bluuebunny/crossref_metadata_2025 huggingface dataset:
How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic
Authors: Bragazzi Nicola Luigi , Dai Haijiang , Damiani Giovanni , Behzadifar Masoud , Martini Mariano , Wu Jianhong
Published: May 2020

SARS-CoV2 is a novel coronavirus, responsible for the COVID-19 pandemic declared by the World Health Organization. Thanks to the latest advancements in the field of molecular and computational techniques and information and communication technologies (ICTs), artificial intelligence (AI) and Big Data can help in handling the huge, unprecedented amount of data derived from public health surveillance, real-time epidemic outbreaks monitoring, trend now-casting/forecasting, regular situation briefing and updating from governmental institutions and organisms, and health facility utilization information. The present review is aimed at overviewing the potential applications of AI and Big Data in the global effort to manage the pandemic.
Validation of the Copenhagen Psychosocial Questionnaire Version III and Establishment of Benchmarks for Psychosocial Risk Management in Sweden
Authors: Berthelsen Hanne , Westerlund Hugo , Bergström Gunnar , Burr Hermann
Published: May 2020

This study presents the Swedish standard version of the Copenhagen Psychosocial Questionnaire, COPSOQ III, and investigates its reliability and validity at individual and workplace levels with the aim of establishing benchmarks for the psychosocial work environment. Cross-sectional data from (1) a random sample of employees in Sweden aged 25–65 years (N = 2847) and (2) a convenience sample of non-managerial employees at 51 workplaces (N = 1818) were analysed. Internal consistency reliability was evaluated as well as the effects of sex, work sector and blue/white-collar work. Population benchmarks and mean scores for major occupational groups were computed based on weighted data. ICC(1) and ICC(2) estimates were computed to evaluate aggregation to the workplace level and Pearson inter-correlations to evaluate construct validity at individual and aggregated levels. The reliability and scale characteristics were satisfactory, with few exceptions, at both individual and workplace levels. The strength and direction of correlations supported the construct validity of the dimensions and the amount of variance explained by workplace justified aggregation to the workplace level. The present study thus supports the use of COPSOQ III for measurement at the workplace level and presents benchmarks for risk management as well as for research purposes.
Association between Living with Children and the Health and Health Behavior of Women and Men. Are There Differences by Age? Results of the “German Health Update” (GEDA) Study
Authors: Rattay Petra , von der Lippe Elena
Published: May 2020

Does the health of women and men living with and without minor children differ, and are age differences evident in the association? For self-rated general health, depression, back pain, overweight, smoking and sporting inactivity, the GEDA data 2009–2012 (18–54 years, n = 39,096) were used to calculate prevalence for women and men stratified by parental status (living with children: yes/no) and age. Moreover, we calculated odds ratios and predictive margins, performing logistic regressions with interaction terms of parental status and age. Women and men aged 45–54 living with children are healthier than those not living with children. Parents aged 18–24 smoke more frequently and do less sport; young mothers are also more likely to be overweight and suffer from back pain than women not living with children. In multivariable analysis, the interaction of living with children and age is significant for all outcomes (except depression and back pain in men). Living with children is an important social determinant of health, highly dependent on age. It is to be discussed whether the bio-psycho-social situation has an influence on becoming a parent, or whether parenthood in different phases of life strains or enhances health.
Gestational Diabetes Mellitus Is Associated with Age-Specific Alterations in Markers of Adiposity in Offspring: A Narrative Review
Authors: Shafaeizadeh Shila , Harvey Louise , Abrahamse-Berkeveld Marieke , Muhardi Leilani , M. van der Beek Eline
Published: May 2020

Maternal hyperglycemia alters an offspring’s metabolic health outcomes, as demonstrated by the increased risk for obesity, impaired glucose handling and diabetes from early childhood onwards. Infant growth patterns are associated with childhood adiposity and metabolic health outcomes and, as such, can be used as potential markers to detect suboptimal metabolic development at an early age. Hence, we aimed to assess whether gestational diabetes mellitus (GDM) has an impact on offspring growth trajectories. Outcomes included weight gain (WG), body mass index (BMI), and skin fold thickness (SFT) measured at least at two time points from birth to later childhood. In addition, we explored the role of early life pre- and post-natal nutritional modifiable factors on longitudinal growth in infants of mother with GDM (GDM–F1). Despite the large heterogeneity of the studies, we can still conclude that GDM seems to be associated with altered growth outcomes in the offspring. More specifically, these alterations in growth outcomes seem to be rather time-specific. Increased SFT were reported particularly at birth, with limited information on reporting SFT between 2–5 y, and increased adiposity, measured via SFT and BMI, appeared mainly in later childhood (5–10 y). Studies evaluating longitudinal growth outcomes suggested a potential role of early life nutritional modifiable factors including maternal nutrition and breastfeeding. These may impact the cycle of adverse metabolic health by attenuating growth outcome alterations among GDM–F1. Conclusions: Timely diagnoses of growth deviations in infancy are crucial for early identification of GDM–F1 who are at risk for childhood overweight and metabolic disease development.
Agreement of Three Posturographic Force Plates in the Assessment of Postural Stability
Authors: Matłosz Piotr , Wyszyńska Justyna , Podgórska-Bednarz Justyna , Leszczak Justyna , Rachwał Maciej , Przednowek Krzysztof , Drzał-Grabiec Justyna , Walicka-Cupryś Katarzyna , Drużbicki Mariusz , Zadarko Emilian
Published: May 2020

