Sustainable development is one of the most important preconditions for preserving resources and balanced functioning of a complete supply chain in different areas. Taking into account the complexity of sustainable development and a supply chain, different decisions have to be made day-to-day, requiring the consideration of different parameters. One of the most important decisions in a sustainable supply chain is the selection of a sustainable supplier and, often the applied methodology is multi-criteria decision-making (MCDM). In this paper, a new hybrid MCDM model for evaluating and selecting suppliers in a sustainable supply chain for a construction company has been developed. The evaluation and selection of suppliers have been carried out on the basis of 21 criteria that belong to all aspects of sustainability. The determination of the weight values of criteria has been performed applying the full consistency method (FUCOM), while a new rough complex proportional assessment (COPRAS) method has been developed to evaluate the alternatives. The rough Dombi aggregator has been used for averaging in group decision-making while evaluating the significance of criteria and assessing the alternatives. The obtained results have been checked and confirmed using a sensitivity analysis that implies a four-phase procedure. In the first phase, the change of criteria weight was performed, while, in the second phase, rough additive ratio assessment (ARAS), rough weighted aggregated sum product assessment (WASPAS), rough simple additive weighting (SAW), and rough multi-attributive border approximation area comparison (MABAC) have been applied. The third phase involves changing the parameter ρ in the modeling of rough Dombi aggregator, and the fourth phase includes the calculation of Spearman’s correlation coefficient (SCC) that shows a high correlation of ranks.

Sustainability is one of the main challenges of the recent decades. In this regard, several prior studies have used different techniques and approaches for solving this problem in the field of sustainability engineering. Multiple criteria decision making (MCDM) is an important technique that presents a systematic approach for helping decisionmakers in this field. The main goal of this paper is to review the literature concerning the application of MCDM methods in the field of sustainable engineering. The Web of Science (WoS) Core Collection Database was chosen to identify 108 papers in the period of 2008–2018. The selected papers were classified into five categories, including construction and infrastructure, supply chains, transport and logistics, energy, and other. In addition, the articles were classified based on author, year, application area, study objective and problem, applied methods, number of published papers, and name of the journal. The results of this paper show that sustainable engineering is an area that is quite suitable for the use of MCDM. It can be concluded that most of the methods used in sustainable engineering are based on traditional approaches with a noticeable trend towards applying the theory of uncertainty, such as fuzzy, grey, rough, and neutrosophic theory.

The rising number of IoT devices is accelerating the research on new solutions that will be able to efficiently deal with unreliable connectivity in highly dynamic computing applications. To improve the overall performance in IoT applications, there are multiple communication solutions available, either proprietary or open source, all of which satisfy different communication requirements. Most commonly, for this kind of communication, developers choose REST HTTP protocol as a result of its ease of use and compatibility with the existing computing infrastructure. In applications where mobility and unreliable connectivity play a significant role, ensuring a reliable exchange of data with the stateless REST HTTP protocol completely depends on the developer itself. This often means resending multiple request messages when the connection fails, constantly trying to access the service until the connection reestablishes. In order to alleviate this problem, in this paper, we combine REST HTTP with random linear network coding (RLNC) to reduce the number of additional retransmissions. We show how using RLNC with REST HTTP requests can decrease the reconnection time by reducing the additional packet retransmissions in unreliable highly dynamic scenarios.

