammetric systems. The growth is also complemented by the development of new standards, even though a comprehensive body specific for LSDM is still lacking. The twofold aim of the present survey is to present a bibliographical and bibliometric analysis of the field and to propose a scheme of classification of the main current approaches. As an output of this paper, a “LSDM Multi-perspective Model” is introduced, according to which dominant technologies and restrictions are analyzed with the aim of individuating current lacks and defining the roadmap for future development of new instruments and systems.

A recent paper (Canavero et al., 2014. Journal of the American Society for Information Science and Technology, doi:10.1109/TPC.2013.2255935) performed a bibliometric analysis of an extensive set of scientific journals within the Engineering field, published by IEEE (Institute of Electrical and Electronics Engineers). The analysis was based on (i) the citation impact of journal articles and (ii) the reputation of journal authors in terms of total scientific production and relevant citation impact. The goal of this paper is to complement the prior analysis, investigating on the different citation cultures of these journals, depending on the sub-field/specialty of interest. To perform this evaluation, it is suggested a novel technique, which takes into account the connections between journals and some highly specialized communities of scientists, known as IEEE Technical Societies and Councils. After showing significant differences in terms of propensity to cite, probably attributable to the large variety of sub-fields and specialties covered by IEEE journals, it is presented a simplified technique for the sub-field normalization of the results of the prior study. The main contribution of this work is (1) providing an empirical confirmation of the complexity of the problem of normalization, even for journals within the same field but different sub-fields/specialties, and (2) showing how the use of highly specialized information on a journal reference sub-field(s) may be helpful for improving the estimation of the journal propensity to cite. Description is supported by a large amount of empirical data.