Evaluating the suitability of Adansonia digitata fruit pulp for the production of yoghurt

The potentials of neglected and under-utilized plant species (NUS) to enhance food security and safety has been highlighted in recent years. NUS have the potential to fight malnutrition and improve human health particularly in Africa. Despite their potentials, there is still a huge  knowledge gap as to their potential effect when used to fortify foods. This research was conducted to evaluate the suitability of Adansonia digitata fruit pulp for yoghurt production using different mixtures of milk and A. digitata fruit pulp powder in ratios of 4:1, 3:2, 2:3, 1:4 and 5:0. Proximate and mineral content analysis was conducted using the AOAC method. Sensorial analysis was done and the outcome informed the choice of  samples analysed for volatile compounds profile by GC-MS analysis of the chloroform extract. The proximate composition of the yoghurt samples increased with the addition of A. digitata pulp powder and the results  showed that the ratio of 2:3 had highest lipid content (5.5%) and fiber, 1:4 had highest protein content (5.65%) while commercial yoghurt had trace ash and no fiber. Calcium content was highest in the mixture; 2:3 and 4:1 (0.5 mg/kg), 2:3 had highest magnesium content (0.8 mg/kg) and  potassium content was highest in 4:1 (1250 mg/kg) respectively. Gas chromatography and mass spectroscopy (GC-MS) analysis revealed that 2:3 mixture had  eleven (11) volatile metabolites, 1:4 had (9) while plain powder also had (9) volatile metabolites. This study shows that  incorporation of A. digitata fruit pulp increased the bioavailability of  nutrients, minerals and a volatile metabolite with medicinal properties. The fortification of yoghurt in the ratio of 2:3 A. digitatato milk is suitable and could lead to reduction in yoghurt price and create job.Keywords: Adansonia, GC-MS, volatile metabolites, yoghurt

Challenges in QCD matter physics --The scientific programme of the Compressed Baryonic Matter experiment at FAIR

Substantial experimental and theoretical efforts worldwide are devoted to explore the phase diagram of strongly interacting matter. At LHC and top RHIC energies, QCD matter is studied at very high temperatures and nearly vanishing net-baryon densities. There is evidence that a Quark-Gluon-Plasma (QGP) was created at experiments at RHIC and LHC. The transition from the QGP back to the hadron gas is found to be a smooth cross over. For larger net-baryon densities and lower temperatures, it is expected that the QCD phase diagram exhibits a rich structure, such as a first-order phase transition between hadronic and partonic matter which terminates in a critical point, or exotic phases like quarkyonic matter. The discovery of these landmarks would be a breakthrough in our understanding of the strong interaction and is therefore in the focus of various high-energy heavy-ion research programs. The Compressed Baryonic Matter (CBM) experiment at FAIR will play a unique role in the exploration of the QCD phase diagram in the region of high net-baryon densities, because it is designed to run at unprecedented interaction rates. High-rate operation is the key prerequisite for high-precision measurements of multi-differential observables and of rare diagnostic probes which are sensitive to the dense phase of the nuclear fireball. The goal of the CBM experiment at SIS100 (sNN= 2.7--4.9 GeV) is to discover fundamental properties of QCD matter: the phase structure at large baryon-chemical potentials (μB> 500 MeV), effects of chiral symmetry, and the equation of state at high density as it is expected to occur in the core of neutron stars. In this article, we review the motivation for and the physics programme of CBM, including activities before the start of data taking in 2024, in the context of the worldwide efforts to explore high-density QCD matter

Using Radial Shock Wave Therapy to Control Cerebral Palsy-Related Dysfunctions: A Randomized Controlled Trial [Letter]

Sumyia Mehrin Omar, Aboma Zewude Abdissa, Maryam Mohammed Bashir Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab EmiratesCorrespondence: Maryam Mohammed Bashir, Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates, Email [email protected]

Impact of managerial skills and ties on business model innovation: the role of exploitative and explorative learning

Purpose: Research in the area of business model innovation (BMI) has focused on theoretical and exploratory discussions, thereby creating a lack of empirical evidence on the role of top management in BMI. The current study focuses on this research gap and provides empirical evidence by studying the impact of top managers’ managerial skills, managerial ties and entrepreneurial skills on BMI. It also seeks to explore the mediating influence of explorative and exploitative learning. Design/methodology/approach: Data were collected from 200 respondents from top multinational firms in India covering six sectors, which was analyzed using structural equation modeling. Findings: The findings reveal significant positive relationships of BMI with managerial skills, entrepreneur skills and managerial ties, and these relationships are found to be mediated by exploitative and explorative learning. Practical implications: Given the increasing importance of BMI to organizational success, the study has highlighted that top managers’ skills and ties favorably influence BMI. Organizations can make related investments in training and capacity building by instituting appropriate programs in their organizations. In addition, organizations can exercise caution during recruitment by recruiting and selecting managers in top management teams who excel in managerial skills. Originality/value: This study is one of the few to validate a comprehensive measurement model that highlights the influence of managerial skills, entrepreneur skills and managerial ties on BMI, explaining these associations with the mediating role of exploitative and explorative learning

Identifying COVID-19 survivors living with post-traumatic stress disorder through machine learning on Twitter