Two-dimensional (2D) materials have emerged as the ideal candidates for many applications, including nanoelectronics, low-power devices, and sensors. Several 2D materials have been shown to possess large Seebeck coefficients, thus making them suitable for thermoelectric (TE) energy conversion. Whether even higher TE power factors can be discovered among the ≈2000 possible 2D materials (Mounet et al 2018 Nat. Nanotechnol. 13 246–52) is an open question. This study aims at formulating selection rules to guide the search for superior 2D TE materials without the need for expensive atomistic simulations. We show that a 2D material having a combination of low effective mass, higher separation in the height of the step-like density of states, and valley splitting, which is the energy difference between the bottom of conduction band and the satellite valley, equal to 5 kBT will lead to a higher TE power factor. Further, we find that inelastic scattering with optical phonons plays a significant role: if inelastic scattering is the dominant mechanism and the energy of the optical phonon equals 5 kBT, then the TE power factor is maximized. Starting from a model for carrier transport in MoS2 and progressively introducing the aforementioned features results in a two-orders-of-magnitude improvement in the power factor. Compared to the existing selection rules or material descriptors, features identified in this study provide the ability to comprehensively evaluate TE capability of a material and helps in identifying future TE materials suitable for applications in waste-heat scavenging, thermal sensors, and nanoelectronics cooling.

Biosensors are nowadays a powerful alternative to conventional analytical techniques for controlling the quality of not only natural water but also process water used by the food industry during the production process, as well as wastewater prior to release into natural watercourses. The goal is to provide the required quality and safety of water from the standpoint of heavy metal contamination. The basic and most important characteristics of biosensors are high sensitivity, short response time, specificity, and relatively low production cost. Biosensors can detect the presence and measure the content of various toxic substances (pesticides, heavy metals, etc.) not only in water but also in food. Detection of contaminants, primarily heavy metals in water used in food production processes, is a potential area of biosensor application in the food industry. Biosensors can be adapted for direct and continuous (online) monitoring by measuring certain analytes that can affect the quality and safety of water. This chapter will give an overview of the development and application of biosensors in order to control the quality and safety of water from the standpoint of the presence of heavy metals.

Objectives: Increased C. difficile infection rates were observed during the last decade, as well as the onset of complicated forms of the disease. The primary objective of this study was to report the first outbreak of C. difficile in a Serbian hospital, aiming to determine clinical and environmental factors associated with the outbreak. The secondary objective was to describe outbreak control measures taken.Design: The retrospective cohort study conducted from 18 April to 22 May 2013 in Serbian healthcare. Ninety-five patients hospitalized at the Department for orthopedic surgery during the CDI outbreak.Results: Prophylactic antibiotic therapy was identified among 93.3% patients with and 87.9% without C. difficile infection. The multivariate logistic regression analysis has shown that the independent risk factors for C. difficile infection incidence are the age beyond 70 (OR = 4.5; 95%CI = 1.1-18.2; p = .031) and the length of antibiotic therapy (OR = 1.5; 95%CI = 1.1-2.1; p = .017).Conclusion: The length of antibiotic prophylaxis is linked with the incidence. Orthopedic departments have a risk of C. difficileinfection. Infection control measure, antimicrobial stewardship programs and compliance to guidelines for the prescribing of antibiotics play important role in the prevention of C. difficile infection burden.

With the ever increasing cell densities in wireless networks, it is desired to enable more self-X features, such as self-configuration. Setting the network parameters in an autonomous manner is not only more time efficient but also increases network performance and reduces the probability of a human error. Among numerous network settings, one of the key parameters that requires such autonomous configuration is the cell ID (CID). It is used during fundamental procedures, such as network access, decoding, or handover, and therefore, its configuration is crucial for network operation. A complete CID management framework together with a centralized method for CID assignment is presented in this paper. It is not only applicable to multiple mobile standards but is also compatible with multi-vendor equipment, since it is based on the TR-069 management protocol. The proposed approach mitigates CID conflicts when there is a high level of reuse. Moreover, in the 4G case it also prevents neighbors from using different CID but with the same reference signal pattern, which avoids significant interference. The proposed method is evaluated in an enterprise small cell scenario, and in comparison with the baseline third generation partnership project approach, significant reductions of assignment conflicts are demonstrated.

