bluuebunny/crossref_metadata_2025 huggingface dataset:
Ex-Vivo Preservation with the Organ Care System in High Risk Heart Transplantation
Authors: Rojas Sebastian V. , Avsar Murat , Ius Fabio , Schibilsky David , Kaufeld Tim , Benk Christoph , Maeding Ilona , Berchtold-Herz Michael , Bara Christoph , Beyersdorf Friedhelm , Haverich Axel , Warnecke Gregor , Siepe Matthias
Published: February 2022

Objective: Ex vivo organ perfusion is an advanced preservation technique that allows graft assessment and extended ex situ intervals. We hypothesized that its properties might be especially beneficial for high-risk recipients and/or donors with extended criteria. Methods: We reviewed the outcomes of 119 consecutive heart transplant patients, which were divided into two groups: A (OCS) vs. B (conventional). Ex vivo organ perfusion was performed using the Organ Care System (OCS). Indications for OCS-usage were expected ischemic time of >4 h or >2 h plus given extended donor criteria. Results: Both groups included mostly redo cases (A: 89.7% vs. B: 78.4%; p = 0.121). Incidences of donors with previous cardiac arrest (%) (A: 32.4 vs. B: 22.2; p < 0.05) or LV-hypertrophy (%) (A: 19.1 vs. B: 8.3; p = 0.119) were also increased in Group A. Ex situ time (min) was significantly longer in Group A (A: 381 (74) vs. B: 228 (43); p < 0.05). Ventilation time (days) (A: 10.0 (19.9) vs. B: 24.3 (43.2); p = 0.057), postoperative need for ECLS (%) (A: 25.0 vs. B: 39.2; p = 0.112) and postoperative dialysis (chronic) (%) (A: 4.4 vs. B: 27.5; p < 0.001) were numerically better in the OCS group, without any difference in the occurrence of early graft rejection. The 30-d-survival (A: 92.4% vs. B: 90.2%; p = 0.745) and mid-term survival were statistically not different between both groups. Conclusions: OCS heart allowed safe transplantation of surgically complex recipients with excellent one-year outcomes, despite long preservation times and unfavourable donor characteristics. Furthermore, we observed trends towards decreased ventilation times and fewer ECLS treatments. In times of reduced organ availability and increasing recipient complexity, OCS heart is a valuable instrument that enables otherwise infeasible allocations and contributes to increase surgical safety.
Identification and Characterization of a New Splicing Variant of Prokineticin 2
Authors: Lattanzi Roberta , Maftei Daniela , Vincenzi Martina , Fullone Maria Rosaria , Miele Rossella
Published: February 2022

Prokineticin 2 (PROK2) is a secreted bioactive peptide that regulates a variety of biological responses via two GPCRs, the prokineticin receptors (PROKRs). The aim of this study was to characterize a new alternatively spliced product of the prok2 gene consisting of four exons. The 40-amino acid peptide, designated PROK2C, is encoded by exon 1 and exon 4, and its expression was detected in the hippocampus and spinal cord of mice. PROK2C was expressed in a heterologous system, Pichia pastoris, and its binding specificity to the amino-terminal regions of PROKR1 and PROKR2 was investigated by GST pull-down experiments. In addition, the introduction of the unnatural amino acid p-benzoyl-L-phenylalanine using amber codon suppression technology demonstrated the role of tryptophan at position 212 of PROKR2 for PROK2C binding by photoactivatable cross-linking. The functional significance of this new isoform was determined in vivo by nociceptive experiments, which showed that PROK2C elicits strong sensitization of peripheral nociceptors to painful stimuli. In order to analyze the induction of PROK2C signal transduction, STAT3 and ERK phosphorylation levels were determined in mammalian CHO cells expressing PROKR1 and PROKR2. Our data show by in vivo and in vitro experiments that PROK2C can bind and activate both prokineticin receptors.
Seismic Behavior of Existing Reinforced Concrete Columns with Non-Seismic Details under Low Axial Loads
Authors: Choi Myeong-Ho , Lee Chang-Hwan
Published: February 2022

Reinforced concrete (RC) columns of old existing buildings are vulnerable to earthquakes because the hoops comprising their transverse reinforcement are widely spaced and anchored using 90° hooks. This study extensively evaluated the seismic behavior of RC columns with such non-seismic details. Experiments were conducted by applying lateral cyclic loads to five full-scale column specimens with various transverse reinforcement details subjected to low axial loads. The experimental results demonstrated that the internal transverse crosstie had a significant confinement effect in the non-seismic detailed columns with 90° hoop anchor hooks. In addition, the lateral load–drift relationships, ductilities, and energy dissipation capabilities of the columns were not significantly affected by the hoop spacing or anchor hook angle when a low axial load was applied up to a drift ratio of 3.5% before failure. The evaluation model based on ASCE/SEI 41-17 was then shown to approximate the initial stiffness, maximum strength, and post-peak strength reduction behavior of the non-seismically reinforced column. This study was based on the experimental behavior of single column members, and it needs to be extended to research on frame structures in which columns are connected to beams and slabs.
Properties of Magnetic Garnet Films for Flexible Magneto-Optical Indicators Fabricated by Spin-Coating Method
Authors: Hashimoto Ryosuke , Itaya Toshiya , Uchida Hironaga , Funaki Yuya , Fukuchi Syunsuke
Published: February 2022

