A significant challenge in the rational design of organic thermoelectric materials is to realize simultaneously high electrical conductivity and high induced-voltage in response to a thermal gradient, which is represented by the Seebeck coefficient. Conventional wisdom posits that the polymer alone dictates thermoelectric efficiency. Herein, we show that doping — in particular, clustering of dopants within conjugated polymer films — has a profound and predictable influence on their thermoelectric properties. We correlate Seebeck coefficient and electrical conductivity of iodine-doped poly(3-hexylthiophene) and poly[2,5-bis(2-octyldodecyl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione-3,6-diyl)-alt-(2,2′;5′,2′′;5′′,2′′′-quaterthiophen-5,5′′′-diyl)] films with Kelvin probe force microscopy to highlight the role of the spatial distribution of dopants in determining overall charge transport. We fit the experimental data to a phonon-assisted hopping model and found that the distribution of dopants alters the distribution of the density of states and the Kang–Snyder transport parameter. These results highlight the importance of controlling dopant distribution within conjugated polymer films for thermoelectric and other electronic applications. Designing organic thermoelectric materials with high electrical conductivity and Seebeck coefficient is challenging due to the direct relationship between these two properties. Here, the authors explore the role of dopant spatial distribution on thermoelectric performance in conjugated polymers.

ABSTRACT In the bauxite-bearing area of Jajce (Bosnia & Herzegovina), exploitation of karst bauxite has occurred for more than 40 years, during which time extensive geological and mining research was also conducted. Here, the geological map of the Jajce bauxite bearing-area (Bosnia & Herzegovina) at a scale of 1:25.000 is presented, accompanied by a geological column and regional geological cross-sections. The map shows the main stratigraphic and tectonic features and positions of the bauxite deposits of the area. This research area covers 343 km2, divided into two structural units with four bauxite districts, Liskovica, Bešpelj, Crvene Stijene and Poljane. The Liskovica-Bešpelj structural unit is tectonically very complex, characterized by W-E trending structures in subvertical, vertical and overturned positions. The Crvene Stijene-Poljane structural unit is characterized by gentle folds and normal faults. The geological map summarizes all the available data and represents the necessary basis for further geological and mining research of the area.

This paper presents a numerical analysis of a reinforced concrete beam in which the concrete and reinforcement are above the yield strength of the material. Further, the procedure for determining the relationship between the cross-sectional forces and the deformations of the layered cross-section of a rod is described. For a short rod with reduced stiffness of the EI and EA cross-sections, a stiffness matrix with variable members is formed. The applicability of the proposed analysis method for the material nonlinearity in a beam calculation is demonstrated through a numerical example. The aim of the present paper is to show the flow of plastification and the load deformation of the system nodes. Finally, the results of the manual deformation calculation system are compared with the results from SCIA software.

Radno mjesto je okruženje unutar kojeg čovjek provede najveći dio aktivnog dijela svojega života. Događanja unutar radnog okruženja, tretman radnika na radnom mjestu, kao i atmosfera koja se stvara unutar radne organizacije umnogome utječu, ne samo na raspoloženje, produktivnost i učinkovitost radnika, već vrlo često i na njegovo zdravlje. Diskriminacija na radnom mjestu je jedan od negativnih, ponižavajućih i degradirajućih oblika tretmana radnika koji, zbog intenziteta posljedica koje proizvodi za pojedinca i njegovo, prije svega, psihičko zdravlje, njegovu obitelj, radnu organizaciju i društvo u cjelini, zaslužuje posebnu pozornost u razmatranju uzroka i posljedica ove negativne pojave. Pri tome je posebno značajno punu pozornost posvetiti iznalaženju adekvatnih načina prevencije diskriminacije kako do njezinih negativnih posljedica uopće ne bi niti došlo ili kako bi se one smanjile na najmanju moguću mjeru. U primjeni različitih modela prevencije diskriminacije, posebno djelotvornima su se pokazali modeli koji uvažavaju postojanje različitosti među ljudima, te ih ne smatraju preprekama, već upravo korisnim resursima za razvoj radne organizacije, kao i u stvaranju ugodne radne atmosfere i povećanju kvalitete i produktivnosti rada. Stoga je ovaj rad posvećen modelu stvaranja kulture tolerancije, primjeni tzv. pozitivnih mjera, te diversity managementu, kao mogućnostima koje stoje na raspolaganju kao modeli prevladavanja problema različitosti među ljudima u radnim odnosima, te ulozi antidiskriminacijskog zakonodavstva na tom polju.