This study was designed to assess how the results obtained for three different posturographic platforms agreed with each other in an assessment of static postural stability. The study included 111 young healthy participants. A measurement of postural stability was made for each participant, with their eyes open and then closed, on each platform in a random order. The Romberg ratio, path length, and center of pressure (COP) area were analyzed. For all measures, significant differences (p < 0.05) were observed among the three force plates. The highest Spearman's rank correlation was observed between Alfa vs. CQStab2P (0.20 to 0.38), and the lowest between Alfa vs. AccuGait (−0.19 to 0.09). Similar results were obtained for the concordance correlation coefficient (0.10 to 0.22 for Alfa vs. CQStab2P and −0.6 to 0.02 for Alfa vs. AccuGait). Bland–Altman analysis for values standardized (z-scores) against AccuGait indicated a low level of agreement between compared platforms, with the largest error between AccuGait vs. Alfa, and a slightly lower error between AccuGait vs. CQStab2P or Alfa vs. CQStab2P. The 95% limits of agreement ranged from 2.38 to 7.16 (Alfa vs. AccuGait), 2.09 to 5.69 (CQStab2P vs. AccuGait), and 1.39 to 7.44 (AccuGait vs. Alfa) in COP length with eyes open and COP length Romberg ratio, respectively. Special care is recommended when comparing values relating to COPs from different devices that are analyzed by different software. Moreover, unperturbed stance tests among young healthy adults can be questioned as a valid postural control parameter.
Influence of Interval Training Frequency on Time-Trial Performance in Elite Endurance Athletes
Authors: Tønnessen Espen , Hisdal Jonny , Ronnestad Bent R.
Published: May 2020

Purpose: To determine the impact of interval training frequency in elite endurance athletes. It was hypothesized that two longer sessions would elicit greater performance improvements and physiological adaptation than four shorter sessions at the same intensity. Methods: Elite cross-country skiers and biathletes were randomly assigned to either a high-frequency group (HF group) (5 M, 1 F, age 22 (19–26), VO2max 67.8 (65.5–70.2) mL/kg/min) doing four short interval sessions per week or a low-frequency group (LF group) (8 M, 1 F, age 22 (18–23), VO2max 70.7 (67.0–73.9) mL/kg/min) doing two longer interval sessions. All interval sessions were performed at ~85% of maximum heart rate, and groups were matched for total weekly training volume. Pre- and post-intervention, athletes completed an 8 km rollerski time-trial, maximal oxygen uptake (VO2max) test, and an incremental, submaximal exercise test. Results: The LF group had a statistically significant improved time-trial performance following the intervention (p = 0.04), with no statistically significant changes in the HF group. Similarly, percentage utilization of VO2max at anaerobic threshold (p = 0.04) and exercise economy (p = 0.01) were statistically significantly improved following the intervention in the LF group only. No statistically significant changes in VO2max were observed in either group. Conclusions: Two longer interval sessions appear superior to four shorter sessions per week in promoting endurance adaptations and performance improvements in elite endurance athletes. Despite matched training volume and exercise intensity, the larger, more concentrated exercise stimulus in the LF group appears to induce more favorable adaptations. The longer time between training sessions in the LF group may also have allowed athletes to recover more effectively and better “absorb” the training. These findings are in line with the “best practice” observed by many of the world’s best endurance athletes.
Early Childhood Caries and Its Associated Factors among 9- to 18-Month Old Exclusively Breastfed Children in Thailand: A Cross-Sectional Study
Authors: Chanpum Pichet , Duangthip Duangporn , Trairatvorakul Chutima , Songsiripradubboon Siriporn
Published: May 2020

Objective: The objective of this study was to investigate the early childhood caries (ECC) status and its risk factors in 9- to 18-month-old exclusively breastfed children in Thailand. Methods: Generally healthy 9- to 18-month-old children who had been exclusively breastfed were recruited. Information on children’s oral hygiene practices and breastfeeding behaviors was collected through parental interviews using a questionnaire. Children’s oral health status was assessed following the WHO caries diagnostic criteria, modified to record the noncavitated lesions. Multivariate logistic regression analysis was adopted to investigate its association with feeding and oral hygiene practices. Results: In total, 513 mother and child dyads (47% boys) were recruited. The prevalence of ECC was 42.5%. The mean (SD) d1mft and d1mfs scores (d1 included noncavitated and cavitated carious teeth/tooth surfaces) were 1.1 (1.4) and 1.3 (2.0), respectively. Multivariate logistic regression analysis revealed that older children with higher plaque scores (OR = 75.60; 95% CI: 40.19–142.20) who were breastfed to sleep (OR = 2.85; 95% CI: 1.48–5.49) and never had their teeth cleaned (OR = 8.51; 95% CI: 1.53–47.14), had a significantly higher chance of having ECC (p < 0.05). Conclusion: Prevalence of ECC is high among exclusively breastfed children aged 9–18 months in Thailand. ECC prevalence is significantly associated with the age of children, the level of dental plaque, breastfeeding to sleep, and oral cleaning. Among all factors, the level of dental plaque is the most significant factor associated with ECC among breastfed children.
The Italian External Quality Assessment Program for Cystic Fibrosis Sweat Chloride Test: Does Active Participation Improve the Quality?
Authors: Salvatore Marco , Amato Annalisa , Floridia Giovanna , Censi Federica , Ferrari Gianluca , Tosto Fabrizio , Padoan Rita , Raia Valeria , Cirilli Natalia , Castaldo Giuseppe , Capoluongo Ettore , Caruso Ubaldo , Corbetta Carlo , Taruscio Domenica
Published: May 2020