Non-destructive testing using a magneto-optical effect is a high-resolution non-destructive inspection technique for a metallic structure. It is able to provide high-spatial resolution images of defects. Previously, it has been difficult to fabricate flexible magneto-optical sensors because thermal treatment is necessary to crystallize the magnetic garnet. Therefore, it was not possible to apply magneto-optical imaging to complicated shapes in a test subject, such as a curved surface. In this study, we developed a new process for deposition of the magnetic garnet on the flexible substrate by applying the magnetic garnet powders that have already undergone crystallization. In this new process, as it does not require thermal treatment after deposition, flexible substrates with low heat resistance can be used. In this paper, we report our observations of the optical properties, magnetic hysteresis loop, crystallizability and density of the particles on the flexible substrate deposited by the spin-coating method.
A k,n-Threshold Secret Image Sharing Scheme Based on a Non-Full Rank Linear Model
Authors: Horng Ji-Hwei , Chen Si-Sheng , Chang Chin-Chen
Published: February 2022

Secret image sharing is a hot issue in the research field of data hiding schemes for digital images. This paper proposes a general k,n threshold secret image sharing scheme, which distributes secret data into n meaningful image shadows based on a non-full rank linear model. The image shadows are indistinguishable from their corresponding distinct cover images. Any k combination of the n shares can perfectly restore the secret data. In the proposed scheme, the integer parameters k,n, with k≤n, can be set arbitrarily to meet the application requirement. The experimental results demonstrate the applicability of the proposed general scheme. The embedding capacity, the visual quality of image shadows, and the security level are satisfactory.
Pyrazine and Phenazine Heterocycles: Platforms for Total Synthesis and Drug Discovery
Authors: Huigens Robert W. , Brummel Beau R. , Tenneti Srinivasarao , Garrison Aaron T. , Xiao Tao
Published: February 2022

There are numerous pyrazine and phenazine compounds that demonstrate biological activities relevant to the treatment of disease. In this review, we discuss pyrazine and phenazine agents that have shown potential therapeutic value, including several clinically used agents. In addition, we cover some basic science related to pyrazine and phenazine heterocycles, which possess interesting reactivity profiles that have been on display in numerous cases of innovative total synthesis approaches, synthetic methodologies, drug discovery efforts, and medicinal chemistry programs. The majority of this review is focused on presenting instructive total synthesis and medicinal chemistry efforts of select pyrazine and phenazine compounds, and we believe these incredible heterocycles offer promise in medicine.
An Emerging Role of Defective Copper Metabolism in Heart Disease
Authors: Liu Yun , Miao Ji
Published: February 2022

Copper is an essential trace metal element that significantly affects human physiology and pathology by regulating various important biological processes, including mitochondrial oxidative phosphorylation, iron mobilization, connective tissue crosslinking, antioxidant defense, melanin synthesis, blood clotting, and neuron peptide maturation. Increasing lines of evidence obtained from studies of cell culture, animals, and human genetics have demonstrated that dysregulation of copper metabolism causes heart disease, which is the leading cause of mortality in the US. Defects of copper homeostasis caused by perturbed regulation of copper chaperones or copper transporters or by copper deficiency resulted in various types of heart disease, including cardiac hypertrophy, heart failure, ischemic heart disease, and diabetes mellitus cardiomyopathy. This review aims to provide a timely summary of the effects of defective copper homeostasis on heart disease and discuss potential underlying molecular mechanisms.
Combining Hyperspectral Reflectance Indices and Multivariate Analysis to Estimate Different Units of Chlorophyll Content of Spring Wheat under Salinity Conditions
Authors: El-Hendawy Salah , Dewir Yaser Hassan , Elsayed Salah , Schmidhalter Urs , Al-Gaadi Khalid , Tola ElKamil , Refay Yahya , Tahir Muhammad Usman , Hassan Wael M.
Published: February 2022

Although plant chlorophyll (Chl) is one of the important elements in monitoring plant stress and reflects the photosynthetic capacity of plants, their measurement in the lab is generally time- and cost-inefficient and based on a small part of the leaf. This study examines the ability of canopy spectral reflectance data for the accurate estimation of the Chl content of two wheat genotypes grown under three salinity levels. The Chl content was quantified as content per area (Chl area, μg cm−2), concentration per plant (Chl plant, mg plant−1), and SPAD value (Chl SPAD). The performance of spectral reflectance indices (SRIs) with different algorithm forms, partial least square regression (PLSR), and stepwise multiple linear regression (SMLR) in estimating the three units of Chl content was compared. Results show that most indices within each SRI form performed better with Chl area and Chl plant and performed poorly with Chl SPAD. The PLSR models, based on the four forms of SRIs individually or combined, still performed poorly in estimating Chl SPAD, while they exhibited a strong relationship with Chl plant followed by Chl area in both the calibration (Cal.) and validation (Val.) datasets. The SMLR models extracted three to four indices from each SRI form as the most effective indices and explained 73–79%, 80–84%, and 39–43% of the total variability in Chl area, Chl plant, and Chl SPAD, respectively. The performance of the various predictive models of SMLR for predicting Chl content depended on salinity level, genotype, season, and the units of Chl content. In summary, this study indicates that the Chl content measured in the lab and expressed on content (μg cm−2) or concentration (mg plant−1) can be accurately estimated at canopy level using spectral reflectance data.
Trade-Off between Facilitation and Interference of Allelopathic Compounds in Vegetation Recovery: The Case of Rosmarinus officinalis in Degraded Gypsum Habitats
Authors: García-Robles Helena , Cañadas Eva María , Lorite Juan , Fernández-Ondoño Emilia
Published: February 2022

