Search

Collagen membranes are routinely used in oral surgery for bone regeneration. Despite their numerous advantages, such as stimulating bone growth, bacterial contamination still remains one of the disadvantages of membrane use. Thus, we assessed the biocompatibility and osteogenic and antibacterial properties of a collagen membrane (OsteoBiol) modified with chitosan (CHI) and hydroxyapatite nanoparticles (HApNPs). Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR FT-IR), X-ray powder diffraction (XRD), and field emission scanning electron microscopy (FE-SEM) were performed for membrane characterization. Biocompatibility was assessed on dental pulp stem cells (DPSCs) by an MTT assay, while the osteogenic effect was assessed by an ALP activity assay and qPCR analysis of osteogenic markers (BMP4, ALP, RUNX2, and OCN). Antimicrobial properties were investigated by counting colony-forming units (CFUs) of Streptococcus mitis, Porphyromonas gingivalis, and Fusobaterium nucleatum on membranes and in the surrounding medium. Membranes showed no cytotoxicity. ALP activity was higher and ALP, BMP4, and OCN genes were up-regulated in DPSCs on modified membranes compared to unmodified membranes. The CFUs were reduced on modified membranes and in the medium. Modified membranes showed great biocompatibility and a high osteoinductive effect. Additionally, they showed antimicrobial and antibiofilm effects against periopathogens. It can be concluded that the incorporation of CHI and hydroxyapatite nanoparticles in collagen membranes may be advantageous to promote osteogenesis and reduce bacterial adhesion.

BackgroundWe present the disease course and long-term follow-up of two patients who were phenotypically diagnosed with atypical Leber Hereditary Optic Neuropathy (LHON) 14 and 12 years ago, respectively, whereby whole exome sequencing revealed recently described recessive DNAJC30:c.152G>A 152 A>G (p.Tyr51Cys) homozygous pathogenic variant with significant spontaneous visual acuity recovery in one.Case presentationTwo presented unrelated males with atypical LHON with sequential visual acuity (VA) loss were followed for many years. Both patients had negative family history. At the presentation at ages 17 (Case 1) and 18 years (Case 2), both had reduced visual acuity (Snellen): (Case 1) right eye (RE):CF 3m, left eye (LE):0.6, (Case 2) RE:0.2, LE:0.15; and color vision (Ishihara): (Case 1) 1/15 and 13/15; (Case 2) 2/15 and 3/15. Both had hyperemic optic disks (PNO) and central scotoma in their visual fields. Electrophysiology in the acute phase showed reduced and delayed visually evoked potentials (VEP) P100 in both patients, with reduced N95 amplitude in Case 2, and initially normal N95 amplitude in Case 1. Fluorescein angiography showed no early leakage with some late pooling at optic disks. Extensive clinical workout, including brain magnetic resonance imaging (MRI), aquaporin 4 (Aq4), and anti-myelin oligodendrocyte protein (anti-MOG) antibodies, was negative. Intravenous corticosteroids did not improve vision. Both experienced further deterioration several months after the onset accompanied by thinning of the peripapillary retinal nerve fiber layer (RNFL). Genetic testing for typical LHON pathogenic variants and whole mitochondrial DNA (mtDNA) sequencing was negative. 1 year after the onset, modest VA improvement began in Case 2 and continued over the next 3 years. VA improved bilaterally to 0.7, color vision 15/15, and islands of vision appeared within the visual field scotoma. VEP P100 peak time shortened, and amplitude increased, despite further RNFL thinning on optical coherent tomography (OCT). The patient's visual function remained stable during the entire 12-year follow-up period. Case 1 experienced modest VA improvement to 0.1 with some improvement in the visual field seven years after the disease onset, remaining stable during the entire 14-year follow-up period. VEP P100 wave remained undetectable.ConclusionsPresented are two autosomal recessive LHON (arLHON, OMIM:619382) cases with the same DNAJC30:c.152G>A pathogenic variant and different degrees of spontaneous visual recovery despite progressive RNFL thinning during a long-term follow-up. This mutation should be screened in every atypical LHON patient.

This paper deals with hub-and-spoke network design in the liner shipping sector. It introduces a capacitated directed cycle hub location and cargo routing problem under congestion. The problem involves four decisions: location of hub ports; allocation of non-hub ports to hub ports; construction of a directed cyclic route at the hub port network level; and the routing of cargo between all origin-destination demand pairs in the network. The objective is to minimize the cost which includes fixed hub opening, feeder collection and distribution, inter-hub transportation, cargo handling, and non-linear hub port congestion costs. We present a mixed integer linear programming model in which the non-linear congestion costs at the hub ports are approximated through a (semi-continuous) piecewise linear function and use this model to calculate lower bounds on the objective function. We also develop a Tabu Search algorithm, which employs a hierarchical approach for the different decisions in the hub-and-spoke network design problem, with customized procedures for the generation of the initial solution and the selection of the search moves. The neighborhood search is diversified by randomly changing the locations of hubs based on their location frequency history in previous solutions. Computational experiments, using instances from the literature and problems based on real-world data, demonstrate that the algorithm finds high quality solutions in a reasonable time. The experiments show that the network design can be highly influenced by scale economies in mainline vs. feeder transportation costs, the port locations and hinterland flows, and congestion at the hub ports.