(1) Background: Diagnostic testing for cystic fibrosis (CF) is based on a sweat chloride test (SCT) considering the appropriate signs and symptoms of the disease and results of a gene mutation analysis. In 2014, the Istituto Superiore di Sanità (ISS) established a pilot Italian external quality assessment program for CF SCT (Italian EQA-SCT), which is now a third party service carried out by the ISS. (2) Methods: The ongoing scheme is prospective, enrollment is voluntary, and the payment of a fee is required. Results are shared through a dedicated web-facility. Assessment covers the analysis, interpretation, and reporting of results. (3) Results: Thirteen, fifteen, sixteen, and fifteen different laboratories, respectively, participated from 2015 to 2016 and from 2018 to 2019 in the Italian EQA-SCT scheme. Eleven different laboratories participated each year in all four rounds of the Italian EQA-SCT. (4) Conclusions: The overall results obtained from the laboratories participating constantly clearly show that their qualitative and quantitative performance improved significantly. This is due to the opportunity—after receiving the EQA results—to constantly review their performance and address any inconsistencies. We firmly believe that participation in the EQA program will improve the quality of participating laboratories and that EQA participation should become mandatory as a fundamental requirement for laboratory accreditation.
A Holistic Model Validation Framework for Current Expected Credit Loss (CECL) Model Development and Implementation
Authors: Jacobs Michael
Published: May 2020

The Current Expected Credit Loss (CECL) revised accounting standard for credit loss provisioning is the most important change to United States (US) accounting standards in recent history. In this study, we survey and assess practices in the validation of models that support CECL, across dimensions of both model development and model implementation. On the development side, this entails the usual SR 11-7 aspects of model validation; however, highlighted in the CECL context is the impact of several key modeling assumptions upon loan loss provisions. We also consider the validation of CECL model implementation or execution elements, which assumes heightened focus in CECL given the financial reporting implications. As an example of CECL model development validation, we investigate a modeling framework that we believe to be very close to that being contemplated by institutions, which projects loan losses using time-series econometric models, for an aggregated “average” bank using Federal Deposit Insurance Corporation (FDIC) Call Report data. In this example, we assess the accuracy of 14 alternative CECL modeling approaches, and we further quantify the level of model risk using the principle of relative entropy. Apart from the illustration of several model validation issues and practices that are of particular relevance to CECL, the empirical analysis has some potentially profound policy and model risk management implications. Specifically, implementation of the CECL standard may lead to under-prediction of credit losses; furthermore, coupled with the assumption that we are at an end to the favorable phase of the credit cycle, this may be interpreted as evidence that the goal of mitigating the procyclicality in the provisioning process that motivated CECL may fail to materialize.
Dynamic Simulation Method of High-Speed Railway Engineering Construction Processes Based on Virtual Geographic Environment
Authors: Ning Xinwen , Zhu Qing , Zhang Heng , Wang Changjin , Han Zujie , Zhang Junxiao , Zhao Wen
Published: May 2020

The spatial conflicts in the construction of high-speed railways not only reduce project efficiency, but also lead to serious accidents. To address these key issues, this paper presents a dynamic simulation method for constructions processes based on a virtual geographic environment. This approach can facilitate the identification of conflicts in the construction scheme through accurately expressing and analysing the intricate spatio-temporal relations among railway facility components, construction equipment and the surrounding environment. First, a high-precision virtual geographic scene in which the construction process and methods can be visualized and modelled intuitively is established with terrain, imagery, and engineering 3D models. Then, the overall construction processes can be accurately simulated by a sequential display of the railway components and the behaviour of construction equipment. To simulate the behaviour of construction equipment, the linkage relations between each joint of construction machinery are accurately modelled and animation control parameters are extracted. Finally, a construction simulation of a high-speed railway bridge was performed, and the experimental results show that the proposed method can provide a scientific basis for the optimization of complex engineering construction schemes, safety hazard assessments, and related full life cycle tasks.
Combining Deep Learning and Location-Based Ranking for Large-Scale Archaeological Prospection of LiDAR Data from The Netherlands
Authors: Verschoof-van der Vaart Wouter B. , Lambers Karsten , Kowalczyk Wojtek , Bourgeois Quentin P.J.
Published: May 2020