Rosmarinus officinalis advantageously competes with other species in restored gypsum outcrops, and further research is needed to understand the causes. Specifically, we focus on the potential allelopathic effects derived from its terpenes on the emergence of gypsum species. To this end, we established 120 circular subplots in a previously restored gypsum outcrop, and randomly applied four different treatments based on the presence/absence of rosemary plants and their leaves on the soil. Afterwards, we conducted an experimental sowing of native gypsophiles. All subplots were monitored to estimate seedling emergence, and soil and leaf samples were analysed for terpenes. The results show that the treatments had significant effects on the overall emergence of seedlings, and terpenes were found in rosemary leaves and soils, with no significant differences in terpene composition. In particular, we identified a clear negative effect in the treatment where rosemary plants were eliminated but its leaves were left along with allelopathy (2.57 ± 0.54 individuals/subplot). Unexpectedly, the presence of rosemary plants seems to facilitate the emergence of gypsum species (9.93 ± 1.61 individuals/subplot), counteracting the effects of the allelopathic substances in the soil. Consequently, we do not suggest removing rosemary plants in early stages to encourage the emergence of gypsum species in restored areas.
Solar-Driven Unmanned Hazardous and Noxious Substance Trapping Devices Equipped with Reverse Piloti Structures and Cooling Systems
Authors: Kim Ye Jin , Kim Hee Ju , Seo Yu Jin , Choi Ji Hee , Koo Hye Young , Choi Won San
Published: February 2022

A solar-driven unmanned hazardous and noxious substance (HNS) trapping device that can absorb, evaporate, condense, and collect HNSs was prepared. The HNS trapping device was composed of three parts: a reverse piloti structure (RPS) for absorption and evaporation of HNSs, Al mirrors with optimized angles for focusing light, and a cooling line system for the condensation of HNSs. The RPS was fabricated by assembling a lower rectangle structure and an upper hollow column. The lower rectangular structure showed a toluene evaporation rate of 6.31 kg/m2 h, which was significantly increased by the installation of the upper hollow column (11.21 kg/m2 h) and led to the formation of the RPS. The installation of Al mirrors on the RPS could further enhance the evaporation rate by 9.1% (12.28 kg/m2 h). The RPS system equipped with an Al mirror could rapidly remove toluene, xylene, and toluene–xylene with high evaporation rates (12.28–8.37 kg/m2 h) and could effectively collect these substances with high efficiencies (81–65%) in an unmanned HNS trapping device. This prototype HNS trapping device works perfectly without human involvement, does not need electricity, and thus is suitable for fast cleanup and collection of HNSs in the ocean.
Multi-Exposure Image Fusion Techniques: A Comprehensive Review
Authors: Xu Fang , Liu Jinghong , Song Yueming , Sun Hui , Wang Xuan
Published: February 2022

Multi-exposure image fusion (MEF) is emerging as a research hotspot in the fields of image processing and computer vision, which can integrate images with multiple exposure levels into a full exposure image of high quality. It is an economical and effective way to improve the dynamic range of the imaging system and has broad application prospects. In recent years, with the further development of image representation theories such as multi-scale analysis and deep learning, significant progress has been achieved in this field. This paper comprehensively investigates the current research status of MEF methods. The relevant theories and key technologies for constructing MEF models are analyzed and categorized. The representative MEF methods in each category are introduced and summarized. Then, based on the multi-exposure image sequences in static and dynamic scenes, we present a comparative study for 18 representative MEF approaches using nine commonly used objective fusion metrics. Finally, the key issues of current MEF research are discussed, and a development trend for future research is put forward.
Enhancing Spatial Resolution of SMAP Soil Moisture Products through Spatial Downscaling over a Large Watershed: A Case Study for the Susquehanna River Basin in the Northeastern United States
Authors: Wakigari Shimelis Asfaw , Leconte Robert
Published: February 2022