(1) Background: The purpose of this study was to evaluate the thickness of retinal layers in Leber hereditary optic neuropathy (LHON) in the atrophic stage compared with presumably inherited bilateral optic neuropathy of unknown cause with the aim of seeing if any LHON-specific patterns exist. (2) Methods: 14 patients (24 eyes) with genetically confirmed LHON (LHON group) were compared with 13 patients (23 eyes) with negative genetic testing results (mtDNA + WES) and without identified etiology of bilateral optic atrophy (nonLHON group). Segmentation analysis of retinal layers in the macula and peripapillary RNFL (pRNFL) measurements was performed using Heidelberg Engineering Spectralis SD-OCT. (3) Results: In the LHON group, the thickness of ganglion cell complex (GCC) (retinal nerve fiber layer (RNFL)—ganglion cell layer (GCL)—inner plexiform layer (IPL)) in the central ETDRS (Early Treatment Diabetic Retinopathy Study) circle was significantly higher than in the nonLHON group (p < 0.001). In all other ETDRS fields, GCC was thinner in the LHON group. The peripapillary RNFL (pRNFL) was significantly thinner in the LHON group in the temporal superior region (p = 0.001). Longitudinal analysis of our cohort during the follow-up time showed a tendency of thickening of the RNFL, GCL, and IPL in the LHON group in the central circle, as well as a small recovery of the pRNFL in the temporal region, which corresponds to the observed central macular thickening. (4) Conclusions: In LHON, the retinal ganglion cell complex thickness (RNFL-GCL-IPL) appears to be relatively preserved in the central ETDRS circle compared to nonLHON optic neuropathies in the chronic phase. Our findings may represent novel biomarkers as well as a structural basis for possible recovery in some patients with LHON.

Benzoic acid has a wide use primarily in food but it is also used in cosmetic, pharmaceutical and other products. Because of noted carcinogenic and toxic characteristics under certain concentration it is considered a pollutant that becomes an important environmental problem. In this study, commercial activated charcoal was tested for the removal of benzoic acid from aqueous solutions. Removal of benzoic acid was investigated in a batch and column system under various values of pH, temperature, activated charcoal granulation and mass. The analysis of all samples was performed by visible absorption spectrometry. The optimum conditions for benzoic acid removal in a batch system were found to be pH 3, contact time of 60 min, the temperature of 273.65 K and adsorbent dose of 10 g L-1. The benzoic acid removal can be performed in a column system as well in which the highest quantity of benzoic acid is removed during the first 20 min (70%) and saturation occurs after 70 min. The used benzoic acid removing methods can be characterized as simple, economical and fast and requiring no chemical treatment.

The subgingival biofilm, as the most complex microbial community, has been proven to be reservoir of Candida spp. The main concept of this study was to investigate if there is a difference between the sensitivity of Candida albicans (C. albicans) isolated from tongue and subgingival areas of periodontitis patients to antifungal agents. The aim of the study was to determine: (1) the distribution of different Candida species in the tongue and subgingival samples of periodontitis patients; (2) the susceptibility of Candida albicans strains from tongue and subgingival biofilm to the effects of commonly used antifungal agents: fluconazole, amphotericin B and itraconazole; (3) the correlation between the susceptibility of Candida albicans and clinical periodontal parameters. Tongue and subgingival biofilm samples of periodontitis subjects (N = 163) were examined. Susceptibility was tested when the same Candida species was isolated from both sites (17 subjects). Candida spp. were isolated in 23.3% of tongue and 21.5% of the subgingival samples. All isolates were susceptible to amphotericin B, while 64.71% of tongue and 52.94% of subgingival isolates were susceptible to fluconazole. A low frequency of itraconazole susceptibility was observed for tongue (17.64%) and subgingival isolates (11.76%). The correlations between full-mouth plaque score and Minimal Inhibitory Concentration (MIC) for tongue isolates were strongly positive for all antimycotics. Positive correlation was also observed between moderate periodontal destruction and MICs for tongue and subgingival isolates. The susceptibility of C. albicans to antifungals correlate with oral hygiene and moderate periodontal destruction. There is no difference in antifungal susceptibility between tongue and subgingival isolates.

Dentures and epitheses are mostly made from poly(methyl methacrylate) (PMMA), which does not show antimicrobial properties. They present reservoirs of microorganisms grown in biofilms. The aim of this study is to prepare a PMMA enriched with gold nanoparticles (AuNPs)-PMMA/AuNPs and the examination of its physical, mechanical and antimicrobial properties. The AuNPS were synthetized from HAuCl4 using the ultrasonic spray pyrolysis method with lyophilization. The PMMA/AuNP samples were compared to PMMA samples. Density was measured by pycnometer. Microhardness was evaluated using the Vickers hardness test. Monomicrobial biofilm formation (Streptococcus mitis, Candida albicans, Staphylococcus aureus and Escherichia coli) was measured by colony-forming units (CFUs) and MTT test and visualized by SEM. AuNP release was measured indirectly (the CFUs of the medium around the sample). The density and microhardness of the PMMA/AuNPs were similar to those of the PMMA. CFU and MTT values for the biofilms formed on the PMMA for each of the tested species were higher than those of the biofilms formed on the PMMA/AuNPs. The CFUs of the medium around the sample were similar for both materials. PMMA/AuNPs showed a significant reduction in the monomicrobial biofilms of all tested species. AuNPs are not released from PMMA/AuNPs. Density, indirect measurement of residual monomer and dentures weight were similar between PMMA and PMMA/AuNPs. Microhardness, as a measure of the wear resistance, was also similar between tested discs.

The subgingival biofilm, as the most complex microbial community, has been proven to be reservoir of