This paper presents WODAN2.0, a workflow using Deep Learning for the automated detection of multiple archaeological object classes in LiDAR data from the Netherlands. WODAN2.0 is developed to rapidly and systematically map archaeology in large and complex datasets. To investigate its practical value, a large, random test dataset—next to a small, non-random dataset—was developed, which better represents the real-world situation of scarce archaeological objects in different types of complex terrain. To reduce the number of false positives caused by specific regions in the research area, a novel approach has been developed and implemented called Location-Based Ranking. Experiments show that WODAN2.0 has a performance of circa 70% for barrows and Celtic fields on the small, non-random testing dataset, while the performance on the large, random testing dataset is lower: circa 50% for barrows, circa 46% for Celtic fields, and circa 18% for charcoal kilns. The results show that the introduction of Location-Based Ranking and bagging leads to an improvement in performance varying between 17% and 35%. However, WODAN2.0 does not reach or exceed general human performance, when compared to the results of a citizen science project conducted in the same research area.
Perphenazine Attenuates the Pro-Inflammatory Responses in Mouse Models of Th2-Type Allergic Dermatitis
Authors: Heo Min-Jeong , Choi Soo Young , Lee Chanmi , Choi Yeong Min , An In-sook , Bae Seunghee , An Sungkwan , Jung Jin Hyuk
Published: May 2020

Developing dermatitis therapeutics has been faced with challenges including adverse effects of topical steroid and high cost of new developing drugs. Here, we found the expression levels of dopamine receptor D2 is higher in skin biopsies of dermatitis patients and an oxazolone-induced animal model of dermatitis. We used perphenazine, an FDA-approved dopamine receptor antagonist to determine the therapeutic effect. Two different animal models including 12-o-tetradecanoylphorbol-13-acetate (TPA) and oxazolone (OXA)-induced dermatitis were employed. TPA and OXA-mediated ear swelling was attenuated by perphenazine. Moreover, perphenazine inhibited infiltrated mast cells into lesion area. We found levels of serum IgE, histamine and cytokines are decreased in mice cotreated with perphenazine and OXA compared to OXA-treated mice. Overall, this is a first study showing that the FDA-approved, anti-psychotic drug, perphenazine, alleviates animal models of dermatitis.
Using a Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) to Classify Network Attacks
Authors: Muhuri Pramita Sree , Chatterjee Prosenjit , Yuan Xiaohong , Roy Kaushik , Esterline Albert
Published: May 2020

An intrusion detection system (IDS) identifies whether the network traffic behavior is normal or abnormal or identifies the attack types. Recently, deep learning has emerged as a successful approach in IDSs, having a high accuracy rate with its distinctive learning mechanism. In this research, we developed a new method for intrusion detection to classify the NSL-KDD dataset by combining a genetic algorithm (GA) for optimal feature selection and long short-term memory (LSTM) with a recurrent neural network (RNN). We found that using LSTM-RNN classifiers with the optimal feature set improves intrusion detection. The performance of the IDS was analyzed by calculating the accuracy, recall, precision, f-score, and confusion matrix. The NSL-KDD dataset was used to analyze the performances of the classifiers. An LSTM-RNN was used to classify the NSL-KDD datasets into binary (normal and abnormal) and multi-class (Normal, DoS, Probing, U2R, and R2L) sets. The results indicate that applying the GA increases the classification accuracy of LSTM-RNN in both binary and multi-class classification. The results of the LSTM-RNN classifier were also compared with the results using a support vector machine (SVM) and random forest (RF). For multi-class classification, the classification accuracy of LSTM-RNN with the GA model is much higher than SVM and RF. For binary classification, the classification accuracy of LSTM-RNN is similar to that of RF and higher than that of SVM.
A New Approach to Nonlinear Invariants for Hybrid Systems Based on the Citing Instances Method
Authors: He Honghui , Wu Jinzhao
Published: May 2020

In generating invariants for hybrid systems, a main source of intractability is that transition relations are first-order assertions over current-state variables and next-state variables, which doubles the number of system variables and introduces many more free variables. The more variables, the less tractability and, hence, solving the algebraic constraints on complete inductive conditions by a comprehensive Gröbner basis is very expensive. To address this issue, this paper presents a new, complete method, called the Citing Instances Method (CIM), which can eliminate the free variables and directly solve for the complete inductive conditions. An instance means the verification of a proposition after instantiating free variables to numbers. A lattice array is a key notion in this paper, which is essentially a finite set of instances. Verifying that a proposition holds over a Lattice Array suffices to prove that the proposition holds in general; this interesting feature inspires us to present CIM. On one hand, instead of computing a comprehensive Gröbner basis, CIM uses a Lattice Array to generate the constraints in parallel. On the other hand, we can make a clever use of the parallelism of CIM to start with some constraint equations which can be solved easily, in order to determine some parameters in an early state. These solved parameters benefit the solution of the rest of the constraint equations; this process is similar to the domino effect. Therefore, the constraint-solving tractability of the proposed method is strong. We show that some existing approaches are only special cases of our method. Moreover, it turns out CIM is more efficient than existing approaches under parallel circumstances. Some examples are presented to illustrate the practicality of our method.
Knowledge Graphs for Online Marketing and Sales of Touristic Services
Authors: Fensel Anna , Akbar Zaenal , Kärle Elias , Blank Christoph , Pixner Patrick , Gruber Andreas
Published: May 2020

