Hyperspectral imaging for predicting soluble solid content of starfruit

Hyperspectral imaging technology is a powerful tool for non-destructive quality assessment of fruits. The objective of this research was to develop novel calibration model based on hyperspectral imaging to estimate soluble solid content (SSC) of starfruits. A hyperspectral imaging system, which consists of a near infrared camera, a spectrograph V10, a halogen lighting and a conveyor belt system, was used in this study to acquire hyperspectral images of the samples in visible and near infrared (500-1000 nm) regions. Partial least square (PLS) was used to build the model and to find the optimal wavelength. Two different masks were applied for obtaining the spectral data. The optimal wavelengths were evaluated using multi linear regression (MLR). The coefficient of determination (R2) for validation using the model with first mask (M1) and second mask (M2) were 0.82 and 0.80, respectively

U-ASD Net: supervised crowd counting based on semantic segmentation and adaptive scenario discovery

Crowd counting considers one of the most significant and challenging issues in computer vision and deep learning communities, whose applications are being utilized for various tasks. While this issue is well studied, it remains an open challenge to manage perspective distortions and scale variations. How well these problems are resolved has a huge impact on predicting a high-quality crowd density map. In this study, a hybrid and modified deep neural network (U-ASD Net), based on U-Net and adaptive scenario discovery (ASD), is proposed to get precise and effective crowd counting. The U part is produced by replacing the nearest upsampling in the encoder of U-Net with max-unpooling. This modification provides a better crowd counting performance by capturing more spatial information. The max-unpooling layers upsample the feature maps based on the max locations held from the downsampling process. The ASD part is constructed with three light pathways, two of which have been learned to reflect various densities of the crowd and define the appropriate geometric configuration employing various sizes of the receptive field. The third pathway is an adaptation path, which implicitly discovers and models complex scenarios to recalibrate pathway-wise responses adaptively. ASD has no additional branches to avoid increasing the complexity. The designed model is end-to-end trainable. This integration provides an effective model to count crowds in both dense and sparse datasets. It also predicts an elevated quality density map with a high structural similarity index and a high peak signal-to-noise ratio. Several comprehensive experiments on four popular datasets for crowd counting have been carried out to demonstrate the proposed method's promising performance compared to other state-of-the-art approaches. Furthermore, a new dataset with its manual annotations, called Haramain with three different scenes and different densities, is introduced and used for evaluating the U-ASD Net

Enhanced rotational feature points matching using orientation correction

In matching between images, several techniques have been developed particularly for estimating orientation assignment in order to make feature points invariant to rotation. However, imperfect estimation of the orientation assignment may lead to feature mismatching and a low number of correctly matched points. Additionally, several possible candidates with high correlation values for one feature in the reference image may lead to matching confusion. In this paper, we propose a post-processing matching technique that will not only increase the number of correctly matched points but also manage to solve the above mentioned two issues. The key idea is to modify feature orientation based on the relative rotational degree between two images, obtained by taking the difference between the major correctly matched points in the first matching cycle. From the analysis, our proposed method shows that the number of detected points correctly matched with the reference image can be increased by up to 50%. In addition, some mismatched points due to similar correlation values in the first matching round can be corrected. Another advantage of the proposed algorithm it that it can be applied to other state-of-the-art orientation assignment techniques

Enhanced rotational feature points matching using orientation correction

In matching between images, several techniques have been developed particularly for estimating orientation assignment in order to make feature points invariant to rotation. However, imperfect estimation of the orientation assignment may lead to feature mismatching and a low number of correctly matched points. Additionally, several possible candidates with high correlation values for one feature in the reference image may lead to matching confusion. In this paper, we propose a post-processing matching technique that will not only increase the number of correctly matched points but also manage to solve the above mentioned two issues. The key idea is to modify feature orientation based on the relative rotational degree between two images, obtained by taking the difference between the major correctly matched points in the first matching cycle. From the analysis, our proposed method shows that the number of detected points correctly matched with the reference image can be increased by up to 50%. In addition, some mismatched points due to similar correlation values in the first matching round can be corrected. Another advantage of the proposed algorithm it that it can be applied to other state-of-the-art orientation assignment techniques