To report the safety, anatomical and functional outcomes of autologous neurosensory retinal transplant in patients with a refractory large unclosed macular hole. This is a prospective case series of four patients with large chronic macular hole that underwent vitrectomy and free-flap neurosensory retinal transplantation surgery with silicone oil tamponade. The hole was closed with an autologous retinal transplant of an approximate diameter of 1.5–1.8 mm, harvested outside the vascular arcades. Anatomical and functional outcomes were assessed using best-corrected visual acuity (BCVA-Snellen), optical coherence tomography (OCT), OCT angiography, microperimetry (MP), and multifocal electroretinography (mfERG). There were 2 male and 2 female patients with median age of 73 (60–81) years. The median follow-up period was 17 (13–23) months. The median preoperative size of the macular hole was 1872.5 (868–2591) μm at the widest basal diameter and 828 (556–1099) μm at the minimum diameter. Surgery resulted in the anatomical closure of the macular hole in all cases. The OCT showed structural integration of the transplant and reappearance of the inner segment ellipsoid to different extents. The BCVA improved from preoperative 0.1 (6/60; + 1.0 logMAR), 0.1 (6/60; + 1.0 logMAR), 0.05 (6/120; + 1.3 logMAR), and 0.005 (6/1200; + 2.3 logMAR) to 0.2 (6/30; + 0.7 logMAR) postoperatively in cases 1, 2, and 4, and to 0.1 (6/60; + 1.0 logMAR) in case 3. MP showed retinal function in the region corresponding to the area of the transplant (circle of 1.8 mm in diameter) in all patients after the surgery (median sensitivity in that region was 4.0 dB, range 1.8–12.4 dB). Improvement was noted in the patient that had MP performed before the surgery (mean sensitivity improved from 0 to 1.8 dB). Detectable function was mostly located in the peripheral regions of the transplant. Multifocal ERG showed abnormal function of the central ring and normal function of the second ring in 3 of 4 cases. The OCT angiography showed normal perfusion, without signs of neovascularization. There were no intra- or postoperative complications. Autologous retinal transplantation surgery is a successful technique for closing of large refractory macular holes. The procedure is safe and provides good anatomical results. Visual acuity, microperimetry, and mfERG suggest some gradual functional integration of outer regions of the transplants, but no central functional restitution has been detected as yet.

The paper is an attempt to point out the problems faced by the new communist authorities in Yugoslavia in the years after the victory in the War and the Revolution in the process of emancipation and additional feminization of the teaching vocation, with particular emphasis on the period until the adoption of the General Law on Education (1958). Particular emphasis will be placed on policy analysis as well as concrete measures that have led to a different profile of the role of the teacher in the post-war society. On the one hand, it will highlight the concrete measures taken by the state to motivate as many women as possible to opt for the teaching job. On the other hand, they will point out the many problems faced by many teachers whose professional and professional qualities, in assessing the quality of their work, are not so infrequently subordinated to their “moral characteristicsˮ. Key words: teacher, socialism, Yugoslavia, Serbia, Communist Party of Yugoslavia, General Law on Education, emancipation, feminization, child, parent, patriarchy

The aims of the study were: 1) to evaluate the effect on biofilm formation of barrier membranes and titanium surfaces coated with graphene-oxide (GO); 2) to analyze the connection between the superficial topography of the tested materials and the amount of bacterial accumulation on them and 3) to analyze the biocompatibility of GO functionalized discs using the zebrafish model. Methods: Single species bacterial biofilms (Streptococcus oralis, Veilonella parvula, Fusobacterium nucleatum, Porphyomonas gingivalis) were grown on GO-free membranes, membranes coated with 2 and 10 μg/ml of GO, GO-free and GO-coated titanium discs. The biofilms were analyzed by determining the CFU count and by Scanning Electron Microscopy (SEM) and the materials’ topography by Atomic Force Microscopy (AFM). Zebrafish model was used to determine the materials’ toxicity and inflammatory effects. Results: AFM showed similar roughness of control and GO-coated materials. CFU counts on GO-coated discs were significantly lower than on control discs for all species. CFU counts of S. oralis, V. parvula and P. gingivalis were lower on biofilms grown on both types of GO-coated membranes than on GO-free membrane. SEM analysis showed different formation of single species biofilm of S. oralis on control and GO-coated materials. GO-functionalized titanium discs do not induce toxic or inflammatory effects. Significance: Titanium implant surfaces functionalized with GO have shown to be biocompatible and less susceptible to biofilm formation. These results encourage further in vivo investigation of the tested materials on infection prevention, specifically in prevention and reduction of peri-implant mucositis and periimplantitis incidence.

Precision and ultra-precision surfaces are crucial for many products – quality optics, joint & cranial implants, turbine blades, and industrial moulds & dies, to name a few. Automation in this context is distinct from standard procedures in industry, where the identical sequence of operations can be repeated over and over again. Ultraprecision tolerances may be tens to hundreds of times tighter, and this is compounded by the hundreds of diverse substrate materials in use. Even with modern computer numerically controlled (CNC) machines, skilled craftspeople are needed to plan a process-chain for a new material or geometry. Processes working at these tight tolerances, fall short of being fully-deterministic, so repeated process-metrology iterations are required. Surface-correction loops may be automated, but expert assessment should be performed at each step to check for unexpected anomalies. The ultimate goal of importing a part, processing autonomously, and delivering a finished part to an “optical” specification with no human intervention, is still a long way off. This paper describes the challenge and why it is important. It then melds together process-monitoring, psychology, artificial intelligence and robotics, to take a far-sighted view of how the ultimate goal can be realised.

Many disasters that have happened in the last decades, including the latest COVID-19 pandemic, have caused a shortage of healthcare resources and change in healthcare operations. Given these impacts, the Operational Research (OR) community has applied various approaches to improve the emergency medical responses. Coordination of healthcare facilities is one of the emergency medical response strategies to ensure the continued provision of medical services during disasters. Although the existing literature reviews of OR approaches have included the perspective of healthcare management, they focused mostly on the application of OR in disaster operations and logistics management. The importance of coordination in healthcare systems during disasters is well recognised in the literature, but to the best of our knowledge there has been no review of the published research in this area. This study provides a focused literature review of the OR contributions in the coordination in healthcare systems during disasters. Definitions of the terms in use in this field are provided. An overall descriptive statistics of the reviewed articles is given, followed by the review of the presented research problems, disaster types, and developed methodologies. The main characteristics of models for the coordination in the healthcare system are described. Measures of coordination effectiveness that denote healthcare resilience are discussed. Based on our findings, we suggest future research directions in the context of existing models extension, and application and development of other methodologies with the aim to provide a solid basis for OR research in the healthcare disaster management.