Direct online marketing and sales are nowadays an essential part of almost any business that addresses an end consumer, such as in tourism. On the downside, the data and content required for such marketing and sales are typically distributed, and difficult to identify and use, especially for small and medium enterprises. Further, a combination of content management and semantics for automated online marketing and sales is becoming practically feasible now, especially with the global adoption of knowledge graphs. A design and feasibility pilot of a solution implementing semantic content and data value chain for online direct marketing and sales, basing on knowledge graphs, and efficiently addressing multiple channels and stakeholders, is provided and evaluated with the end-users. The implementation is shown to be suitable for the use on the Web, social media and mobile channels. The proof of concept addresses the tourism sector, exploring, in particular, the case of touristic service packaging, and is applicable globally. The typically encountered challenges, particularly, the ones related to data quality, are identified, and the ways to overcome them are discussed. The paper advances the knowledge of employment of knowledge graphs in online marketing and sales, and showcases its related innovative practical application, co-created by the industry providing marketing and sales solutions for Austria, one of the world’s leading touristic regions.
Assessment of Shape Variation Patterns in Triatoma infestans (Klug 1834) (Hemiptera: Reduviidae: Triatominae): A First Report in Populations from Bolivia
Authors: Vilaseca Carolina , Méndez Marco A. , Pinto Carlos F. , Benítez Hugo A.
Published: May 2020

The morphological variations of four populations of geographically isolated Triatoma infestans located in the area of inter-Andean valleys and Chaco of Chuquisaca, Bolivia, were evaluated. Fifty-three females and sixty-one males were collected in the peri-domicile and analyzed with geometric morphometrics tools to study the patterns of the head and wing shape variation. The principal component analysis and canonical variate analysis revealed morphological variations between the populations studied, which were then confirmed by the permutation test of the differences between populations using Mahalanobis and Procustes distances. The multivariate regression analysis shows that the centroid size influences the shape of the heads and wings. T. infestans of the inter-Andean valleys are longer in the head and wings compared to the population of the Chaco. We propose that the geometric shape variation may be explained by geographical changes in climatic conditions, peri-domiciliar habitats, food source quality, and the use of insecticides.
RETRACTED: Cold Responses of the Mediterranean Fruit Fly Ceratitis capitata Wiedemann (Diptera: Tephritidae) in Blueberry
Authors: Al-Behadili Farhan , Agarwal Manjree , Xu Wei , Ren Yonglin
Published: May 2020

This article has been retracted and removed at the request of Murdoch University owing to legal issues of confidentiality. Please refer to the retraction note.
Highly Crystalline Ordered Cu-dopedTiO2Nanostructure by Paper Templated Method: Hydrogen Production and Dye Degradation under Natural Sunlight
Authors: Kale Gajanan , Arbuj Sudhir , Chothe Ujjwala , Khore Supriya , Nikam Latesh , Kale Bharat
Published: May 2020

A highly crystalline ordered Cu-TiO2 nanostructure was synthesized using a simple paper template method using cupric nitrate and titanium isopropoxide as precursors. The structural study by XRD confirmed the formation of highly crystalline anatase phase of Cu-TiO2. The broad diffraction peaks of Cu-TiO2 exhibit the nanocrystalline nature of the product. The optical study by UV-DRS indicated the red shift in absorption wavelength with an increase in Cu doping, i.e., towards the visible region. The FE-SEM and FE-TEM study validated the formation of spherical shaped nanoparticles of Cu-TiO2 having sizes in the range of 20–30 nm. Considering the absorption in the visible region, the photocatalytic study was performed for water splitting and rhodamine-B (RhB) dye degradation under natural sunlight. The 2% Cu-doped TiO2 showed the highest photocatalytic hydrogen evolution, i.e., 1400 µmol·g−1·h−1 from water, among the prepared compositions. The photocatalytic performance of Cu-TiO2 conferred complete degradation of RhB dye within 40 min. The higher activity in both cases was attributed to the formation of highly crystalline ordered nanostructure of Cu-doped TiO2. This synthesis approach has potential to prepare other highly crystalline ordered nanostructured semiconductors for different applications.
Fusing Appearance and Spatio-Temporal Models for Person Re-Identification and Tracking
Authors: Chen Andrew Tzer-Yeu , Biglari-Abhari Morteza , Wang Kevin I-Kai
Published: May 2020

Knowing who is where is a common task for many computer vision applications. Most of the literature focuses on one of two approaches: determining who a detected person is (appearance-based re-identification) and collating positions into a list, or determining the motion of a person (spatio-temporal-based tracking) and assigning identity labels based on tracks formed. This paper presents a model fusion approach, aiming towards combining both sources of information together in order to increase the accuracy of determining identity classes for detected people using re-ranking. First, a Sequential k-Means re-identification approach is presented, followed by a Kalman filter-based spatio-temporal tracking approach. A linear weighting approach is used to fuse the outputs from these models together, with modification of the weights using a decay function and a rule-based system to reflect the strengths and weaknesses of the models under different conditions. Preliminary experimental results with two different person detection algorithms on an indoor person tracking dataset show that fusing the appearance and spatio-temporal models significantly increases the overall accuracy of the classification operation.
Redesigned Skip-Network for Crowd Counting with Dilated Convolution and Backward Connection
Authors: Sooksatra Sorn , Kondo Toshiaki , Bunnun Pished , Yoshitaka Atsuo
Published: May 2020