Optimal Number of Nodes Deployment Method in Corona-Based WSN

Wireless sensor networks (WSNs) consist of several nodes with limited and non-rechargeable power resources. Therefore, energy efficiency and network lifetime depend on the utilize way of sensor nodes. Recently, some methods and strategies have been employed in this regard. Most of them could improve network lifespan to an acceptable level. Energy hole is one of inherent problems which can decrease the network lifetime to 89%. In multi-hop WSNs, the sensors located closer to sink must relay more data packets in comparison with other ones, thus their power supplies will be exhausted earlier than other nodes. Whereas, the sensor nodes belonging to other layers still have required energy for transmitting their data packets. This asynchronous energy depletion is considered as a problem. In this paper, we present a mathematical model for non-uniform node deployment for corona-based WSNs. According to results, Optimal Number of Nodes Deployment Method (ONNDM) enhance the network lifetime via balancing energy consumption and workload among coronas. In ONNDM, the optimum number of nodes in each corona is obtained by a mathematical formula, which can outperform other proposed strategies

Kinetic studies of the partially purified molybdenum-reducing enzyme from Bacillus pumilus strain Lbna

Bacterial based remediation of environmental toxicants is a promising innovative technology for molybdenum pollution. To date, the enzyme responsible for molybdate reduction to Mo-blue from bacteria show that the Michaelis-Menten constants varies by one order of magnitude. It is important that the constants from newer enzyme sources be characterized so that a comparison can be made. The aim of this study is to characterize kinetically the enzyme from a previously isolated Mo-reducing bacterium; Bacillus pumilus strain Lbna. The maximum activity of this enzyme occurred at pH 5.5 and in between 25 and 35 °C. The Km and Vmax of NADH were 6.646 mM and 0.057 unit/mg enzyme, while the Km and Vmax of LPPM were 3.399 mM and 0.106 unit/mg enzyme. The results showed that the enzyme activity for Bacillus pumilus strain Lbna were inhibited by all heavy metals used. Zinc, copper, silver, chromium, cadmium and mercury all caused more than 50% inhibition to the Mo-reducing enzyme activity with copper being the most potent with an almost complete inhibition of enzyme activity observed

Visualization of the stingless bee research in Southeast Asia region through Bibliometric analysis using Scopus database from 1984 to 2022

The increasing activity of meliponiculture which plays a role as a natural agricultural pollinator as well as the production of stingless bee honey over time has encouraged high-impact research efforts around the world. Stingless bee honey is well known as a "superfood" product and has received significant attention due to its various applications such as the treatment of various diseases both traditionally and clinically. In this context, understanding interesting topics and expanding the network of collaborations is desirable to advance research towards integrated efforts, moreover, the Southeast Asia region (SEA) is one of the major revenue contributors to the global market, especially stingless bees. The purpose of this paper is to evaluate the research literature on stingless bee honey in the SEA region by conducting a bibliometric analysis of research papers in the Scopus database. A total of 543 journal articles published between 1984–2022 were obtained. The results have shown that since 2008, the average number of publications has increased by 35 articles per year, resulting in a steady increase in the number of publications accumulated until 2022. Only six countries are listed and almost 60% of total SEA publications are contributed by researchers from Malaysia, followed by Indonesia and Thailand which contribute 21% and 15%, respectively. In addition, among the top 10 most productive affiliates from every country in SEA, seven are universities in Malaysia, while Indonesia and Thailand have only one. The intellectual structure of research on stingless honey has been studied to offer a basic insight into the latest developments in this field of research, which will provide researchers and academics with broad guidelines for conducting further research in related fields

Frequency dependence of electroluminescence measurement in LDPE

A good insulator for high voltage cable has low dielectric loss, reasonable flexibility and thermo-mechanically stable. However, prolonged application of electrical stresses on the cable will degraded the cable; physically and morphologically. Electrical degradation in high voltage cable can be detected using electroluminescence (EL) method. Electroluminescence is a phenomenon that occurs when the atoms of a material are being excited due to the application of and external high electrical stresses. There are several external factors that affect the behaviour of electroluminescence emission such as, applied voltage, applied frequency, ageing of material and types of materials. In this paper, the EL measurement is employed to determine the effect of applied frequency on virgin LDPE at fixed and varying applied voltage. It can be observed that EL emission increases as applied frequency increases with increasing voltage applied. However, interesting EL behaviour is observed when varying frequency is applied from 10 Hz to 100 Hz

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030