Soil moisture (SM) with a high spatial resolution plays a paramount role in many local and regional hydrological and agricultural applications. The advent of L-band passive microwave satellites allowed for it to be possible to measure near-surface SM at a global scale compared to in situ measurements. However, their use is often limited because of their coarse spatial resolution. Aiming to address this limitation, random forest (RF) models are adopted to downscale the SMAP level-3 (L3SMP, 36 km) and SMAP enhanced (L3SMP_E, 9 km) SM to 1 km. A suite of predictors derived from the Sentinel-1 C-band SAR and MODIS is used in the downscaling process. The RF models are separately trained and verified at both spatial scales (i.e., 36 and 9 km) considering two experiments: (1) using predictors derived from the MODIS and Sentinel-1 along with other predictors such as elevation and brightness temperature and (2) using all predictors of the first experiment except for the Sentinel-1 predictors. Only dates when the Sentinel-1 images were available are considered for the comparison of the two experiments. The comparison of the results of the two experiments indicates that the removal of Sentinel-1 predictors from the second experiment only reduces the R value from 0.84 to 0.83 and from 0.91 to 0.86 for 36 and 9 km spatial scales, respectively. Among the predictors used in the downscaling, the brightness temperature in VV polarization is identified as the most important predictor, followed by NDVI, surface albedo and API. On the contrary, the Sentinel-1 predictors play a less important role with no marked contribution in enhancing the predictive accuracy of RF models. In general, the two experiments have limitation, such as a small sample size for the training of the RF model because of the scarcity of Sentinel-1 images (i.e., revisit time of 12 days). Therefore, based on this limitation, a third experiment is proposed, in which the Sentinel-1 predictors are not considered at all in the training of the RF models. The results of the third experiment show a good agreement between the downscaled L3SMP and L3SMP_E SM, and in situ SM measurements at both spatial scales. In addition, the temporal availability of the downscaled SM increased. Moreover, the downscaled SM from both SMAP products presented greater spatial detail while preserving the spatial patterns found in their original products. The use of the two SMAP SM products as background fields for the downscaling process does not show marked differences. Overall, this study demonstrates encouraging results in the downscaling of SMAP SM products over humid climate with warm summers dominated by vegetation.
The Role of Remote Sensing Data and Methods in a Modern Approach to Fertilization in Precision Agriculture
Authors: Radočaj Dorijan , Jurišić Mladen , Gašparović Mateo
Published: February 2022

The precision fertilization system is the basis for upgrading conventional intensive agricultural production, while achieving both high and quality yields and minimizing the negative impacts on the environment. This research aims to present the application of both conventional and modern prediction methods in precision fertilization by integrating agronomic components with the spatial component of interpolation and machine learning. While conventional methods were a cornerstone of soil prediction in the past decades, new challenges to process larger and more complex data have reduced their viability in the present. Their disadvantages of lower prediction accuracy, lack of robustness regarding the properties of input soil sample values and requirements for extensive cost- and time-expensive soil sampling were addressed. Specific conventional (ordinary kriging, inverse distance weighted) and modern machine learning methods (random forest, support vector machine, artificial neural networks, decision trees) were evaluated according to their popularity in relevant studies indexed in the Web of Science Core Collection over the past decade. As a shift towards increased prediction accuracy and computational efficiency, an overview of state-of-the-art remote sensing methods for improving precise fertilization was completed, with the accent on open-data and global satellite missions. State-of-the-art remote sensing techniques allowed hybrid interpolation to predict the sampled data supported by remote sensing data such as high-resolution multispectral, thermal and radar satellite or unmanned aerial vehicle (UAV)-based imagery in the analyzed studies. The representative overview of conventional and modern approaches to precision fertilization was performed based on 121 samples with phosphorous pentoxide (P2O5) and potassium oxide (K2O) in a common agricultural parcel in Croatia. It visually and quantitatively confirmed the superior prediction accuracy and retained local heterogeneity of the modern approach. The research concludes that remote sensing data and methods have a significant role in improving fertilization in precision agriculture today and will be increasingly important in the future.
Towards Automatic License Plate Detection
Authors: Mahmood Zahid , Khan Khurram , Khan Uzair , Adil Syed Hasan , Ali Syed Saad Azhar , Shahzad Mohsin
Published: February 2022

Automatic License Plate Detection (ALPD) is an integral component of using computer vision approaches in Intelligent Transportation Systems (ITS). An accurate detection of vehicles’ license plates in images is a critical step that has a substantial impact on any ALPD system’s recognition rate. In this paper, we develop an efficient license plate detecting technique through the intelligent combination of Faster R-CNN along with digital image processing techniques. The proposed algorithm initially detects vehicle(s) in the input image through Faster R-CNN. Later, the located vehicle is analyzed by a robust License Plate Localization Module (LPLM). The LPLM module primarily uses color segmentation and processes the HSV image to detect the license plate in the input image. Moreover, the LPLM module employs morphological filtering and dimension analysis to find the license plate. Detailed trials on challenging PKU datasets demonstrate that the proposed method outperforms few recently developed methods by producing high license plates detection accuracy in much less execution time. The proposed work demonstrates a great feasibility for security and target detection applications.
Polymer Microtip on a Multimode Optical Fiber as a Threshold Volatile Organic Compounds Sensor
Authors: Marć Paweł , Żuchowska Monika , Jakubowska Iwona , Jaroszewicz Leszek R.
Published: February 2022