Crowd counting is a challenging task dealing with the variation of an object scale and a crowd density. Existing works have emphasized on skip connections by integrating shallower layers with deeper layers, where each layer extracts features in a different object scale and crowd density. However, only high-level features are emphasized while ignoring low-level features. This paper proposes an estimation network by passing high-level features to shallow layers and emphasizing its low-level feature. Since an estimation network is a hierarchical network, a high-level feature is also emphasized by an improved low-level feature. Our estimation network consists of two identical networks for extracting a high-level feature and estimating the final result. To preserve semantic information, dilated convolution is employed without resizing the feature map. Our method was tested in three datasets for counting humans and vehicles in a crowd image. The counting performance is evaluated by mean absolute error and root mean squared error indicating the accuracy and robustness of an estimation network, respectively. The experimental result shows that our network outperforms other related works in a high crowd density and is effective for reducing over-counting error in the overall case.
Selected Papers from the Sixth International Symposium on Marine Propulsors
Authors: Koushan Kourosh , Steen Sverre
Published: May 2020

This Special Issue is following up the success of the latest Symposium on Marine Propulsors (www [...]
Ship Wakes and Their Potential Impacts on Salt Marshes in Jamaica Bay, New York
Authors: El Safty Hoda , Marsooli Reza
Published: May 2020

Aerial photographs and field studies have revealed a rapid deterioration of salt marshes in Jamaica Bay, New York. Past studies have linked marsh deterioration to sediment supply, water quality, storms, and sea level rise. Yet ship wakes and their potential impacts on marsh edge erosion are not understood. Here, we study ship wake transformation in Jamaica Bay and their potential impacts on salt marsh erosion. We apply short-time, Fourier transform (spectrogram) on existing water level measurements collected during 2015 and 2016. Our analysis reveals the existence of typical wake components. Among the observed wake components is a long wave component which propagates over shallow areas where short wind waves do not reach. We further implement a phase-resolving wave model to study wake transformation in the vicinity of salt marsh islands Little Egg and Big Egg and the consequent morphological changes. The selected marshes are located near a deep shipping channel and a ferry station, making them exposed to wakes of vessels with different size and sailing speed. A series of numerical experiments show that ship wakes can result in erosion spots near the border of deep shipping channels and their banks, i.e., edges of mudflats and marsh substrates. We show that the cumulative erosion increases rapidly with the number of vessels that pass through the study area. For instance, the magnitude of final bed erosion after the passage of 10 vessels is two to three times larger than that after the passage of five vessels.
SPIDER as A Rehabilitation Tool for Patients with Neurological Disabilities: The Preliminary Research
Authors: Glowinski Sebastian , Blazejewski Andrzej
Published: May 2020

(1) Background and purpose: SPIDER (Strengthening Program for Intensive Developmental Exercises and activities for Reaching health capability) is dedicated for patients suffering from Cerebral Palsy, Sclerosis Multiplex, Spinal Bifida, Spinal Muscular Atrophy and strokes. Authors proposed a computer model for the evaluation patient’s condition and the rehabilitation progress. (2) Methods: The 2-year-old and 76-year-old patients with neurological problems, who underwent individual therapy included balancing and coordination practising with SPIDER device. The model comparing the forces, which act during the therapy process, such as the expander and gravity forces, was worked out using Matlab software. (3) Results: The model allowed controlling the changes into the patients centre of gravity forces continuous adjustment and postural stability during any patient’s movement. After rehabilitation sessions, lasted for 28 days during which patients received the progress information and the therapist got the numeric data, regarding the period of the therapy. (4) Conclusions: The first patient was able to move, dramatically improved the ability to balance and coordination. The second one presented change in gait, improvement in mobility, motor function and decreased fall risk. The proposed computer model gives information about the forces acting to the patient body. The physiotherapist can evaluate the progress of patient verticalization and receive information, in the form of numbers and charts.
Relations between Land Tenure Security and Agricultural Productivity: Exploring the Effect of Land Registration
Authors: Alban Singirankabo Uwacu , Willem Ertsen Maurits
Published: May 2020

This paper reviews the scholarly literature discussing the effect(s) of land registration on the relations between land tenure security and agricultural productivity. Using 85 studies, the paper focuses on the regular claim that land registration’s facilitation of formal documents-based land dealings leads to investment in a more productive agriculture. The paper shows that this claim is problematic for three reasons. First, most studies offer no empirical evidence to support the claim on the above-mentioned effect. Second, there are suggestions that land registration can actually threaten ‘de facto’ tenure security or even lead to insecurity of tenure. Third, the gendered realization of land registration and security may lead to uneven distribution of costs and benefits, but these effects are often ignored. Next to suggesting the importance of land information updating and the efficiency of local land management institutions, this paper also finds that more research with a combined locally-set approach is needed to better understand any relation(s) between land tenure security and agricultural productivity.
Acceleration Characteristics of Discrete Fragments Generated from Explosively-Driven Cylindrical Metal Shells
Authors: Zhou Mingxue , Wu Cheng , An Fengjiang , Liao Shasha , Yuan Xiaoxia , Xue Dongyu , Liu Jian
Published: May 2020