Introduction. Urrets-Zavalia syndrome (UZS) has been defined as a fixed and dilated pupil accompanied by iris atrophy and occasionally secondary glaucoma. The precise cause of the syndrome is uncertain. Most often it has been described following anterior segment surgery. The objective of this article is to present how to successfully handle patients with UZS after posterior segment surgery. We present all the dilemmas and difficulties we encountered during the diagnostic process. Case outline. This is a case presentation of a patient with UZS following scleral buckle procedure. To our knowledge, this is the first case of UZS following this type of posterior segment surgery. The delay in treatment was mostly due to the lack of knowledge about the linkage of this syndrome with posterior segment surgery. Once the diagnosis was confirmed, parasympathomimetic drops were administered. The patient responded well to the therapy and partial reduction of mydriasis and restoration of pupillary kinetics was observed. Conclusion. Two months after surgery, the treatment of UZS resulted in slight residual anisocoria with signs of iris atrophy. This could indicate reversible mechanism of UZS after posterior segment surgery with iris atrophy as the only permanent consequence.

Four patients with traumatic mydriasis and aphakia following blunt injury of the eye globe were evaluated. Patients with severe glare and photophobia due to wide pupil diameter from 6.0 to 9.0 mm were managed by combined iris cerclage pupilloplasty and retropupillar iris-claw lens implantation. The postoperative anatomic results, visual acuity, subjective degree of glare, photophobia, as well as intraoperative and postoperative complications were evaluated. The mean follow-up time was 32.6 months. Best-corrected visual acuity improved in all patients from preoperative 20/60, 20/30, 20/25, 20/22 to postoperative 20/20, 20/22, 20/20, and 20/20 (Snellen charts). All eyes achieved satisfactory anatomic result with round pupil diameter 3.5–4.5 mm. Glare and photophobia disappeared in all patients. There were no intraoperative or postoperative complications. During the follow-up period, pupils remained round and iris-claw lenses well positioned, without tilting. Combined iris cerclage pupilloplasty with retropupillar iris claw lens implantation appears to be a safe and effective surgical technique in reducing pupil size and improving visual outcomes. It is also a cost- and time-effective procedure, providing great results with a single surgery.

Personnel scheduling problems have attracted research interests for several decades. They have been considerably changed over time, accommodating a variety of constraints related to legal and organisation requirements, part-time staff, flexible hours of staff, staff preferences, etc. This led to a myriad of approaches developed for solving personnel scheduling problems including optimisation, meta-heuristics, artificial intelligence, decision-support, and also hybrids of these approaches. However, this still does not imply that this research has a large impact on practice and that state-of-the art models and algorithms are widely in use in organisations. One can find a reasonably large number of software packages that aim to assist in personnel scheduling. A classification of this software based on its purpose will be proposed, accompanied with a discussion about the level of support that this software offers to schedulers. A general conclusion is that the available software, with some exceptions, does not benefit from the wealth of developed models and methods. The remaining of the paper will provide insights into some characteristics of real-world scheduling problems that, in the author’s opinion, have not been given a due attention in the personnel scheduling research community yet and which could contribute to the enhancement of the implementation of research results in practice. Concluding remarks are that in order to bridge the gap that still exists between research into personnel scheduling and practice, we need to engage more with schedulers in practice and also with software developers; one may say we need to get wet if we want to learn how to swim.

Increasing energy price and requirements to reduce emission are new chal-lenges faced by manufacturing enterprises. A considerable amount of energy is wasted by machines due to their underutilisation. Consequently, energy saving can be achieved by turning off the machines when they lay idle for a comparatively long period. Otherwise, turning the machine off and back on will consume more energy than leave it stay idle. Thus, an effective way to reduce energy consumption at the system level is by employing intelligent scheduling techniques which are capable of integrating fragmented short idle periods on the machines into large ones. Such scheduling will create opportunities for switching off underutilised resources while at the same time maintaining the production performance. This paper introduces a model for the bi-objective optimisation problem that minimises the total non-processing electricity consumption and total weighted tardiness in a job shop. The Turn off/Turn on is applied as one of the electricity saving approaches. A novel multi-objective genetic algorithm based on NSGA-II is developed. Two new steps are introduced for the purpose of expanding the solution pool and then selecting the elite solutions. The research presented in this paper is focused on the classical job shop envi-ronment, which is widely used in the manufacturing industry and provides considerable opportunities for energy saving. The algorithm is validated on job shop problem instances to show its effectiveness. Keywords: Energy efficient production planning

Buildings consume a significant amount of energy today and are expected to consume even more in the future. This consumption necessitates the use of fossil fuels such as coal and natural gas, both of which have significant environmental impacts. While renewable energy sources remain promising, the most of the energy supply will still use conventional fuels in the near term. Therefore, improving the energy efficiency in buildings is critical, and one of the central visions of “smart buildings” is to reduce their energy use while maintaining the same level of service and comfort. However, to make the buildings meaningfully “smart”, their envelopes must first be made compliant with the current energy efficiency standards. In this paper we first examine how the public awareness of energy efficiency was risen in Serbia through different demonstration projects, funded by the state budget and through implementation of the energy efficiency measures in public buildings, funded by municipal funds and soft loans from the banks. Then, we describe how the energy efficiency in buildings might further be increased by the use of new technologies and smart networks for control of the energy consumption. We finally argue that these controls should take into account the personal variables (activity, clothing) along with environmental variables (air temperature, velocity, and humidity) for an optimum thermal comfort to be achieved in public and residential buildings.

The paper describes the determination of Ag, Al, B, Ba, Bi, Ca, Cd, Co, Cr, Cu, Fe, Ga, In, K, Li, Mg, Mn, Na, Ni, Pb, Sr, Tl and Zn, as well as total fat content of milk samples, originated from different sources. The analyzed milk samples were: human milk, fresh cow milk, pasteurized cow milk from a local market, and reconstituted powder milk. The milk samples were obtained from Jablanica District (Serbia) territory. Preparation of samples for macro- and micro-analyses was done by wet digestion. Concentrations of the elements after digestion were determined by inductively coupled plasma optical emission spectrometry (ICP-OES). Total fat content of milk samples was determinate by the Weibull and Stoldt method. The results showed that potassium and calcium concentrations were the highest in all samples: 1840.64 - 2993.26 mg/L and 456.05 - 1318.08 mg/L, respectively. Of all heavy metals from the examined milk samples (copper, zinc, manganese, nickel, cadmium, and lead), the most common were zinc and copper, with approximately similar content in the range of 5 - 12 mg/l, while cadmium nickel and manganese were not detected at all. Samples of fresh cow milk and human milk showed the highest fat content of 3.6 and 4.2 %, respectively. Results for total fat and macro- and micro-analyses showed that fresh cow milk has the highest contents of fat and calcium, making it the most nutritious. [Projekat Ministarstva nauke Republike Srbije, br. TR 34012]