Polymer microtips are 3D microstructures manufactured on the end face of an optical fiber by using the photopolymerization process. Such micro-optic elements made on a multi-mode optical fiber were previously tested as a transducer of refractive index sensor. These studies were an inspiration to investigate the possibility of using this type of transducer to measure the presence of volatile organic compounds in the air. The experimental results of microtips polymerized with UV and VIS were reported. It was possible to detect the presence of five different volatile compounds in the air due to the sensitivity of the transducer to the refractive indices changes. These changes were induced by the vapors condensed on the microtip surface. The measured time responses have shown that the return loss decreases rapidly as the microtip is inserted inside a glass vial filled with the tested compound. Moreover, correlations between calculated dynamic ranges and refractive indices and volumes of the volatile compounds inside the vials were negligible. Therefore, this type of sensor can be categorized as a condensed material threshold sensor. This sensor can be used in warning systems for monitoring leakages of pipelines carrying volatile chemicals.
Respiratory Monitoring by Ultrafast Humidity Sensors with Nanomaterials: A Review
Authors: Kano Shinya , Jarulertwathana Nutpaphat , Mohd-Noor Syazwani , Hyun Jerome K. , Asahara Ryota , Mekaru Harutaka
Published: February 2022

Respiratory monitoring is a fundamental method to understand the physiological and psychological relationships between respiration and the human body. In this review, we overview recent developments on ultrafast humidity sensors with functional nanomaterials for monitoring human respiration. Key advances in design and materials have resulted in humidity sensors with response and recovery times reaching 8 ms. In addition, these sensors are particularly beneficial for respiratory monitoring by being portable and noninvasive. We systematically classify the reported sensors according to four types of output signals: impedance, light, frequency, and voltage. Design strategies for preparing ultrafast humidity sensors using nanomaterials are discussed with regard to physical parameters such as the nanomaterial film thickness, porosity, and hydrophilicity. We also summarize other applications that require ultrafast humidity sensors for physiological studies. This review provides key guidelines and directions for preparing and applying such sensors in practical applications.
Acceleration of Magnetic Resonance Fingerprinting Reconstruction Using Denoising and Self-Attention Pyramidal Convolutional Neural Network
Authors: Hong Jia-Sheng , Hermann Ingo , Zöllner Frank Gerrit , Schad Lothar R. , Wang Shuu-Jiun , Lee Wei-Kai , Chen Yung-Lin , Chang Yu , Wu Yu-Te
Published: February 2022

Magnetic resonance fingerprinting (MRF) based on echo-planar imaging (EPI) enables whole-brain imaging to rapidly obtain T1 and T2* relaxation time maps. Reconstructing parametric maps from the MRF scanned baselines by the inner-product method is computationally expensive. We aimed to accelerate the reconstruction of parametric maps for MRF-EPI by using a deep learning model. The proposed approach uses a two-stage model that first eliminates noise and then regresses the parametric maps. Parametric maps obtained by dictionary matching were used as a reference and compared with the prediction results of the two-stage model. MRF-EPI scans were collected from 32 subjects. The signal-to-noise ratio increased significantly after the noise removal by the denoising model. For prediction with scans in the testing dataset, the mean absolute percentage errors between the standard and the final two-stage model were 3.1%, 3.2%, and 1.9% for T1, and 2.6%, 2.3%, and 2.8% for T2* in gray matter, white matter, and lesion locations, respectively. Our proposed two-stage deep learning model can effectively remove noise and accurately reconstruct MRF-EPI parametric maps, increasing the speed of reconstruction and reducing the storage space required by dictionaries.
Effect of Wave Attenuation on Shear Wave Velocity Determination Using Bender Element Tests
Authors: Gao Yanbin , Zheng Xiaojun , Wang Hao , Luo Wenkang
Published: February 2022

Wave attenuation is a widespread physical phenomenon in most acoustic tests, but there is a scarcity of quantitative investigations into the influence of wave attenuation on the determination of shear wave travel time in bender element tests. To ascertain this attenuation effect, a series of bender element tests were conducted on clay samples with different lengths under unconfined conditions. The experimental results suggest that the real first peak of the received signal attenuates gradually with the increase of the sample length and even becomes undistinguished when the sample length exceeds a limit. This phenomenon results in misinterpretation of the wave travel time using the time domain method. In this study, the shear wave travel time is misinterpreted when wave travel distance over approximately 80 mm, leading to underestimation of the VS by 17% for the peak-to-peak approach and 10% for the arrival-to-arrival method. Therefore, besides the near field effect and boundary reflection, the wave attenuation effect turned out to be an important factor influencing the determination of VS using the time domain method. Accordingly, it is advisable to predetermine the limit test distance for a specific testing system under conditions, particularly for long distance testing.
CVDF DYNAMIC—A Dynamic Fuzzy Testing Sample Generation Framework Based on BI-LSTM and Genetic Algorithm
Authors: Ma Mingrui , Han Lansheng , Qian Yekui
Published: February 2022