The objective of this study was to investigate causal associations between cattle farms’ management practices and reproductive disorders (abortion, stillbirth, retention of placenta, metritis). Besides, direct causal associations between farms’ management and reproductive infections (Chlamydia abortus, Coxiella burnetii, and Neospora caninum), reproductive disorders and infections were also investigated in this study. As a secondary objective, constraints that affect the production in cattle farms were examined. The study was carried out in the north-western (Una-Sana), western (Canton 10) and central part (Central Bosnia Canton) of Bosnia and Herzegovina. A total of 201 farms were selected for participation. A semi-structured questionnaire-based interview was conducted among farmers/managers from January 1st to August 31st, 2015. The 40 questions were divided into three groups: socio-demographic, management, and information on reproductive performances in cattle. Supplementary questions were asked about the perceived primary constraints of the production. A multivariable mixed-effects logistic regression was used to screen management factors for potential statistical influence. All investigated outcomes were associated with farms’ management. The final multivariable models were merged into a Structural Equation Model (SEM). The causal model was then specified graphically. The SEM model showed that herds that experienced abortions (OR=4.3) and stillbirth (OR=6.7) were associated with N. caninum seropositivity. Also, herds that experienced retention of placenta were strongly associated with the occurrence of metritis (OR=10.1). C. abortus and C. burnetii herd seropositivities were mainly associated with environmental factors and contact with potential intermediate hosts. Our study demonstrated that management practices on dairy farms in Bosnia and Herzegovina contributed to the occurrence of severe reproductive outcomes and reproductive infections. N. caninum seems to be an infectious agent that substantially contributed to the reproductive underperformance. Further we demonstrate the need for using causal models in understanding complex relationships.

Thermal changes in water cause many metabolic changes that manifest themselves in physiological fish adaptations. The analysis of hematologic and biochemical blood parameters provides important information on environmental influences on the health status of fish. The hematocrit (HCT) (l/l), hemoglobin concentration (Hb) (g/l), mean corpuscular volume (MCV) (fl), mean corpuscular hemoglobin (MCH) (pg), mean corpuscular hemoglobin concentration (MCHC) (g/l) and red blood cells (RBC) (x1012/L) were analyzed. Animals were grouped into two groups: control (n=10) and experimental (n=16). The experimental fish were exposed to 28°C for 30 min. Puncture of the heart was done and the blood without anticoagulant was analyzed. During hyperthermia, an increase in hematological parameters was observed, except for MCV values that were low. Significant differences were established only for the number of erythrocytes and the hematocrit values (p<0.05). The results showed a decrease in MCV and an increase in the value of other erythrocyte parameters. Significant changes in the number of erythrocyte and hematocrit values were found. Some hematological parameters such as erythrocyte and MCV values are significant stress indicators and can serve us as important factors for physiological adaptations of fish. The carp shows excellent ability to adjust to temperature variations that can be seen through the analysis of hematological status.

Of the four species of the genus Satureja (Lamiaceae) that are recognized in Bosnia and Herzegovina, S. subspicata has the the widest distribution. It is taxonomically challenging species of geographically limited distribution and little data on its genetic diversity throughout its range is available. We sampled six geographically distinct populations from Bosnia and Herzegovina and applied nrDNA (ITS1, ITS2), chloroplast markers (matK and trnL) and AFLP to examine genetic diversity of S. subspicata in the center of its distribution range and to explore the possibility of establishing the species DNA barcode. AFLP analysis showed large genetic differentiation among populations as well as moderate correlation between genetic distance among populations and geographic distance among locations. MatK has not proven useful in distinguishing S. subspicata from sympatric species. However, nrDNA sequences provided necessary resolution power, with ITS2 being more informative. Estimates of evolutionary divergence between nrDNA sequences obtained in our research and homologous sequences of sympatric Satureja deposited in the GenBank reveal closer relationship between geographically proximate populations of different species and slight divergence within S. subspicata sequences pool. This outcome highlights the importance of considering overall genetic diversity across the distribution range of a species when assigning DNA barcode.

Objective: The accuracy and applicability of various cardiovascular disease (CVD) risk calculators may not be same in different populations. Wecompared 5 RFS for CVD risk on patients from Bosnia an...