The acceleration characteristics of fragments generated from explosively-driven cylindrical shells are important issues in warhead design. However, there is as yet no reasonable theory for predicting the acceleration process of a specific metallic shell; existing approaches either ignore the effects of shell disintegration and the subsequent gas leakage on fragment acceleration or treat them in a simplified manner. In this paper, a theoretical model was established to study the acceleration of discrete fragments under the combined effect of shell disintegration and gas leakage. Firstly, an equation of motion was developed, where the acceleration of a cylindrical shell and the internal detonation gas was determined by the motive force impacting the inner surface of the metallic cylinder. To account for the force decrease induced by both the change in fragment area after the shell disintegrates and the subsequent drop in gas pressure due to gas leakage, the equation of motion was then associated with an equation for the locally isentropic expansion of the detonation gas and a modified gas-leakage equation. Finally, theoretical analysis was conducted by solving the associated differential equations. The proposed model showed good agreement with experimental data and numerical simulations, indicating that it was suitable for predicting the acceleration of discrete fragments generated from a disintegrated warhead shell. In addition, this study facilitated a better understanding of the complicated interaction between fragment acceleration and gas outflow.
New Materials Based on Ethylene Propylene Diene Terpolymer and Hemp Fibers Obtained by Green Reactive Processing
Authors: Stelescu Maria Daniela , Manaila Elena , Georgescu Mihai , Nituica Mihaela
Published: May 2020

The paper presents the obtaining of new green polymeric composites using a sustainable reactive processing method, namely electron beam irradiation. EPDM rubber mixtures were reinforced with different amounts of short hemp fibers, which were then irradiated at doses between 75 and 600 kGy. The samples were analyzed by determination of physical–mechanical properties, sol–gel analysis, crosslink density (using the well-known modified Flory–Rehner equation for tetra functional networks), determination of rubber–fiber interactions (using the Kraus equation), water uptake test and FTIR analysis. The obtained results indicate an improvement of the hardness, the tensile and tear strength as the quantity of hemp fibers increases. As the irradiation dose increases, there is an increase in the degree of crosslinking and the gel fraction. Analyzing the behavior of the irradiation samples using the Charlesby–Pinner equation, it is observed that all the samples tend to crosslink by irradiation, the share of degradation reactions being low. For these reasons, the new materials can be used in the food, pharmaceutical or medical field, because the obtained products are sterile and can be easily resterilized by irradiation. They have high elasticity values and can be used to make packaging, seals and other consumer goods.
Pd-Catalyzed Cyclocarbonylation of Allylic Alcohol under Benign Conditions with Ionic Liquid as Stabilizer
Authors: Nemati Nasrin , Eslamloueyan Reza , Modvig Amalie , Riisager Anders
Published: May 2020

Homogeneous palladium-catalyzed (Pd-catalyzed) cyclocarbonylation of unsaturated allylic alcohols and alkynols in the presence of hydrogen forms lactone products with important applications in the food, perfume, and polymer industry. In this work, the cyclocarbonylation of 2-methyl-3-buten-2-ol was studied for the first time using a very active Pd-DPEphos (bis[(2-diphenylphosphino)phenyl]ether) catalyst in the presence of the ionic liquid (IL) [BMIM]Cl (1-butyl-3-methylimidazolium chloride) in dichloromethane to selectively produce 4,4-dimethyl-γ-butyrolactone. The effect of different parameters such as temperature, gas partial pressures, time of reaction, substrate and ligand concentrations were investigated and found to provide optimal conditions for lactonization (95 °C, 28 bar (CO/H2/N2: 20/5/3)), 18 h, 0.1 M substrate, and 16 mol% DPEphos), which were significantly milder than previously reported systems for cyclocarbonylation. Importantly, the study further showed that presence of the IL in the reaction mixture provided stabilization of the catalyst system and prevented formation of Pd-black, which allowed reuse of the catalytic system in consecutive reactions after intermediate extraction of the lactone product.
Investigation of Porous Metal-Based 3D-Printed Anode GDLs for Tubular High Temperature Proton Exchange Membrane Fuel Cells
Authors: Bermúdez Agudelo María Catalina , Hampe Manfred , Reiber Thorsten , Abele Eberhard
Published: May 2020

A high-temperature proton exchange membrane fuel cell (HT-PEMFC) conventionally uses a planar design with carbon-based substrates as the gas diffusion layer (GDL) materials. However, the metal-based substrates allow for alternative designs. In this study, the applicability of porous thin-walled tubular elements made of 316L stainless steel as the anode GDL in a multi-layer tubular HT-PEMFC was investigated. The anode GDLs were fabricated via powder bed fusion using a laser beam (PBF-LB) process with defined porosities (14% and 16%). The morphology of the porous elements was compared using scanning electron microscopy (SEM) micrographs. The influence of the porosity on the fuel cell performance was evaluated through electrochemical characterization and a short-term stability test (45 h) in a commercial test station operated at 160 °C and ambient pressure, using hydrogen as the fuel and air as the oxidant. The results showed that the fuel cell manufactured upon the anode GDL with a porosity of 16% had a higher performance with a peak power density of 329.25 W/m2 after 5 h of operation at 125.52 A/m2 and a voltage degradation rate of 0.511 mV/h over the stability test period. Moreover, this work indicates that additive manufacturing could be a useful tool for further fuel cell development.
Microstructure and Compression Properties of VSS-V3B2 Eutectic Alloys in the V-Si-B System
Authors: Müller Christopher , Hasemann Georg , Regenberg Maximilian , Betke Ulf , Krüger Manja
Published: May 2020