As one of the most effective methods of vulnerability mining, fuzzy testing has scalability and complex path detection ability. Fuzzy testing sample generation is the key step of fuzzy testing, and the quality of sample directly determines the vulnerability mining ability of fuzzy tester. At present, the known sample generation methods focus on code coverage or seed mutation under a critical execution path, so it is difficult to take both into account. Therefore, based on the idea of ensemble learning in artificial intelligence, we propose a fuzzy testing sample generation framework named CVDF DYNAMIC, which is based on genetic algorithm and BI-LSTM neural network. The main purpose of CVDF DYNAMIC is to generate fuzzy testing samples with both code coverage and path depth detection ability. CVDF DYNAMIC generates its own test case sets through BI-LSTM neural network and genetic algorithm. Then, we integrate the two sample sets through the idea of ensemble learning to obtain a sample set with both code coverage and vulnerability mining ability for a critical execution path of the program. In order to improve the efficiency of fuzzy testing, we use heuristic genetic algorithm to simplify the integrated sample set. We also innovatively put forward the evaluation index of path depth detection ability (pdda), which can effectively measure the vulnerability mining ability of the generated test case set under the critical execution path of the program. Finally, we compare CVDF DYNAMIC with some existing fuzzy testing tools and scientific research results and further propose the future improvement ideas of CVDF DYNAMIC.
Performance Management and the Police Response to Women in India
Authors: Kapuria Monica , Maguire Edward R.
Published: February 2022

Crimes against women have critical implications, not only for victims but also for overall community health and safety. Communities entrust law enforcement agencies with the responsibility to safeguard vulnerable people through effective and efficient policing approaches that provide a safe environment. Enhancing and improving the efficiency and performance of the police is an important part of preventing and reducing crimes against women. One approach to addressing specific performance targets is to adopt a performance management strategy. This paper examines survey data from 310 police officials in northern India about one such strategy: the balanced scorecard (BSC). Our analysis illuminates police perspectives about the perceived benefits of a generalized performance management strategy such as the BSC for improving police performance in addressing crimes against women and the needs of female citizens. Our findings reveal that respondents’ assessments of all four dimensions of the balanced scorecard are associated with their degree of optimism that performance measurement can improve the police response to crimes against women.
Dimensions of Digital Literacy in the 21st Century Competency Frameworks
Authors: Martínez-Bravo María Cristina , Sádaba Chalezquer Charo , Serrano-Puche Javier
Published: February 2022

The Information and Knowledge Society demands the development of skills for the critical and responsible consumption and use of technology for leisure, personal, professional, academic development, and citizen participation. The international frameworks of “21st Century Competences” underline the importance of digital competence as the axis to enhance the rest of competences. This key competence goes beyond the operational use of technological tools and applications and has been studied from different approaches. This research explores digital literacy in eight international frameworks from different institutions and initiatives: UNESCO, European Union, OECD, ATCS, P21, NETS, NAEP, and Engauge, from which a content analysis is performed, and where the areas of scope of the competencies and the relationships between the different proposals are explored. The findings contribute to the understanding of an integrated approach to digital literacy, where six dimensions are identified: critical, cognitive, operational, social, emotional, and projective. Three dimensional profiles are also identified that point towards the critical use of technology, the appropriation of technology in daily life and social innovation, which invites a rethink towards digital literacy from a multi and interdimensional vision.
Social Marketing in Promoting Sustainable Healthy Lifestyle among Student Population
Authors: Milicevic Nikola , Djokic Ines , Djokic Nenad , Grubor Aleksandar
Published: February 2022

Although there are some differences in healthy lifestyle measurement, physical activity is an indispensable factor within that construct. By increasing the level of physical activity of the population, the contribution to social sustainability is provided. Social marketing can be considered as a manner to promote behavior change (including increase in physical activity level). It uses commercial marketing tools in delivering social goods. In that context can be explained previous uses of the theory of planned behavior (TPB) in social marketing researches aiming at increasing the level of physical activity of the population. In this paper, the modified TPB model, extended with self-identity and motivation variable, is implemented within the student population of the University of Novi Sad, Serbia, in 2019. The results show that intention to do regular physical activity in the week after the research was directly influenced by behavioral and normative beliefs and self-identity. It was influenced indirectly by students’ motivation. The motivation, however, directly affects students’ behavioral, normative and control beliefs. Nevertheless, the results differ among genders; although positive at both genders, the effects of normative beliefs and motivation on intention were significant only in female students (0.123 and 0.243, respectively). The authors also provide social marketing implications, i.e., potential activities within social marketing that could be performed in order to encourage students to be more physically active. In addition to belonging to relatively scarce similar researches in domestic context, the wider contribution of this paper can be identified from a methodological aspect, treating the behavioral, normative and control beliefs as formative constructs.
Sustainable Fashion Consumption: Advocating Philanthropic and Economic Motives in Clothing Disposal Behaviour
Authors: Hassan Siti Hasnah , Yeap Jasmine A. L. , Al-Kumaim Nabil Hasan
Published: February 2022

The fast fashion market is becoming popular, escalating and aggravating the throwaway culture phenomenon. Thus, it is valuable to understand the factors that influence sustainable fashion consumption and the clothing disposal pattern among young consumers in developing countries like Malaysia. Data were obtained from the online survey of 324 young adults aged 18 to 35 and were analysed using the Partial Least Square using SmartPLS (v.3.3.3i). The findings indicate that personal norms, social norms and environmental awareness were the key influencing factors of sustainable fashion consumption. Consequently, sustainable fashion consumption exhibited a positive and significant relationship towards philanthropic and economic reasons for clothing disposal behaviour. The insights from this study will assist practitioners, green manufacturers, business owners and policy makers in giving a clearer picture of what motivates sustainable fashion consumption and the clothing disposal behaviour of today’s young adults.
Do University Students’ Security Perceptions Influence Their Walking Preferences and Their Walking Activity? A Case Study of Granada (Spain)
Authors: Lizárraga Carmen , Martín-Blanco Cathaysa , Castillo-Pérez Isabel , Chica-Olmo Jorge
Published: February 2022

