Contemporary dynamic market conditions are characterized by high levels of competition. Businesses are forced to make continuous changes in order to maintain a high level of customer’s satisfaction. Contact centers are part of the global economy and a key channel for communication with customers. Access to the contact centers is realized through several channels (telephone, e-mail, fax, web forms, etc.), but the primary method is still a phone call. Most call centers use Interactive Voice Response (IVR) to route users with a particular problem for directing the user to an agent with appropriate capabilities (Skill-based routing – SBR). This type of contact center operation can have a negative impact on the quality considering customer’s experience, due to the complexity and length of the process, which often results in directing calls to the inadequate agent and describing the problem multiple times to reach the right agent. This paper aims at applying machine learning methods based on prior experience with matching customers and agents in order to reduce time and target agents with adequate problem-solving abilities.

Research on how to implement blockchain technology within governance has avoided to further explore on the possibilities of the technology to replace standard nation state architectures. This in turn has created a wave of technological questions directed to better enforce decentralization and security within the popular networks, rather than proposing normative possibilities to be implemented into the institutional framework of the state. This article addresses this issue by analyzing a set of functional areas with the aim of replacing processes, institutions and actors that are often considered as part of the modern bureaucratic nation state. It also drafts functional concepts and recommendations on security issues that should be addressed in any attempt to implement blockchain solutions at the national level.

Many organizations developing software-intensive systems face challenges with high product complexity and large numbers of variants. In order to effectively maintain and develop these product variants, Product-Line Engineering methods are often considered, while Model-based Systems Engineering practices are commonly utilized to tackle product complexity. In this paper, we report on an industrial case study concerning the ongoing adoption of Product Line Engineering in the Model-based Systems Engineering environment at Volvo Construction Equipment (Volvo CE) in Sweden. In the study, we identify and define a Product Line Engineering process that is aligned with Model-based Systems Engineering activities at the engines control department of Volvo CE. Furthermore, we discuss the implications of the migration from the current development process to a Model-based Product Line Engineering-oriented process. This process, and its implications, are derived by conducting and analyzing interviews with Volvo CE employees, inspecting artifacts and documents, and by means of participant observation. Based on the results of a first system model iteration, we were able to document how Model-based Systems Engineering and variability modeling will affect development activities, work products and stakeholders of the work products.

The paper analyses the influence of cigarette butts and waste coffee grounds addition on the properties of the brick clay. The waste materials were added to the clay in amounts of 5 wt.% and 10 wt.%. Standard consistency, plasticity, drying and firing behaviour and refractoriness were tested on the clay sample and the samples with wastes additions. Apparent density, apparent porosity, water absorption, strength and thermal conductivity were investigated on the samples fired at 1173 K. Addition of the waste materials improved thermal insulation characteristics and drying shrinkage, while other properties remain within the required limits for brick industry.

INTRODUCTION Spindle cell carcinoma is a rare subtype of metaplastic breast cancer, with triple-negative (TNBC: estrogen receptor-negative/progesterone receptor-negative/human epidermal growth factor receptor 2-negative) phenotype. It is associated with a marked resistance to conventional chemotherapy and has an overall poor outcome. MATERIALS AND METHODS Twenty-three pure spindle cell carcinomas of the breast (18 primary and 5 recurrent/metastatic) were comprehensively explored for biomarkers of immuno-oncology and targeted therapies using immunohistochemistry and DNA/RNA sequencing. RESULTS The majority (21/23) of spindle cell carcinomas were TNBC. Estrogen and androgen receptor expression above the therapeutic thresholds were detected in 2 cases each. Pathogenic gene mutations were identified in 21 of 23 cases, including PIK3CA, TP53, HRAS, NF1, and PTEN. One case with matched pre- and post-chemotherapy samples exhibited a consistent mutational profile (PIK3CA and HRAS mutations) in both samples. Gene amplifications were present in 5 cases, including 1 case without detectable mutations. The spindle cell carcinomas cohort had consistently low total mutational burden (all below the 80th percentile for the entire TNBC cohort). All tumors were microsatellite stable. Programmed death-ligand 1 expression was observed on both tumor cells (in 7/21 cases), and in tumor-infiltrating immune cells (2/21 cases). CONCLUSIONS Spindle cell carcinomas are characterized by targetable molecular alterations in the majority of cases, but owing to the lack of uniform findings, individual patient profiling is necessary. Detection of individual combinations of biomarkers should improve treatment options for this rare but aggressive disease.

An increasing number of emerging applications, e.g., Internet of Things (IoT), vehicular communications, augmented reality, and the growing complexity due to the interoperability requirements of these systems, lead to the need to change the tools used for the modeling and analysis of those networks. Agent-based modeling (ABM) as a bottom-up modeling approach considers a network of autonomous agents interacting with each other, and therefore represents an ideal framework to comprehend the interactions of heterogeneous nodes in a complex environment. Here, we investigate the suitability of ABM to model the communication aspects of a road traffic management system as an example of an IoT network. We model, analyze, and compare various medium access control (MAC) layer protocols for two different scenarios, namely uncoordinated and coordinated. Besides, we model the scheduling mechanisms for the coordinated scenario as a high-level MAC protocol by using three different approaches: 1) centralized decision maker (DM); 2) DESYNC; and 3) decentralized learning MAC (L-MAC). The results clearly show the importance of coordination between multiple DMs in order to improve the information reporting error and spectrum utilization of the system.