Introduction. Primary acquired iris stromal cyst is rare in adults. In this group, they are generally stable lesions which require no treatment. Case outline. We describe a rare case of a small primary iris cyst in a 39-year-old patient, associated with unusual signs of irritation. Ultrasound biomicroscopy demonstrated iris stromal cyst measuring 3 ? 2 mm. A neodymium-doped yttrium aluminium garnet (Nd:YAG) laser cystotomy was engaged as the least invasive treatment approach. However, the cyst recurred soon after repeated laser treatment and sector iridectomy with excision of the cyst was performed. Five years after surgery there was no evidence of recurrence. Conclusion. Although more benign clinical course of primary stromal iris cyst is generally assumed in adults as compared to children, complete cyst removal seems to be mandatory for preventing cyst recurrence regardless of the cyst size or patient age. To the authors? knowledge this is the first documented report of Nd:YAG laser photodisruption of acquired primary iris stromal cyst in an adult.

Detection and quantification of Candida spp. from subgingival areas using two methods- sterile periodontal curette and sterile paper points.

[Context] Models play an important role in Software and Systems Engineering processes. Reviews are well-established methods for model quality assurance that support early and efficient defect detection. However, traditional document-based review processes have limitations with respect to the number of experts, resources, and the document size that can be applied. [Objective] In this paper, we introduce a distributed and scalable review process for model quality assurance to (a) improve defect detection effectiveness and (b) to increase review artifact coverage. [Method] We introduce the novel concept of Expected Model Elements (EMEs) as a key concept for defect detection. EMEs can be used to drive the review process. We adapt a best-practice review process to distinguish (a) between the identification of EMEs in the reference document and (b) the use of EMEs to detect defects in the model. We design and evaluate the adapted review process with a crowdsourcing tool in a feasibility study. [Results] The study results show the feasibility of the adapted review process. Further, the study showed that inspectors using the adapted review process achieved results for defect detection effectiveness, which are comparable to the performance of inspectors using a traditional inspection process, and better defect detection efficiency. Moreover, from a practical perspective the adapted review process can be used to complement inspection efforts conducted using the traditional inspection process, enhancing the overall defect detection effectiveness. [Conclusions] Although the study shows promising results of the novel process, future investigations should consider larger and more diverse review artifacts and the effect of using limited and different scopes of artifact coverage for individual inspectors.

Many manufacturing companies in China currently are suffering from a Rolling Blackout policy for the industry electricity supply which means that the government electricity is cut off several days in every week resulting in manufacturing companies illegally starting their own diesel generators to maintain production. However, the private generation of electricity is more polluting and costly than the government supplied resource. Thus, the increased price of energy and the requirement to become more environmentally sustainable exert substantial pressures on manufacturing enterprises to reduce energy consumption for cost saving and to become more environmentally friendly. Scheduling of less energy consumption critical operations during Rolling Blackout periods can help minimise the negative effect of this policy. This is a multi-objective optimisation problem as production due dates cannot be ignored and cost is not directly proportional to electricity consumption anymore. Optimal scheduling even of relatively small production orders is clearly beyond the capability of manual tools or common single objective scheduling optimisation methods. Therefore, a multi-objective scheduling optimisation method has been developed which includes reducing electricity consumption and its related cost as part of the objectives in addition to total weighted tardiness. This research focuses on classical job shop environments which are widely used in the manufacturing industry in China and the rest of the world. A mathematical model for the tri-objectives problem that minimises total electricity cost, total electricity consumption and total weighted tardiness has been developed. A specific heuristic has been devised for investigating how the Rolling Blackout policy affects the performance of existing scheduling plans. This heuristic can also be used as a remedial measurement by plant managers if they do not have access to multi-objective optimisation tools. The Non-dominant Sorting Genetic Algorithm has been used as the basis for solving the optimisation problem. Case studies based on four modified job shop instances have been studied to show the effectiveness of the proposed heuristic and the algorithm.

Fruit juice is the product obtained by mechanical processing of one or more types of technologically ripe, fresh, chilled or frozen fruit, which is not but can be fermented, the taste, color and aroma of which must be specific to the type of fruit from which the fruit juice is produced. Fruit juices are important in the human diet since they contain different nutrients, especially vitamins, minerals and carbohydrates. In this paper the content of Ag, Al, B, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Pb, Sr, Zn, Si, As, P, Mo and Sb in clear orange juices found the local market on the territory of Leskovac was investigated. The preparation of the samples was done by wet digestion. The concentrations of elements after digestion were determined by Inductively Coupled Plasma - Optical Emission Spectrometry (ICP-OES). Based on the obtained results it can be concluded that all investigated samples of clear orange juices do not have the required level of potassium and phosphorus. On the other side, due to high levels of molybdenum and arsenic, the consumption of clear orange juices in higher amounts could lead to a greater intake of these elements and potentially unwanted adverse effects.

Pellet stoves may play an important role in Serbia in the future when fossil fuel fired conventional heating appliances are replaced by more efficient and environmentally friendly devices. Experimental investigation was conducted in order to examine the influence of wood pellet quality, as well as burner capacity (6, 8 and 10 kW), used in the same stove configuration, on the performance of pellet stove with declared nameplate capacity of 8 kW. The results obtained showed that in case of nominal load and combustion of pellets recommended by the stove manufacturer, stove efficiency of 80.03% was achieved. The use of lower quality pellet caused additional 1.13 kW reduction in heat output in case of nominal load and 0.63 kW in case of reduced load. This was attributed to less favourable properties and lower bulk and particle density of lower quality pellet. The use of different burner capacity has shown to have little effect on heat output and efficiency of the stove when pre-set values in the control system of the stove were not altered. It is concluded that replacement of the burner only is not sufficient to increase/decrease the declared capacity of the same stove configuration, meaning that additional measures are necessary. These measures include a new set up of the stove control system, which needs to be properly adjusted for each alteration in stove configuration. Without the adjustment mentioned, declared capacity of the stove cannot be altered, while its CO emission shall be considerably increased.