A sustainable city must be a safe place for its inhabitants when walking, with the absence of fear of crime being one of its main attributes. Although perceived insecurity is one of the main deterrents of walking activity, this relationship requires some clarification in environments which are walkable and safe, with low crime rates. This article contributes to the evidence for the influence of perceived security on walking activity and, as a novel aspect, also analyzes the effects of perceived security on walking as the preferred travel mode. In order to study this relationship, we use a method that combines non-linear principal component analysis (NLPCA) and a logit model (LM). The data are taken from a survey of university students carried out in the city of Granada. Results show that gender and perceived security have a greater effect on the choice of walking as the preferred travel mode, while location factors have significantly more weight in the explanation of the choice of walking as the most usual travel mode. These findings may be extended to other urban areas and can be of use for the implementation of urban policies aimed at designing the built environment to develop more sustainable cities.
Chemical Properties of Soil and Cassava Yield as a Function of Weed Management by Cover Crops in the Amazon Ecosystem
Authors: Soares Daniel Oscar , Pinto Karla Gabrielle , Bhowmik Prasanta Chitta , Albertino Sônia Maria
Published: February 2022

Cassava (Manihot esculenta) yields are severely affected by the interference of weed plants. Using cover crops for weed control appears as a sustainable alternative practice because it maintains the soil covered and reduces the need for herbicides. The aim of this study was to assess cassava crop yields and the soil chemical properties as a function of use of cover crops for weed management. Treatments were three cover crops (Brachiaria ruziziensis, Canavalia ensiformis, and Mucuna pruriens), chemical control, mechanical control, and treatment with no weed control. Cover crops reduced the diversity of species and the quantity of individuals of the weed community in cassava cultivation. The treatments with chemical and physical weed control achieved higher yields. The cover crops B. ruziziensis and C. ensiformis increased cassava yields by 30% and 14%, respectively, when compared with the treatment with no control. The cover crops increased the pH, MO, K, Ca, and Mg values when compared with the treatments with chemical and mechanical weed control. Brachiaria ruziziensis and C. ensiformis are recommended as a cover plants in cassava production systems in the Amazon region. The use of cover crops associated with cassava is a sustainable management option because, in addition to the suppressive effect on weeds, cover crops improve the chemical properties of soil, which may contribute to increasing cassava production in the long term.
From Macro to Micro: Impact of Smart Turbine Energy Harvesters (STEH), on Environmental Sustainability and Smart City Automation
Authors: Akin-Ponnle Ajibike Eunice , Pereira Felisberto Sequeira , Madureira Raquel Castro , Carvalho Nuno Borges
Published: February 2022

In the digital transition era of scaling down from macro through micro turbine; to the setting up of Smart Turbine Energy Harvesters (STEH), this paper presents Project Management (PM) principles applicable and best practices to meet the increasing energy demand of digitised technology. The massive deployment of autonomous devices such as those for Internet of Things (IoT), for the support of smart cities, has necessitated more research about their energy demands. With the use of ‘waterfall’ Project Management Methodology (PMM), turbine grid-connected energy are classified into different categories, and comparative study is made between scaling down of turbine grid from macro to micro, to the economic impact of setting up of STEH. This study concludes by proposing the use of STEH, which is an onsite green energy harvesting scheme that is self-sustaining; ubiquitous; and long lasting; as preferable source to other categories of turbine grid system. Additionally, it is an improvement on energy harvesting (EH) mechanisms using battery; whose replacement and disposal are not economical. STEH is considered economical and time saving with little or no physical and investment risk attached, the Return on Investment (RI) is considered favourable. Also, the energy delivery is sufficient for the requirement of IoT and Wireless Sensor Networks (WSN).
Sustainable Local Food Evaluation by Dosage of Some Metallic Pollutants in Wild Insect Species Consumed in Togo
Authors: Badanaro Fègbawè , Barsan Narcis , Tété-Benissan Amivi , Nedeff Valentin , Panainte-Lehadus Mirela
Published: February 2022

In tropical countries, where human consumption of insects is a traditional practice, insects are mainly harvested in the natural environment. These insects are thus exposed to all forms of pollution, particularly metallic pollutants. However, an inventory of scientific knowledge on the risks related to the consumption of insects is missing in the international scientific literature. It is therefore essential to conduct research on the trace metals (TMEs) contained in insects caught in the wild. The objective of this work is to evaluate the level of accumulation of TMEs by insect species commonly consumed in Togo to estimate the health risk related to insect consumption. To do this, 12 species of insects consumed in their adult stage were collected across the whole territory of Togo. These samples were analyzed by atomic absorption spectrophotometry to determine TMEs. It appears that traces of different metallic elements exist in the samples at variable rates. The aquatic species Cybister tripunctatus is the most contaminated, with levels of cadmium (0.504 mg/kg) and lead (0.501 mg/kg) at the limit of edibility threshold. The concentrations of all TMEs in insects during this study are within acceptable limits for human consumption. The risk of human contamination with TMEs through insect consumption is therefore low.
A Mixed Ensemble Learning and Time-Series Methodology for Category-Specific Vehicular Energy and Emissions Modeling
Authors: Moradi Ehsan , Miranda-Moreno Luis
Published: February 2022

