Fear of needles can significantly limit professional and social functioning of a person, and is highly prevalent in general population (4%).
The aim of our study was to reveal risk factors that are ...associated with fear of needles among healthy university students of medicine and pharmacy.
The study was of a cross-sectional type. In total, 301 students of medicine or pharmacy (82% female and 18% male) attending from 1st to 5th year of study were surveyed at the Faculty of Medical Sciences, University of Kragujevac, Serbia. The students were surveyed using a questionnaires (scales) for assessing the fear of needless, a visual analog scale for self-assessment intensity of the fear of needless, and a general questionnaire with questions about socio-demographic characteristics of the participants. Using a score on the scales as out-come variables, multiple regressions were employed to reveal factors that may influence the fear of needles.
Average values of Blood/Injection Fear Scale, Injection Phobia Scale-Anxiety and Medical Avoidance Survey scores were 7.89 ± 9.48, 4.46 ± 5.18 and 89.95 ± 12.73, respectively. The following factors affected significantly the score of the scales: course of study, chronic disease in the family, fear of a dentist, smell of the room phobia, sound phobia, score on the Beck’s anxiety scale and fear of a situation when medical staff give an injection. The presence of chronic disease in the family was a protective factor, while the other six factors were contributing to the fear of needles.
Fear of needles is more prevalent among the students of pharmacy than among the students of medicine. It is less frequent among students with chronic disease in their family, while fear of dentist, smell of the room phobia, sound phobia, general anxiety and fear from the situation when medical staff give an injection are all factors that predispose students of medicine or pharmacy to develop fear of needles.
Problem observed in this research is inspired by distribution of parcels in courier service where city area is divided into service zones based on the historical data of deliveries intensities and ...city structure. Each service zone is served by own vehicle of known limited capacity. Number of deliveries per zone varies between days, where average intensity is known in advance. Additionally, total number of deliveries can exceed capacity of the vehicle. All exceeded deliveries in service zones must be served by the "sweep" vehicle. Main idea of the paper is to evaluate the impact of fixed and flexible zoning strategies on total traveled distance of vehicles in the parcel distribution. In fixed zoning strategy, deliveries cannot be transferred, whereas in flexible zoning these deliveries can be transferred between zones. For the purpose of solving problems of realistic size, the authors use heuristics approach, while Mixed Integer Programming model was developed in solving the small scale problems.
This paper introduces a conceptual 100BillionTransistor (100BT) SuperComputers-on-a-Chip consisting of N big multi-core processors, 1000N small many-core processors, and two hardware accelerators - ...an ASIC TPU-like fixed-structure systolic array accelerator and a FPGA based flexible-structure re-programmable accelerator for bandwidth-bound and latency-critical Machine Learning applications respectively. The proposed SuperComputers-on-a-chip concept requires interfaces to specific external accelerators based on Quantum, Optical, Molecular, and Biological paradigms (programmable using EnergyFlow programming models - Energy Flow also representing a concept introduced in this paper) but these issues are outside the scope of this article. Keywords - Accelerators, Big Data, ControlFlow, DataFlow, ManyCore, Machine Learning, MultiCore, Systolic Array
This article starts from the assumption that near future 100BTransistor SuperComputers-on-a-Chip will include N big multi-core processors, 1000N small many-core processors, a TPU-like fixed-structure ...systolic array accelerator for the most frequently used Machine Learning algorithms needed in bandwidth-bound applications and a flexible-structure reprogrammable accelerator for less frequently used Machine Learning algorithms needed in latency-critical applications.
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