Context. Expert sourcing is a novel approach to support quality assurance: it relies on methods and tooling from crowdsourcing research to split model quality assurance tasks and parallelize task execution across several expert users. Typical quality assurance tasks focus on checking an inspection object, e.g., a model, towards a reference document, e.g., a requirements specification, that is considered to be correct. For example, given a text-based system description and a corresponding model such as an Extended Entity Relationship (EER) diagram, experts are guided towards inspecting the model based on so-called expected model elements (EMEs). EMEs are entities, attributes and relations that appear in text and are reflected by the corresponding model. In common inspection tasks, EMEs are not explicitly expressed but implicitly available via textual descriptions. Thus, a main improvement is to make EMEs explicit by using crowdsourcing mechanisms to drive model quality assurance among experts. Objective and Method. In this paper, we investigate the effectiveness of identifying the EMEs through expert sourcing. To that end, we perform a feasibility study in which we compare EMEs identified through expert sourcing with EMEs provided by a task owner who has a deep knowledge of the entire system specification text. Conclusions. Results of the data analysis show that the effectiveness of the crowdsourcing-style EME acquisition is influenced by the complexity of these EMEs: entity EMEs can be harvested with high recall and precision, but the lexical and semantic variations of attribute EMEs hamper their automatic aggregation and reaching consensus (these EMEs are harvested with high precisions but limited recall). Based on these lessons learned we propose a new task design for expert sourcing EMEs.

In the context of Industrie 4.0, we have previously described the roles of robots in optical processing, and their complementarity with classical CNC machines, providing both processing and automation functions. After having demonstrated robotic moving of parts between a CNC polisher and metrology station, and auto-fringe-acquisition, we have moved on to automate the wash-down operation. This is part of a wider strategy we describe in this paper, leading towards automating the decision-making operations required before and throughout an optical manufacturing cycle.

Traditional Software Inspection is a well-established approach to identify defects in software artifacts and models early and efficiently. However, insufficient method and tool support hinder efficient defect detection in large software models. Recent Human Computation and Crowdsourcing processes may help to overcome this limitation by splitting complex inspection artifacts into smaller parts including a better control over defect detection tasks and increasing the scalability of inspection tasks. Therefore, we introduce a Crowdsourcing-Based Inspection (CSI) process with tool support with focus on inspection teams and the quality of defect detection. We evaluate the CSI process in a feasibility study involving 63 inspectors using the CSI process and 12 inspectors using a traditional best-practice inspection process. The CSI process was found useful by the participants. Although the preliminary results of the study were promising, the CSI process should be further investigated with typical large software engineering models.

Recent advances in the column technology have led to the development of small particles as stationary phase carriers in reversed-phase liquid chromatography for separation of large scale of molecules. This work represents an application of UHPLC (ultrahigh performance liquid chromatography with 1.9 μm C-18 particles) coupled with ESI-MS (electro spray ionization-mass spectrometry) and DAD (diode array) analysis for the identification of the mixture of porphyrins such as hemato­porphyrin and protoporphyrin derivatives, widely known photosensitizers used in medicine. Five porphyrin derivatives were separated and identified in the hemato­porphyrin mixture: hematoporphyrin IX, protoporphyrin IX, two hydroxyethyl-vinyl-derivatives and methyl-ester of protoporphyrin IX.

The application of best-practice software inspection processes for early defect detection requires considerable human effort. Crowdsourcing approaches can support inspection activities (a) by distributing inspection effort among a group of human experts and (b) by increasing inspection control. Thus, the application of crowdsourcing techniques aims at making inspection processes more effective and efficient. In this paper, we present a crowdsourcing-supported model inspection (CSI) process and investigate its defect detection effectiveness and efficiency when inspecting an Extended Entity Relationship (EER) model. The CSI process uses so-called Expected Model Elements (EMEs) to guide CSI inspectors during defect detection. We conducted a controlled experiment on defect detection effectiveness, efficiency, and false positives. While CSI effectiveness and efficiency is lower for CSI inspectors, the number of false positives decreases. However, CSI was found promising for increasing the control of defect detection and supports the inspection of large-scale engineering models.

The aim of this work was to give more accurate insight in the interaction of major photosynthesis pigment, chlorophyll (Chl), with copper (II) and zinc (II) in solution by flow injection analysis with electrospray ionization mass spectrometry (FIA-ESI-MS) method, as well as combined with ultra high performance liquid chromatography with DAD detection (UHPLC-DAD). These interactions may potentially, but not necessarily lead to formation of Cu-Chl and Zn-Chl complexes of two different types, which has a lot of - at least - disfunctional implications in plant world. The results based on analysis of full-scan and MS/MS spectra - with or without the UHPLC chromatograms - confirm formation of “central type” Cu-Chl complex, and “central type” Zn-Chl complex as well, along with a proof for formation of “peripheral” Zn-Chl complex, the latter one originating from a very week coordinative interaction at the edge of Chl structure. The used techniques appeared to be an efficient and reliable tool for studying formation and stability of heavy metals complexes with chlorophyll, at least in vitro, with a considerable possibility for assessment of real bio-environmental behavior. [Projekat Ministarstva nauke Republike Srbije, br. TR-34012 i br. OI-172044]

This paper proposes a hyper-heuristic that combines genetic algorithm with mixture experiments to solve multi-objective optimisation problems. At every iteration, the proposed algorithm combines the selection criterion (rank indicator) of a number of well-established evolutionary algorithms including NSGA-II, SPEA2 and two versions of IBEA. Each indicator is called according to an associated probability calculated and updated during the search by means of mixture experiments. Mixture experiments are a particular type of experimental design suitable for the calibration of parameters that represent probabilities. Their main output is an explanatory model of algorithm performance as a function of its parameters. By finding the maximum (probability distribution) of the surface represented by this model, we also find a good algorithm parameterisation. The design of mixture experiments approach allowed the authors to identify and exploit synergies between the different rank indicators at the different stages of the search. This is demonstrated by our experimental results in which the proposed algorithm compared favourably against other well-established algorithms.