The present study reports on the microstructural evolution and room temperature plasticity of V(-Si)-B alloys with respect to the V solid solution (VSS)-V3B2 phase region. To investigate the occurring effects systematically, different binary V-B and ternary V-Si-B alloys were produced by conventional arc melting. Scanning electron microscope (SEM) analyses and X-ray diffraction (XRD) measurements were used to characterize the resulting as-cast microstructures. For the first time, the eutectic composition was systematically traced from the binary V-B domain to the ternary V-Si-B system. The observations discover that the binary eutectic trough (VSS-V3B2) seems to reach into the ternary system up to an alloy composition of V-5Si-9B. Room temperature compression tests were carried out in order to study the impact of single-phase and multi-phase microstructures on the strength and plasticity of binary and ternary alloys. The results indicate that the VSS phase controls the plastic deformability in the VSS-V3B2 eutectic microstructure whereas the intermetallic V3B2 acts as a strong hardening phase.
The Methods and Experiments of Shape Measurement for Off-Axis Conic Aspheric Surface
Authors: Li Shijie , Zhang Jin , Liu Weiguo , Liang Haifeng , Xie Yi , Li Xiaoqin
Published: May 2020

The off-axis conic aspheric surface is widely used as a component in modern optical systems. It is critical for this kind of surface to obtain the real accuracy of the shape during optical processing. As is widely known, the null test is an effective method to measure the shape accuracy with high precision. Therefore, three shape measurement methods of null test including auto-collimation, single computer-generated hologram (CGH), and hybrid compensation are presented in detail in this research. Although the various methods have their own advantages and disadvantages, all methods need a special auxiliary component to accomplish the measurement. In the paper, an off-axis paraboloid (OAP) was chosen to be measured using the three methods along with auxiliary components of their own and it was shown that the experimental results involved in peak-to-valley (PV), root-mean-square (RMS), and shape distribution from three methods were consistent. As a result, the correctness and effectiveness of these three measurement methods were confirmed, which are very useful in engineering.
Following the Martensitic Configuration Footprints in the Transition Route of Ni-Mn-Ga Magnetic Shape Memory Films: Insight into the Role of Twin Boundaries and Interfaces
Authors: Takhsha Ghahfarokhi Milad , Nasi Lucia , Casoli Francesca , Fabbrici Simone , Trevisi Giovanna , Cabassi Riccardo , Albertini Franca
Published: May 2020

Magnetic shape memory Heuslers have a great potential for their exploitation in next-generation cooling devices and actuating systems, due to their “giant” caloric and thermo/magnetomechanical effects arising from the combination of magnetic order and a martensitic transition. Thermal hysteresis, broad transition range, and twinning stress are among the major obstacles preventing the full exploitation of these materials in applications. Using Ni-Mn-Ga seven-modulated epitaxial thin films as a model system, we investigated the possible links between the phase transition and the details of the twin variants configuration in the martensitic phase. We explored the crystallographic relations between the martensitic variants from the atomic-scale to the micro-scale through high-resolution techniques and combined this information with the direct observation of the evolution of martensitic twin variants vs. temperature. Based on our multiscale investigation, we propose a route for the martensitic phase transition, in which the interfaces between different colonies of twins play the major role of initiators for both the forward and reverse phase transition. Linking the martensitic transition to the martensitic configuration sheds light onto the possible mechanisms influencing the transition and paves the way towards microstructure engineering for the full exploitation of shape memory Heuslers in different applications.
Study on the Microstructure of the New Paste of Recycled Aggregate Self-Compacting Concrete
Authors: Zitouni Kheira , Djerbi Assia , Mebrouki Abdelkader
Published: May 2020

Previous literature indicates a decrease in the mechanical properties of various concrete types that contain recycled aggregates (RA), due to their porosity and to their interface of transition zone (ITZ). However, other components of the RA concrete microstructure have not yet been explored, such as the modification of the new paste (NP) with respect to a reference concrete. This paper deals with the microstructure of the new paste of self-compacting concrete (SCC) for different levels of RA. The water to binder ratio (w/b) was kept constant for all concrete mixtures, and equal to 0.5. The SCC mixtures were prepared with percentages of coarse RA of 0%, 30%, 50% and 100%. Mercury intrusion porosimetry test (MIP) and scanning electron microscope (SEM) observations were conducted on the new paste of each concrete. The results indicated that the porosity of the new paste presents a significant variation for replacement percentages of 50% and 100% with respect to NP0 and NP30. However, RA contributed to the refinement of the pore structure of the new paste. The amount of macrospores the diameter of which is in the 50–10,000 nm range was reduced to 20% for NP50 and NP100, while it was about 30% for NP0 and NP30, attributed to the water released by RA. Compressive strength loss for SCC50 and SCC100 concretes are both influenced by porosity of RA, and by the NP porosity. The latter is similar for these two concretes with the 26% increase compared to a reference concrete.