maturity stage
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2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Híngred Ferraz Pereira Resende ◽  
Patricia Alcantara Cardoso ◽  
Tharcisio Cotta Fontainha ◽  
Adriana Leiras

PurposeThis paper proposes a maturity model (MM) for assessing disaster operations and identifying strategies for organisations to evolve their maturity stages.Design/methodology/approachThis study applies a systematic literature review to identify state-of-the-art work related to maturity models for disaster operations. In addition, the study develops a case study to validate the proposed maturity model in a generic scenario and two real-life scenarios.FindingsThe analysis of 158 papers in the literature resulted in identifying 8 maturity models for disaster operations. Based on their structure, the authors proposed a new model with five maturity stages suitable for any of the four phases of the disaster life cycle (i.e. mitigation, preparedness, response and recovery). In addition, the research identified and presents 24 strategies for improving disaster operations according to each maturity stage transition. Finally, the research presents a case study that evaluates the disaster response operations from a Civil Defense organisation considering a response scenario disaster in general, a flood scenario, and the COVID-19 pandemic scenario.Originality/valueThis study provides the following three main contributions useful for academics and practitioners in the disaster operations area: a new maturity model for assessing disaster operations, a strategy guide for improving disaster operations based on a maturity evolution and an empirical study exploring the approximation between academia and professionals involved in real-life disaster operations management.

María Teresa Martínez-Romero ◽  
Antonio Cejudo ◽  
Pilar Sainz de Baranda

Puberty is a vulnerable period for musculoskeletal disorders due to the existence of a wide inter-individual variation in growth and development. The main objective of the present study was to describe the prevalence of back pain (BP) in the past year and month in school-aged children according to sex, age, maturity status, body mass index (BMI) and pain characteristics. This study involved 513 students aged between 9 and 16 years. Anthropometric measures were recorded to calculate the maturity stage of the students using a regression equation comprising measures for age, body mass, body height, sitting height and leg length. An ad hoc questionnaire composed of eight questions was used to describe BP prevalence in school-aged children. The results showed that the prevalence of BP in school-aged children was observed in 35.1% over the last year (45% boys and 55% girls), and 17.3% (40.4% boys and 59.6% girls, with an association found between female sex and BP) in the last month. The prevalence of back pain in the past year and month was higher the older the students were, or the more pubertal development they had experienced. The prevalence of BP in the last year was also higher in those with overweight or obesity. After adjustment for sex, there was an association between BP and older age and higher BMI in boys and an association between BP and higher pubertal development in girls. In summary, the present study showed that the prevalence of BP was related to the maturity stage and weight of the participants, with different prevalence patterns found according to sex.

2022 ◽  
Vol 4 (1) ◽  
pp. 32-47
Denchai Worasawate ◽  
Panarit Sakunasinha ◽  
Surasak Chiangga

Most mango farms classify the maturity stage manually by trained workers using external indicators such as size, shape, and skin color, which can lead to human error or inconsistencies. We developed four common machine learning (ML) classifiers, the k-mean, naïve Bayes, support vector machine, and feed-forward artificial neural network (FANN), all of which were aimed at classifying the ripeness stage of mangoes at harvest. The ML classifiers were trained on biochemical data and then tested on physical and electrical data.The performance of the ML models was compared using fourfold cross validation. The FANN classifier performed the best, with a mean accuracy of 89.6% for unripe, ripe, and overripe classes, when compared to the other classifiers.