The serially-correlated nature of engine operation is overlooked in the vehicular fuel and emission modeling literature. Furthermore, enabling the calibration and use of time-series models for instrument-independent eco-driving applications requires reliable forecast aggregation procedures. To this end, an ensemble time-series machine-learning methodology is developed using data collected through extensive field experiments on a fleet of 35 vehicles. Among other results, it is found that Long Short-Term Memory (LSTM) architecture is the best fit for capturing the dynamic and lagged effects of speed, acceleration, and grade on fuel and emission rates. The developed vehicle-specific ensembles outperformed state-of-the-practice benchmark models by a significant margin and the category-specific models outscored the vehicle-specific sub-models by an average margin of 6%. The results qualify the developed ensembles to work as representatives for vehicle categories and allows them to be utilized in both eco-driving services as well as environmental assessment modules.
Fractional Calculus for Convex Functions in Interval-Valued Settings and Inequalities
Authors: Khan Muhammad Bilal , Zaini Hatim Ghazi , Treanțǎ Savin , Santos-García Gustavo , Macías-Díaz Jorge E. , Soliman Mohamed S.
Published: February 2022

In this paper, we discuss the Riemann–Liouville fractional integral operator for left and right convex interval-valued functions (left and right convex I∙V-F), as well as various related notions and concepts. First, the authors used the Riemann–Liouville fractional integral to prove Hermite–Hadamard type (𝓗–𝓗 type) inequality. Furthermore, 𝓗–𝓗 type inequalities for the product of two left and right convex I∙V-Fs have been established. Finally, for left and right convex I∙V-Fs, we found the Riemann–Liouville fractional integral Hermite–Hadamard type inequality (𝓗–𝓗 Fejér type inequality). The findings of this research show that this methodology may be applied directly and is computationally simple and precise.
Size Effects of Microplastics on Embryos and Observation of Toxicity Kinetics in Larvae of Grass Carp (Ctenopharyngodon idella)
Authors: Zhang Chaonan , Zuo Zhiheng , Wang Qiujie , Wang Shaodan , Lv Liqun , Zou Jixing
Published: February 2022

Microplastics have caused great concern in recent years. However, few studies have compared the toxicity of different sizes of microplastics in fishes, especially commercial fishes, which are more related to human health. In the present study, we revealed the effects of varying sizes of microplastics on grass carp embryos and larvae using scanning electron microscopy (SEM) and fluorescence imaging. Embryos were exposed to 80 nm and 8 μm microplastics at concentrations of 5, 15, and 45 mg/L. Toxicity kinetics of various sizes of fluorescent microplastics were analyzed through microscopic observation in the larvae. Results found that nanoplastics could not penetrate the embryo’s chorionic membrane, instead they conglutinated or aggregated on the chorion. Our results are the first to explore the defense mechanisms of commercial fish embryos against microplastics. Larvae were prone to ingesting their own excrement, resulting in microplastic flocculants winding around their mouth. For the first time, it was found that excreted microplastics could be reconsumed by fish and reaccumulated in the oral cavity. Microplastics of a certain size (1 μm) could be accumulated in the nasal cavity. We speculate that the presence of a special groove structure in the nasal cavity of grass carp larvae may manage to seize the microplastics with a particular size. As far as we know, this is the first report of microplastics being found in the nasal passages of fish. Fluorescence images clearly recorded the toxicity kinetics of microplastics in herbivorous fish.
Acknowledgment to Reviewers of Transplantology in 2021
Authors:   Transplantology Editorial Office
Published: February 2022

Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Optimization, Production, Purification and Characterization of HIV-1 GAG-Based Virus-like Particles Functionalized with SARS-CoV-2
Authors: Boix-Besora Arnau , Lorenzo Elianet , Lavado-García Jesús , Gòdia Francesc , Cervera Laura
Published: February 2022

Virus-like particles (VLPs) constitute a promising approach to recombinant vaccine development. They are robust, safe, versatile and highly immunogenic supra-molecular structures that closely mimic the native conformation of viruses without carrying their genetic material. HIV-1 Gag VLPs share similar characteristics with wild-type severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, making them a suitable platform for the expression of its spike membrane protein to generate a potential vaccine candidate for COVID-19. This work proposes a methodology for the generation of SARS-CoV-2 VLPs by their co-expression with HIV-1 Gag protein. We achieved VLP functionalization with coronavirus spike protein, optimized its expression using a design of experiments (DoE). We also performed the bioprocess at a bioreactor scale followed by a scalable downstream purification process consisting of two clarifications, an ion exchange and size-exclusion chromatography. The whole production process is conceived to enhance its transferability at current good manufacturing practice (cGMP) industrial scale manufacturing. Moreover, the approach proposed could be expanded to produce additional Gag-based VLPs against different diseases or COVID-19 variants.