This paper describes a rational approach to improve the existing guidelines for road design in the regions of Slovenia, Croatia, Bosnia and Herzegovina, and Serbia in order to determine the carriageway crossfall in curves. In these guidelines there are certain shortcomings in determination of crosfall in comparison to some other European countries guidelines. During the last decades, worldwide and in Europe specifically, significant studies have been conducted on the issue of the operating speed and its implementation into the design process. Most European countries have been implementing this concept. The new German guidelines went a step further and introduced a new concept of a self-explaining class road. Using the results of research carried out in Croatia, this work focuses only on a determination of the carriageway crossfall based on operating speed, separately observing new and existing roads. Whereas the new road segments require implementing the principle of a consistent route, an existing road network can be safely improved only by introducing the criteria of the determination of crossfall in curves based on the operating speed.

Ensuring access to reliable and sustainable power supply is becoming more and more challenging due to a combination of factors such as more frequent power grid outages caused by extreme weather events, the large-scale introduction of renewable energy resources that increases the complexity of the power system, but also aging infrastructure, supply and demand imbalance and power theft in some areas. Combined, all these factors can cause outages and together they can make electricity supply unreliable. The implications of this are many, ranging from minor inconveniences to major failures of critical infrastructures. A potential solution to ensure power supply during outages is to use local generation in the form of renewable resources to supply energy. This paper proposes a community-based mechanism that demonstrates that when community members can determine for themselves how excess energy generation is distributed, the power supply of specific members can be ensured. Self-determination is achieved by prioritizing and differentiating between community members as well as automatically and continuously redistributing energy, thereby adapting to sudden changes in supply and demand. Simulation results show that the proposed mechanism can be used to empower local communities to decide for themselves how local resources are distributed during events such as outages, ensuring prolonged power supply for differentiated members of affected communities. Harnessing the potential of renewable resources and smart technologies for intelligent coordination through empowerment of consumers to become pro-active participants is a promising solution for the future power systems.

This paper analyses information literacy competencies of students at the Department of Comparative Literature and Library Science, Faculty of Philosophy, University of Sarajevo that offers bachelor's degree and master's degree in library science. Survey on information literacy competencies of library science students at the Department was realized by the online questionnaire for self-assessment that was developed on the basis of Permutation Model Components with the purpose to obtain insight in student’s perception of their information literacy competencies, to detect to what degree students improve their information literacy competencies and confidence during studies and what possible difficulties they face in this process. This is particularly important considering that there is no separate information literacy course adopted in Departments curricula but the information literacy related content is offered and taught in different courses. Analysis expectedly reveals that in general students feel confident in their information literacy competencies, that their information literacy competencies progressively improve during their studies, but also that students consider that the introduction of a stand-alone information literacy course would greatly contribute to the simpler and faster improvement of their information literacy competencies.

This paper presents an off-body channel model for polarized communications with dynamic users. The model is based on Geometrical Optics and Uniform Theory of Diffraction and accounts for free space propagation, reflections, and diffractions. It allows for arbitrary antennas’ polarizations and gain patterns and supports a number of on-body antenna placements. In order to take the influence of users’ motion into account, a mobility model for wearable antennas on dynamic users is used. Signal depolarization mechanisms are identified, and simulations are performed to analyze the influence of user dynamics on the channel. The results show that significant polarization mismatch losses occur due to wearable antenna rotations, resulting in received power variations up to 37.5 dB for the line-of-sight component and 41.4 dB for the scattered one. The importance of taking signal polarization into account is demonstrated by comparing the simulation results between polarized and nonpolarized channel models in a free space propagation scenario, where a difference up to 53 dB in between the two is observed.