In this paper, we propose a novel bee colony optimization approach to the nurse rostering problem. The bee colony optimization algorithm is motivated by the foraging habits of honey bees. In iterations, artificial bees collectively improve their solutions. The developed algorithm alternates constructive and local search phases. In the constructive phase, unscheduled shifts are assigned to available nurses, while the aim of local search phase is to improve the quality of the solution. The algorithm incorporates a novel intelligent discarding of portions of large neighborhoods for which it is predicted that they will not lead to the improvement of the objective function. Performance of the algorithm was evaluated on real-world data from hospitals in Belgium. The results show that the bee colony optimization is able to efficiently find solutions that are competitive compared to the solutions produced by other algorithms reported in the literature.

HighlightsThis paper is concerned with a case-based reasoning (CBR) system for radiotherapy treatment planning for brain cancer patients, which has been developed in collaboration with medical physicists at the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK.The developed CBR system generates the parameters of a treatment plan by capturing the subjective and intuitive knowledge of medical physicists.In this research we focus on the adaptation stage of the CBR system in which the solution (treatment plan) of the retrieved case is adapted to meet the needs of the new case (patient) by considering differences between the retrieved and new cases.We investigate approaches to adaptation that do not require much domain knowledge, referred to as knowledge-light adaptation.Results obtained by three developed adaptation approaches including adaptation based on Neural Networks and naive Bayes classifier, and adaptation-guided retrieval are presented. ObjectiveRadiotherapy treatment planning aims at delivering a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour-surrounding area. It is a time-consuming trial-and-error process that requires the expertise of a group of medical experts including oncologists and medical physicists and can take from 2 to 3h to a few days. Our objective is to improve the performance of our previously built case-based reasoning (CBR) system for brain tumour radiotherapy treatment planning. In this system, a treatment plan for a new patient is retrieved from a case base containing patient cases treated in the past and their treatment plans. However, this system does not perform any adaptation, which is needed to account for any difference between the new and retrieved cases. Generally, the adaptation phase is considered to be intrinsically knowledge-intensive and domain-dependent. Therefore, an adaptation often requires a large amount of domain-specific knowledge, which can be difficult to acquire and often is not readily available. In this study, we investigate approaches to adaptation that do not require much domain knowledge, referred to as knowledge-light adaptation. MethodologyWe developed two adaptation approaches: adaptation based on machine-learning tools and adaptation-guided retrieval. They were used to adapt the beam number and beam angles suggested in the retrieved case. Two machine-learning tools, neural networks and naive Bayes classifier, were used in the adaptation to learn how the difference in attribute values between the retrieved and new cases affects the output of these two cases. The adaptation-guided retrieval takes into consideration not only the similarity between the new and retrieved cases, but also how to adapt the retrieved case. ResultsThe research was carried out in collaboration with medical physicists at the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. All experiments were performed using real-world brain cancer patient cases treated with three-dimensional (3D)-conformal radiotherapy. Neural networks-based adaptation improved the success rate of the CBR system with no adaptation by 12%. However, naive Bayes classifier did not improve the current retrieval results as it did not consider the interplay among attributes. The adaptation-guided retrieval of the case for beam number improved the success rate of the CBR system by 29%. However, it did not demonstrate good performance for the beam angle adaptation. Its success rate was 29% versus 39% when no adaptation was performed. ConclusionsThe obtained empirical results demonstrate that the proposed adaptation methods improve the performance of the existing CBR system in recommending the number of beams to use. However, we also conclude that to be effective, the proposed adaptation of beam angles requires a large number of relevant cases in the case base.

A genetic algorithm heuristic that uses multiple rank indicators taken from a number of well established evolutionary algorithms including NSGA-II, IBEA and SPEA2 is developed. It is named Multi-Indicator GA (MIGA). At every iteration, MIGA uses one among the available indicators to select the individuals which will participate as parents in the next iteration. MIGA chooses the indicators according to predefined probabilities found through the analysis of mixture experiments. Mixture experiments are a particular type of experimental design suitable for the calibration of parameters that represent probabilities. Their main output is an explanatory model of algorithm performance as a function of its parameters. By finding the point that provides the maximum we also find good algorithm parameters. To the best of our knowledge, this is the first paper where mixture experiments are used for heuristic tuning. The design of mixture experiments approach allowed the authors to identify and exploit synergy between the different rank indicators. This is demonstrated by our experimental results in which the tuned MIGA compares favorably to other well established algorithms, an uncalibrated multi-indicator algorithm, and a multi-indicator algorithm calibrated using a more conventional approach.

We present a hybrid approach of goal programming and meta-heuristic search to find compromise solutions for a difficult employee scheduling problem, i.e. nurse rostering with many hard and soft constraints. By employing a goal programming model with different parameter settings in its objective function, we can easily obtain a coarse solution where only the system constraints (i.e. hard constraints) are satisfied and an ideal objective-value vector where each single goal (i.e. each soft constraint) reaches its optimal value. The coarse solution is generally unusable in practise, but it can act as an initial point for the subsequent meta-heuristic search to speed up the convergence. Also, the ideal objective-value vector is, of course, usually unachievable, but it can help a multi-criteria search method (i.e. compromise programming) to evaluate the fitness of obtained solutions more efficiently. By incorporating three distance metrics with changing weight vectors, we propose a new time-predefined meta-heuristic approach, which we call the falling tide algorithm, and apply it under a multi-objective framework to find various compromise solutions. By this approach, not only can we achieve a trade off between the computational time and the solution quality, but also we can achieve a trade off between the conflicting objectives to enable better decision-making.