The COVID-19 pandemic has disrupted people’s lives and caused significant economic damage around the world, but its impact on people’s mental health has not been paid due attention by the research community. According to anecdotal data, the pandemic has raised serious concerns related to mental health among the masses. However, no systematic investigations have been conducted previously on mental health monitoring and, in particular, detection of post-traumatic stress disorder (PTSD). The goal of this study is to use classical machine learning approaches to classify tweets into COVID-PTSD positive or negative categories. To this end, we employed various Machine Learning (ML) classifiers, to segregate the psychotic difficulties with the user’s PTSD in the context of COVID-19, including Random Forest Support Vector Machine, Naïve Bayes, and K-Nearest Neighbor. ML models are trained and tested using various combinations of feature selection strategies to get the best possible combination. Based on our experimentation on real-world dataset, we demonstrate our model’s effectiveness to perform classification with an accuracy of 83.29% using Support Vector Machine as classifier and unigram as a feature pattern

Estimation of entrance surface dose to adult patients undergoing plain chest radiographic examinations in a Northern Nigerian population.

Objective: The entrance surface doses (ESD) to adult patients undergoing postero-anterior (PA) chest radiography were measured at Shika Ahmedu Bello University Teaching Hospital (ABUTH) Zaria, Northern Nigeria. Method:A total of 30 patients were prospectively considered in the study. The ESDs were obtained using thermo luminescence dosimeter (TLDs) chips, and Kumar's formula. Results: The estimated ESD obtained were 1.08 mGy and 0.76 mGy for TLD chips readings and Kumar's formula respectively. Comparison was made between the two readings, and a statistically significant difference was noted (p<0.029). Conclusion: Procedural changes are suggested in order to lower the ESD and enhance the image quality of the radiographs. ESDs in this study were found to be generally higher compared with those reported in similar studies in Southern Nigeria, UK, and CEC. The results call for improved operators technique and application of quality Assurance Programme (QAP) in radiology departments, to ensure that doses are kept as low as reasonably achievable, and also for the formulation of local diagnostic reference levels (LDRL)

Mitigation of bio-corrosion characteristics of coronary artery stent by optimising fs-laser micromachining parameters.

Cardiovascular diseases, particularly coronary artery disease, pose big challenges to human life. Deployment of the stent is a preferable treatment for the above-mentioned disease. However, stents are usually made up of shape memory alloy called Nitinol. The poorer surface finish on the machined nitinol stents accelerates the migration of Nickel ions from the implanted nitinol stent, which is considered toxic and can lead to stenosis. The current study deals with controlling surface quality by minimising surface roughness and improving corrosion resistance. Femtosecond laser (fs-laser 10-15 s) micromachining was employed to machine the Nitinol surface to achieve sub-micron surface roughness. The Grey relational analysis (GRA)-coupled design of the experimental technique was implemented to determine optimal levels of four micromachining parameters (laser power, pulse frequency, scanning speed, and scanning pattern) varied at three levels to achieve minimum surface roughness and to maximise the volume ablation. The results show that to yield minimum surface roughness and maximum volume ablation, laser power and scanning speed are in a higher range. In contrast, the pulse frequency is lower, and the scanning pattern is in a zig-zag manner. ANOVA results manifest that scanning speed is the predominant factor in minimising surface roughness, followed by pulse frequency. Furthermore, the corrosion behaviour of the machined nitinol specimens was evaluated, and the results show that specimens with lower surface roughness had lower corrosion rates

Biocrude from hydrothermal liquefaction of indigenous municipal solid waste for green energy generation and contribution towards circular economy: A case study of urban Pakistan.

In this study, biocrude was successfully produced by the hydrothermal liquefaction of municipal solid waste collected from the landfill site of Lahore, the capital of Punjab, Pakistan, boasting a population of 12 million and an annual waste collection of 10 million tons. The hydrothermal liquefaction process was performed at reaction parameters of 350 °C and 165 bars with 15 min of residence time. The solid waste was found to have 78 % dry matter, 22 % moisture contents, 22.2 % ash, 22.69 MJ/kg higher heating value, 52.062 % C, 8.007 % H, 0.764 % N, and 39.164 % O. Non-catalytic process only produced 10.57 % oil, however when using the catalytic process, the biocrude yield improved to 17.61 %, with 22.61 % energy recovery for biocrude and 12.14 % for solids, when using 2 g dose of K2CO3. The resultant biocrude has a 28.61 MJ/kg higher heating value, having 60.28 % C and 9.28 % H. In contrast, the aqueous phase generated had 4.43 pH, 71.5 g/L TOC, and 1.35 g/L Total Nitrogen. TGA indicated that biocrude contains approximately 80 % of volatile fractions of different fuels. The organic compounds having the six highest peak areas in GC-MS were Ethyl ether 25.74 %, 2-pentanone, 4-hydroxy-4-methyl 9.08 %, 2-propanone, 1,1-dimethoxy 5.62 %, Silane, dimethyl (docosyloxy) butoxy 5.08 %, 1-Hexanol, 2-ethyl 4.53 %, and. Phenol 4.07 %. This work makes the first-ever successful use of indigenous solid waste from a landfill dumping site in Lahore to successfully produce useful biocrude with aims of waste reduction and management, circular economy, and energy recovery

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication