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2021 ◽  
Vol 9 (6) ◽  
pp. 1597-1598
R. Bauersachs ◽  
H.E. Gerlach ◽  
A. Heinken ◽  
U. Hoffmann ◽  
F. Langer ◽  

2021 ◽  
Vol 30 (4) ◽  
pp. 255-261
Rezzan Eren Sadioglu ◽  
Mert Karaoglan ◽  
Merve Aktar ◽  
Sayeste Akkan Eren ◽  

GeroScience ◽  
2021 ◽  
Nóra Balázs ◽  
Dániel Bereczki ◽  
András Ajtay ◽  
Ferenc Oberfrank ◽  
Tibor Kovács

Abstract Dementia is one of the leading causes of death and disability in older population. Previous reports have shown that antidementia medications are associated with longer survival; nonetheless, the prevalence of their use and the compliance with them are quite different worldwide. There is hardly any available information about the pharmacoepidemiology of these drugs in the Eastern-European region; we aimed to analyze the use of cholinesterase inhibitors (ChEis) for the treatment of dementia to provide real-life information from the Eastern European region. All medical and medication prescription reports of the in- and outpatient specialist services collected in the NEUROHUN database in Hungary were analyzed between 2013 and 2016. Survival, adherence, and persistence values were calculated. 8803 patients were treated with ChEis during the study period, which was only 14.5% of the diagnosed demented patients. The survival of treated patients (more than 4 years) was significantly longer than patients without ChEi treatment (2.50 years). The best compliance was observed with rivastigmine patch. Choosing the appropriate medication as soon as possible after the dementia diagnosis may lead to increased life expectancy.

2021 ◽  
Vol 11 (20) ◽  
pp. 9551
Ali Louati ◽  
Rahma Lahyani ◽  
Abdulaziz Aldaej ◽  
Racem Mellouli ◽  
Muneer Nusir

This paper presents multiple readings to solve a vehicle routing problem with pickup and delivery (VRPPD) based on a real-life case study. Compared to theoretical problems, real-life ones are more difficult to address due to their richness and complexity. To handle multiple points of view in modeling our problem, we developed three different Mixed Integer Linear Programming (MILP) models, where each model covers particular constraints. The suggested models are designed for a mega poultry company in Tunisia, called CHAHIA. Our mission was to develop a prototype for CHAHIA that helps decision-makers find the best path for simultaneously delivering the company’s products and collecting the empty boxes. Based on data provided by CHAHIA, we conducted computational experiments, which have shown interesting and promising results.

Qiaokang Liang ◽  
Qiao Ge ◽  
Wei Sun ◽  
Dan Zhang ◽  

In the food and beverage industry, the existing recognition of code characters on the surface of complex packaging usually suffers from low accuracy and low speed. This work presents an efficient and accurate inkjet code recognition system based on the combination of the deep learning and traditional image processing methods. The proposed system mainly consists of three sequential modules, i.e., the characters region extraction by modified YOLOv3-tiny network, the character processing by the traditional image processing methods such as binarization and the modified character projection segmentation, and the character recognition by a Convolutional recurrent neural network (CRNN) model based on a modified version of MobileNetV3. In this system, only a small amount of tag data has been made and an effective character data generator is designed to randomly generate different experimental data for the CRNN model training. To the best of our knowledge, this report for the first time describes that deep learning has been applied to the recognition of codes on complex background for the real-life industrial application. Experimental results have been provided to verify the accuracy and effectiveness of the proposed model, demonstrating a recognition accuracy of 0.986 and a processing speed of 100 ms per bottle in the end-to-end character recognition system.

2021 ◽  
Vol 14 (4) ◽  
pp. 733
Nessren Zamzam ◽  
Ahmed Elakkad

Purpose: Time and Space assembly line balancing problem (TSALBP) is the problem of balancing the line taking the area required by the task and to store the tools into consideration. This area is important to be considered to minimize unplanned traveling distance by the workers and consequently unplanned time waste. Although TSALBP is a realistic problem that express the real-life situation, and it became more practical to consider multi-manned assembly line to get better space utilization, few literatures addressed the problem of time and space in simple assembly line and only one in multi-manned assembly line. In this paper the problem of balancing bi-objective time and space multi-manned assembly line is proposedDesign/methodology/approach: Hybrid genetic algorithm under time and space constraints besides assembly line conventional constraints is used to model this problem. The initial population is generated based on conventional assembly line heuristic added to random generations. The objective of this model is to minimize number of workers and number of stations.Findings: The results showed the effectiveness of the proposed model in solving multi-manned time and space assembly line problem. The proposed method gets better results in solving real-life Nissan problem compared to the literature. It is also found that there is a relationship between the variability of task time, maximum task time and cycle time on the solution of the problem. In some problem features it is more appropriate to solve the problem as simple assembly line than multi-manned assembly line.Originality/value: It is the first article to solve the problem of balancing multi-manned assembly line under time and area constraint using genetic algorithm. A relationship between the problem features and the solution is found according to it, the solution method (one sided or multi-manned) is defined.