Scheduling plays a vital role in ensuring the effectiveness of the production control of a flexible manufacturing system (FMS). The scheduling problem in FMS is considered to be dynamic in its nature as new orders may arrive every day. The new orders need to be integrated with the existing production schedule immediately without disturbing the performance and the stability of existing schedule. Most FMS scheduling methods reported in the literature address the static FMS scheduling problems. In this paper, rescheduling methods based on genetic algorithms are described to address arrivals of new orders. This study proposes genetic algorithms for match-up rescheduling with non-reshuffle and reshuffle strategies which accommodate new orders by manipulating the available idle times on machines and by resequencing operations, respectively. The basic idea of the match-up approach is to modify only a part of the initial schedule and to develop genetic algorithms (GAs) to generate a solution within the rescheduling horizon in such a way that both the stability and performance of the shop floor are kept. The proposed non-reshuffle and reshuffle strategies have been evaluated and the results have been compared with the total-rescheduling method.

Purpose: Prostate cancer is the most common cancer in the male population. Radiotherapy is often used in the treatment for prostate cancer. In radiotherapytreatment, the oncologist makes a trade-off between the risk and benefit of the radiation, i.e., the task is to deliver a high dose to the prostate cancer cells and minimize side effects of the treatment. The aim of our research is to develop a software system that will assist the oncologist in planning new treatments. Methods: A nonlinear case-based reasoning system is developed to capture the expertise and experience of oncologists in treating previous patients. Importance (weights) of different clinical parameters in the dose planning is determined by the oncologist based on their past experience, and is highly subjective. The weights are usually fixed in the system. In this research, the weights are updated automatically each time after generating a treatment plan for a new patient using a group based simulated annealing approach. Results: The developed approach is analyzed on the real data set collected from the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. Extensive experiments show that the dose plan suggested by the proposed method is coherent with the dose plan prescribed by an experienced oncologist or even better. Conclusions: The developed case-based reasoning system enables the use of knowledge and experience gained by the oncologist in treating new patients. This system may play a vital role to assist the oncologist in making a better decision in less computational time; it utilizes the success rate of the previously treated patients and it can also be used in teaching and training processes.

Radiotherapy planning is a complex problem which requires both expertise and experience of an oncologist. A case based reasoning (CBR) system is developed to generate dose plans for prostate cancer patients. The proposed approach captures the expertise and experience of oncologists in treating previous patients and recommends a dose in phase I and phase II of the treatment of a new patient considering also the success rate of the treatment. The proposed CBR system employs a modified Dempster-Shafer theory to fuse dose plans suggested by the most similar cases retrieved from the case base. In order to mimic the continuous learning characteristic of oncologists, the weights corresponding to each feature used in the retrieval process are updated automatically each time after generating a treatment plan for a new patient. The efficiency of the proposed methodology has been validated using real data sets collected from the Nottingham University Hospitals NHS, City Hospital Campus, UK. Experiments demonstrated that for most of the patients, the dose plan generated by our approach is coherent with the dose plan suggested by an experienced oncologist. This methodology can assist both new and experienced oncologists in the treatment planning.

This article considers the problem of inserting arriving jobs into an existing schedule of a real world manufacturer. A number of match-up strategies, which collect the idle time on machines of a current schedule for the insertion of new jobs, are proposed. Their aim is to obtain new schedules with a good performance which are at the same time highly stable, meaning that they resemble as closely as possible the initial schedule. Basic rescheduling strategies such as ‘total rescheduling’, ‘right shift’ and ‘insertion in the end’ deliver either good performance or stability, but not both. Contrarily, our experimentation and statistical analysis reveal that the proposed match-up strategies deliver high performing schedules with a high stability. An analysis of the problem parameters that determine the behaviour of the proposed match-up algorithms is included in this article.

Research highlights? We developed and implemented three genetic algorithms (GAs) for scheduling radiotherapy treatments for different patient categories: (1) Standard-GA, which considers all patient categories equally, (2) KB-GA, which has an embedded knowledge on the scheduling of emergency patient category and (3) Weighted-GA, which operates with different weights given to the patient categories. Performances of generated schedules were compared using real life data and statistical analysis. KB-GA generated the schedules with best performance considering emergency patients and KB-GA and Weighted-GA generated better performance schedules for emergency and palliative patients simultaneously than Standard-GA. This paper presents a multi-objective optimisation model and algorithms for scheduling of radiotherapy treatments for categorised cancer patients. The model is developed considering real life radiotherapy treatment processes at Arden Cancer Centre, in the UK. The scheduling model considers various real life constraints, such as doctors' rota, machine availability, patient's category, waiting time targets (i.e., the time when a patient should receive the first treatment fraction), and so on. Two objectives are defined: minimisation of the Average patient's waiting time and minimisation of Average length of breaches of waiting time targets. Three genetic algorithms (GAs) are developed and implemented which treat radiotherapy patient categories, namely emergency, palliative and radical patients in different ways: (1) Standard-GA, which considers all patient categories equally, (2) KB-GA, which has an embedded knowledge on the scheduling of emergency patient category and (3) Weighted-GA, which operates with different weights given to the patient categories. The performance of schedules generated by using the three GAs is compared using the statistical analyses. The results show that KB-GA generated the schedules with best performance considering emergency patients and slightly outperforms the other two GAs when all patient categories are considered simultaneously. KB-GA and Weighted-GA generated better performance schedules for emergency and palliative patients than Standard-GA.

Demand for radiotherapy treatment services has increased due to higher cancer incidence, ageing population, and a larger number of prescribed radiotherapy fractions. This higher demand can, in turn, produce longer waiting times for radiotherapy treatment. We introduce a real-world radiotherapy pre-treatment scheduling problem at a hospital in the UK. This scheduling problem is modelled as an optimisation problem with multiple objectives. The objectives are hierarchical, thus the solution approach is based on solving a series of single-objective optimisation scheduling problems. Each of these problems is formulated as a mathematical programming model. Dispatching rules were introduced to produce an initial solution for the mathematical programming model. Their performance is compared to the mathematical programming approach.