Background: Preclinical ultrasound (US) and contrast-enhanced ultrasound (CEUS) imaging have long been used in oncology to noninvasively measure tumor volume and vascularity. While the value of preclinical US has been repeatedly demonstrated, these modalities are not without several key limitations that make them unattractive to cancer researchers, including: high user-variability, low throughput, and limited imaging field-of-view (FOV). Herein, we present a novel robotic preclinical US/CEUS system that addresses these limitations and demonstrates its use in evaluating tumors in 3D in a rodent model. Methods: The imaging system was designed to allow seamless whole-body 3D imaging, which requires rodents to be imaged without physical contact between the US transducer and the animal. To achieve this, a custom dual-element transducer was mounted on a robotic carriage, submerged in a hydrocarbon fluid, and the reservoir sealed with an acoustically transmissive top platform. Eight NOD/scid/gamma (NSG) female mice were injected subcutaneously in the flank with 8×109 786-O human clear-cell renal cell carcinoma (ccRCC) cells. Weekly imaging commenced after tumors reached a size of 150 mm3 and continued until tumors reached a maximum size of 1 cm3 (∼4-5 weeks). An additional six nude athymic female mice were injected subcutaneously in the flank with 7 × 105 SVR angiosarcoma cells to perform an inter-operator variability study. Imaging consisted of 3D B-mode (conventional ultrasound) of the whole abdomen ( Results: Wide-field US images reconstructed from 3D volumetric data showed superior FOV over conventional US. Several anatomical landmarks could be identified within each image surrounding the tumor, including the liver, small intestines, bladder, and inguinal lymph nodes. Tumor boundaries were clearly delineated in both B-mode and BVD images, with BVD images showing heterogeneous microvessel density at later timepoints suggesting tumor necrosis. Excellent agreement was measured for both inter-reader and inter-operator experiments, with alpha coefficients of 0.914 (95% CI: 0.824-0.948) and 0.959 (0.911-0.981), respectively. Conclusion: We have demonstrated a novel preclinical US imaging system that can accurately and consistently evaluate tumors in rodent models. The system leverages cost-effective robotic technology, and a new scanning paradigm that allows for easy and reproducible data acquisition to enable wide-field, 3D, multi-parametric ultrasound imaging. Note: This abstract was not presented at the meeting. Citation Format: Tomasz Czernuszewicz, Virginie Papadopoulou, Juan D. Rojas, Rajalekha Rajamahendiran, Jonathan Perdomo, James Butler, Max Harlacher, Graeme O9Connell, Dzenan Zukic, Paul A. Dayton, Stephen Aylward, Ryan C. Gessner. A preclinical ultrasound platform for widefield 3D imaging of rodent tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1955.

Abstract Motivation Despite the remarkable advances in sequencing and computational techniques, noise in the data and complexity of the underlying biological mechanisms render deconvolution of the phylogenetic relationships between cancer mutations difficult. Besides that, the majority of the existing datasets consist of bulk sequencing data of single tumor sample of an individual. Accurate inference of the phylogenetic order of mutations is particularly challenging in these cases and the existing methods are faced with several theoretical limitations. To overcome these limitations, new methods are required for integrating and harnessing the full potential of the existing data. Results We introduce a method called Hintra for intra-tumor heterogeneity detection. Hintra integrates sequencing data for a cohort of tumors and infers tumor phylogeny for each individual based on the evolutionary information shared between different tumors. Through an iterative process, Hintra learns the repeating evolutionary patterns and uses this information for resolving the phylogenetic ambiguities of individual tumors. The results of synthetic experiments show an improved performance compared to two state-of-the-art methods. The experimental results with a recent Breast Cancer dataset are consistent with the existing knowledge and provide potentially interesting findings. Availability and implementation The source code for Hintra is available at https://github.com/sahandk/HINTRA.

Hyoid bone movement is an important physiological event during swallowing that contributes to normal swallowing function. In order to determine the adequate hyoid bone movement, clinicians conduct an X-ray videofluoroscopic swallowing study, which even though it is the gold-standard technique, has limitations such as radiation exposure and cost. Here, we demonstrated the ability to track the hyoid bone movement using a non-invasive accelerometry sensor attached to the surface of the human neck. Specifically, deep neural networks were used to mathematically describe the relationship between hyoid bone movement and sensor signals. Training and validation of the system were conducted on a dataset of 400 swallows from 114 patients. Our experiments indicated the computer-aided hyoid bone movement prediction has a promising performance when compared with human experts’ judgements, revealing that the universal pattern of the hyoid bone movement is acquirable by the highly nonlinear algorithm. Such a sensor-supported strategy offers an alternative and widely available method for online hyoid bone movement tracking without any radiation side-effects and provides a pronounced and flexible approach for identifying dysphagia and other swallowing disorders.

This paper presents a method for distributed generation (DG) allocation in low voltage distribution network based on the total annual energy loss reduction and Artificial Neural Network (ANN). The proposed method is applied to the PV solar based DG allocation problem in the low voltage distribution network using realistic network data and measurements. This research is motivated by numerous realistic issues faced by the Distribution System Operator in the area of DG planning. The main objective of this work is to develop, test and validate a robust method for DG allocation which can be used in practical problems without the need for extensive system modelling and load flow analysis. The results confirm the importance of appropriate DG planning and show that the proposed method can be used as a promising tool for efficient and effective DG allocation in low voltage distribution network.