Geofluids ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-9
Jingkui Mi ◽  
Kun He ◽  
Yanhuan Shuai ◽  
Jinhao Guo

In this study, a methane (CH4) cracking experiment in the temperature range of 425–800°C is presented. The experimental result shows that there are some alkane and alkene generation during CH4 cracking, in addition to hydrogen (H2). Moreover, the hydrocarbon gas displays carbon isotopic reversal ( δ 13 C 1 > δ 13 C 2 ) below 700°C, while solid carbon appears on the inner wall of the gold tube above 700°C. The variation in experimental products (including gas and solid carbon) with increasing temperature suggests that CH4 does not crack into carbon and H2 directly during its cracking, but first cracks into methyl (CH3⋅) and proton (H+) groups. CH3⋅ shares depleted 13C for preferential bond cleavage in 12C–H rather than 13C–H. CH3⋅ combination leads to depletion of 13C in heavy gas and further causes the carbon isotopic reversal ( δ 13 C 1 > δ 13 C 2 ) of hydrocarbon gas. Geological analysis of the experimental data indicates that the amount of heavy gas formed by the combination of CH3⋅ from CH4 early cracking and with depleted 13C is so little that can be masked by the bulk heavy gas from organic matter (OM) and with enriched 13C at R o < 2.5 % . Thus, natural gas shows normal isotope distribution ( δ 13 C 1 < δ 13 C 2 ) in this maturity stage. CH3⋅ combination (or CH4 polymerization) intensifies on exhaustion gas generation from OM in the maturity range of R o > 2.5 % . Therefore, the carbon isotopic reversal of natural gas appears at the overmature stage. CH4 polymerization is a possible mechanism for carbon isotopic reversal of overmature natural gas. The experimental results indicate that although CH4 might have start cracking at R o > 2.5 % , but it cracks substantially above 6.0% R o in actual geological settings.

Molecules ◽  
2022 ◽  
Vol 27 (1) ◽  
pp. 308
Jing Wang ◽  
Xuxiao Tang ◽  
Qiulu Chu ◽  
Mengyu Zhang ◽  
Yingzhong Zhang ◽  

Volatile flavor of edible oils is an important quality index and factor affecting consumer choice. The purpose of this investigation was to characterize virgin Camellia oleifera seed oil (VCO) samples from different locations in southern China in terms of their volatile compounds to show the classification of VCO with respect to geography. Different samples from 20 producing VCO regions were collected in 2020 growing season, at almost the same maturity stage, and processed under the same conditions. Headspace solid-phase microextraction (HS-SPME) with a gas chromatography–mass spectrometer system (GC–MS) was used to analyze volatile compounds. A total of 348 volatiles were characterized, including aldehydes, ketones, alcohols, acids, esters, alkenes, alkanes, furans, phenols, and benzene; the relative contents ranged from 7.80–58.68%, 1.73–12.52%, 2.91–37.07%, 2.73–46.50%, 0.99–12.01%, 0.40–14.95%, 0.00–27.23%, 0.00–3.75%, 0.00–7.34%, and 0.00–1.55%, respectively. The VCO geographical origins with the largest number of volatile compounds was Xixiangtang of Guangxi (L17), and the least was Beireng of Hainan (L19). A total of 23 common and 98 unique volatile compounds were detected that reflected the basic and characteristic flavor of VCO, respectively. After PCA, heatmap and PLS-DA analysis, Longchuan of Guangdong (L8), Qingshanhu of Jiangxi (L16), and Panlong of Yunnan (L20) were in one group where the annual average temperatures are relatively low, where annual rainfalls are also low. Guangning of Guangdong (L6), Yunan of Guangdong (L7), Xingning of Guangdong (L9), Tianhe of Guangdong (L10), Xuwen of Guangdong (L11), and Xiuying of Hainan (L18) were in another group where the annual average temperatures are relatively high, and the altitudes are low. Hence, volatile compound distributions confirmed the differences among the VCO samples from these geographical areas, and the provenance difference evaluation can be carried out by flavor.

2022 ◽  
Vol 44 (3) ◽  
pp. 277-280
H.P. DAS ◽  

Results of an experiment conducted at the Central Agromet Observatory on gram crop during 1990-1991 winter crop season, to investigate relative contribution of energy balance parameters, presented in the study.   The analysis revealed that latent heat is the major source of dissipation of net r early maturity stage. After crop attains maturity, sensible heat predominates over other components.    