High-intensity training is becoming more popular nowadays when people have less time to engage in prolonged physical activity. Expertly led high intensity training is a safe way to achieve desired fitness goals. The aim of the study was to check if there were significant changes in the concentrations of sodium, potassium, calcium, magnesium, zinc, iron and copper in the blood and urine of twelve trainees after a short but intense training. Blood and urine sampling was performed before and after high intensity training where bodyweight exercises and exercises with external load were used. Statistical analysis was performed using paired t-test (2-tailed) with α=0.05 as statistical significance. The results obtained showed that the measured mineral concentrations varied as a result of intense physical activity, but these variations were small and did not have a general trend of increase or decrease of analyzed mineral content. Based on these results, it can be concluded that, from the standpoint of the mineral concentrations loss, short high-intensity training is safe for the trainee’s health.

Tearful crying is a ubiquitous and mainly human phenomenon. The persistence of this behavior throughout adulthood has fascinated and puzzled many researchers. Scholars have argued that emotional tears serve an attachment function: Tears are thought to act as a social glue that binds individuals together and triggers social support intentions. Initial experimental studies supported this proposition across several methodologies, but these were typically conducted only across Western participants, resulting in limited generalizability. The present study examines this effect across 36 countries spanning all populated continents, providing the most comprehensive investigation of the social effects of tearful crying to-date. Next to testing possible mediating factors, we also examine a number of moderating factors, including the crier’s gender and group membership, the situational valence (positive or negative situations), the social context (in private or public settings), the perceived appropriateness of crying, and trait empathy of the observer. The current work can inform theories on crying across the social sciences.

Due to the increased popularity of robotic systems and their more frequent application, some companies have opted to incorporate modular robotic systems in their assortment. The advantages of such systems are great flexibility in terms of combining components, relatively easy programmability, a wide range of functions that can be performed, the availability of components, as well as modularity in terms of functional and structural connectivity. The disadvantages are reflected by the fact that these systems are not optimized for a particular application. The precision and accuracy of such systems are substantially less than those of the system created exclusively for a particular application. Gaps and dead strokes of moving parts are very influential on the performance of functions and there is relatively little autonomy to such systems. The problem of mutual inarticulation of motors was introduced, and a solution was given to overcome these problems. The observations concerning the aforementioned problems have been explained and the most important features of this approach to robotic systems highlighted.

This commentary is about predicting a woman’s breast cancer risk from her mammogram, building on the work of Wolfe, Boyd and Yaffe on mammographic density. We summarise our efforts at finding new mammogram-based risk predictors, and how they combine with the conventional mammographic density, in predicting risk for interval cancers and screen-detected breast cancers across different ages at diagnosis and for both Caucasian and Asian women. Using the OPERA (odds ratio per adjusted standard deviation) concept, in which the risk gradient is measured on an appropriate scale that takes into account other factors adjusted for by design or analysis, we show that our new mammogram-based measures are the strongest of all currently known breast cancer risk factors in terms of risk discrimination on a population-basis. We summarise our findings graphically using a path diagram in which conventional mammographic density predicts interval cancer due to its role in masking, while the new mammogram-based risk measures could have a causal effect on both interval and screen-detected breast cancer. We discuss attempts by others to pursue this line of investigation, the measurement challenge that allows different measures to be compared in an open and transparent manner on the same datasets, as well as the biological and public health consequences.

In the present work, freeze crystallization studies, as a novel concentration method for aqueous 1,5-diazabicyclo[4.3.0]non-5-enium acetate ([DBNH][OAc]) ionic liquid solution, were conducted. In order to find the appropriate temperature and composition range for freeze crystallization, the solid–liquid equilibrium of a binary [DBNH][OAc]–water compound system was investigated with differential scanning calorimetry (DSC). Results of this analysis showed that the melting temperature of the pure ionic liquid was 58 ℃, whereas the eutectic temperature of the binary compound system was found to be −73 ℃. The activity coefficient of water was determined based on the freezing point depression data obtained in this study. In this study, the lowest freezing point was −1.28 ℃ for the aqueous 6 wt.% [DBNH][OAc] solution. Ice crystal yield and distribution coefficient were obtained for two types of aqueous solutions (3 wt.% and 6 wt.% [DBNH][OAc]), and two freezing times (40 min and 60 min) were used as the main parameters to compare the two melt crystallization methods: static layer freeze and suspension freeze crystallization. Single-step suspension freeze crystallization resulted in higher ice crystal yields and higher ice purities when compared with the single-step static layer freeze crystallization. The distribution coefficient values obtained showed that the impurity ratios in ice and in the initial solution for suspension freeze crystallization were between 0.11 and 0.36, whereas for static layer freeze crystallization these were between 0.28 and 0.46. Consequently, suspension freeze crystallization is a more efficient low-energy separation method than layer freeze crystallization for the aqueous-ionic liquid solutions studied and, therefore, this technique can be applied as a concentration method for aqueous-ionic liquid solutions.