İlhan KESER ◽  

Although the term “disaster” includes natural events like earthquake, flood and drought, it also covers; the wars, intense migration waves, industrial accidents and even epidemic diseases. In recent years, the number and severity of both natural and man-made disasters has been increasing. In this context Gaziantep –the border city of Turkey to Syria- is facing many logistical problems because of the crisis in the region that has a broad repercussion in press. In addition, the corona virus pandemic increased the supply traffic in the region. The region is in need for many emergency warehouses to store the emergency supplies and send to the needy. Thus, a three step hybrid solution method is developed to solve this real life problem. The first stage is the determination of selection criteria; secondly the spatial database is created by using a Geographical Information System (GIS). Then, Analytic Hierarchy Process (AHP) technique is applied to assign the importance levels to the selection criteria to generate the suitability map to choose the most appropriate emergency warehouse site selection in Gaziantep. Additionally, scenario analyses are conducted to understand the effects of importance levels on the problem results. As a result, 1.3% of the study area is determined as “quite suitable” for establishing an emergency warehouse.

Tonya M. Evans

The “Downtrodden Artist Stands Up to Big Bad Music Mogul” trope makes for a heartwarming plot line in movies and television, but how often does the artist prevail in real life? The music industry is plagued by issues with content management, rights management, and royalty distribution, yet legislative efforts such as the Music Modernization Act of 2018 fail to provide meaningful solutions because they continue to uphold the power structure in which the Big Bad intermediary thrives. As an alternative, this chapter argues for the disintermediation of the music industry, and consequent empowerment of the individual content creator, through the use of blockchain technology. It discusses the ways in which smart contracts, blockchain ledgers, and a global copyright database could help to support more efficient and secure payments to artists, track usage and sales data, and protect copyrights, all without the need for traditional intermediary roles. In effect, this chapter provides a technical yet comprehensive explanation of the ways in which—as well as the policy implications of—implementing decentralized blockchain technology can help maximize the value of music for creators, improve the music experience for consumers, and reduce friction, waste, and fraud in the music industry.

2021 ◽  
Vol 118 (42) ◽  
pp. e2108507118
Kinneret Teodorescu ◽  
Ori Plonsky ◽  
Shahar Ayal ◽  
Rachel Barkan

External enforcement policies aimed to reduce violations differ on two key components: the probability of inspection and the severity of the punishment. Different lines of research offer different insights regarding the relative importance of each component. In four studies, students and Prolific crowdsourcing participants (Ntotal = 816) repeatedly faced temptations to commit violations under two enforcement policies. Controlling for expected value, we found that a policy combining a high probability of inspection with a low severity of fines (HILS) was more effective than an economically equivalent policy that combined a low probability of inspection with a high severity of fines (LIHS). The advantage of prioritizing inspection frequency over punishment severity (HILS over LIHS) was greater for participants who, in the absence of enforcement, started out with a higher violation rate. Consistent with studies of decisions from experience, frequent enforcement with small fines was more effective than rare severe fines even when we announced the severity of the fine in advance to boost deterrence. In addition, in line with the phenomenon of underweighting of rare events, the effect was stronger when the probability of inspection was rarer (as in most real-life inspection probabilities) and was eliminated under moderate inspection probabilities. We thus recommend that policymakers looking to effectively reduce recurring violations among noncriminal populations should consider increasing inspection rates rather than punishment severity.

S. A. Sadabadi ◽  
A. Hadi-Vencheh ◽  
A. Jamshidi ◽  
M. Jalali

Owing to vague concepts frequently represented in decision data, the crisp values are inadequate to model real-life situations. In this paper, the rating of each alternative and the weight of each criterion is described by linguistic terms which can be expressed in triangular fuzzy numbers. Next, we focus on fuzzy TOPSIS (FTOPSIS) method. We show that, however, the conventional FTOPSIS is interesting, but it suffers from some flaws. The shortcomings of classical FTOPSIS are shown and some solutions are given. Further, a new similarity index is proposed and then is illustrated using numerical examples. By treating the separations of an alternative from the fuzzy positive ideal solution (FPIS) and the fuzzy negative ideal solution (FNIS) as “cost” criterion and “benefit” criterion, respectively, we reduce the original fuzzy multiple criteria decision making (FMCDM) problem to a new one with two criteria. Illustrative examples are given to show the advantages of the proposed approach.

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