2021 ◽  
Vol 43 (4) ◽  
pp. 411-414
H.P. DAS ◽  

A methodology has been presented to compute basal crop coefficient from soil moisture and heat unit accumulations, for wheat in the humid region of northeast India. In developing the method data from 1976-77 to 1981-82 crop seasons for the Sonalika variety of wheat from germination to maturity have been used and tested on independent data set for 1982-83 and 1985-86 crop seasons.   Milk stage to physiological maturity stage is found to use maximum fraction of heat unit totals. The largest value of basal crop coefficient is about I 5 occurring during milk stage of the crop growth. Very high correlation is noticed between the actual ET and those computed from the model.

2021 ◽  
Vol 12 (6) ◽  
pp. 745-750
D. Anil Kumar ◽  
P. Srikanth ◽  
T. L. Neelima ◽  
M. Uma Devi ◽  

A study was carried out using the temporal Sentinel-1B microwave data (June to November at 12 days interval) and Sentinel-2A/2B optical data (June to November) to discriminate the maize crop from other competing crops rice and cotton in Siddipet district, Telangana state, India during kharif, 2019 (June to November). The study utilized the data from multiple sources such as Multi-temporal VH backscatter intensity from Sentinel-1B SAR and NDVI values from Sentinel-2A/2B in combination with field data to discriminate the maize crop. Synchronous to satellite pass, ground truth data on crop parameters viz., crop stage, crop vigour, biomass, plant height, plant density, soil moisture, LAI and chlorophyll content were collected. Multi-temporal VH backscatter intensity and Normalized Difference Vegetation Index (NDVI) data were used to characterize backscatter and greenness behaviour of the maize crop. The backscatter intensity (dB) for maize crop ranged from -21.83 (the lowest backscatter values) at planting to -12.52 (the highest backscatter values) at peak growth stage. The NDVI values during vegetative and reproductive stages (August and September) were >0.6 and during senescence to harvesting the values were less than or equal to 0.52. The increase in backscatter intensity values from initial vegetative stage to peak stage was due to increased volume scattering of the maize crop canopy and a continuous decline in backscatter intensity values of VH band at maturity stage, was due to decrease in greenness and moisture content in leaves of the maize crop helped in maize crop discrimination from other dominant kharif crops in the study area.

Ammar Motea Askarieh, Sawsan Suleiman, Mahasen Tawakalna Ammar Motea Askarieh, Sawsan Suleiman, Mahasen Tawakalna

The study aims to increase the fruitset percentage of sweet cherry trees, reduce their fall rate and increase fruit retention percentage that reaches the maturity stage. It was conducted during 2019/2020 years at Cherry orchard located in Sargaya- Al- Zabadani area in Rural Damascus, in Syria. the experiment included 4 foliar spray treatments (T1: Control, T2: Zn (100 ppm), T3: B (500 ppm), T4: (100 ppm Zn + 500 ppm B) on sweet cherry trees (Prunus Avium L.) cultivar (Bing) the fruitset percentage, fruit drop percentage, fruiting factor, and yield quantity were calculated for all treatments. The results showed that all treatments (T2, T3, T4) recorded higher fruitset percentage, compared to the control (T1) with no significant differences between (74.83, 76.35, 76.25%) respectively, while the control fruitset percentage (72.76%), and (T4) has achieved the highest percentage of fruiting factor (41.40%) with no significant differences between it and treatment (T3) (37.12%), and the highest yield (19.98 kg), as well as (T2, T3) treatments was (9.39, 10.80 kg/tree) respectively, while the control yield was (5.93 kg/tree). Therefore, it can be considered that treatment (T4) has succeeded in reducing Sweet cherry fruit drop, where the fruit drop percentage didn't exceed (70.27%), and in (T2, T3) treatments was (74.94, 72.99%) respectively, while it reached in the control treatment to (80.64%).

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