Carbon dioxide is one of the leading contributors to global warming. Oxy-fuel combustion (OFC) integrated with carbon capture and storage (CCS) technology is an efficient way to reduce carbon dioxide emissions. In OFC, pure oxygen (O2) is used instead of air to react with hydrocarbon fuel. Consequently, the products of combustion mainly include carbon dioxide (CO2) and water vapor (H2O) under lean conditions. Meanwhile, due to the absence of N2 in the intake charge, nitrogen-related emissions such as NOx are greatly removed from the exhaust gases. In the present study, the effect of intake charge temperature on OFC has been investigated in a diesel engine under the homogeneous charge compression ignition (HCCI) mode. In order to control combustion temperature and avoid overheating problems caused by oxygen in OFC, a portion of the exhaust CO2 was added to the O2. For this purpose, different CO2 dilutions ranging from 79-85% have been employed. It has been found that OFC can significantly reduce CO and particulate matter (PM) emissions while eliminating NOx emissions. With a higher intake charge temperature, combustion occurs earlier with shorter main stages, reducing the indicated mean effective pressure (IMEP) and increasing the indicated specific fuel consumption (ISFC), whereas, with a lower intake charge temperature, combustion stability deteriorates leading to incomplete OFC. By raising the intake charge temperature from 140 C to 220 C and applying 21% O2 and 79% CO2 v/v, the indicated thermal efficiency (ITE) is reduced from 34.6% to 29.2% while ISFC is increased from 0.24 to 0.285 Kg/kWh.

Human milk is the biological norm for newborn nutrition, with breast milk from the mother being recognized as the best source of nutrition for infant health. When the mother’s milk is unavailable, donor human milk is the best alternative for infants with low birthweights. Growing recognition of the benefits of donor human milk has led to increasing global interest in monitoring and controlling human milk’s quality to fulfil the need for donor human milk. In response to this need, the REAMIT project proposed to adapt and apply existing innovative technology to continuously monitor and record human milk quality and signal potential milk quality issues. IoT sensors and big data technology have been used to monitor conditions that may increase spoilage (such as temperature and humidity) in the transportation stage. The sensors were installed in the insulated bags used to transport the milk from the donor’s home or hospital to the human milk bank and vice versa. The temperature and humidity were collected every 30 min, whilst the GPS locator sent data every 2 min. The data are collected in the cloud using GPRS/CAT-M1 technology. An algorithm was designed to send alerts when the milk temperature is above the prespecified threshold specified by the organisation, i.e., above −20 °C. The experience showed evidence that IoT sensors can efficiently be used to monitor and maintain quality in supply chains of high-quality human milk. This rare product needs a high level of quality control, which is possible with the support of smart technologies. The IoT technology used can help the human milk supply chain in five different aspects, namely by reducing waste, assuring quality, improving availability, reducing cost and improving sustainability. This system could be extended to various supply chains of rare and precious commodities, including further medical supplies such as human blood and organs, to completely avoid waste and ensure total quality in supply chains.

Each individual has a unique gut microbiota; therefore, the genes in our microbiome outnumber the genes in our genome by about 150 to 1. Perturbation in host nutritional status influences gut microbiome composition and vice versa. The gut microbiome can help in producing vitamins, hormones, and other active metabolites that support the immune system; harvest energy from food; aid in digestion; protect against pathogens; improve gut transit and function; send signals to the brain and other organs; oscillate the circadian rhythm; and coordinate with the host metabolism through multiple cellular pathways. Gut microbiota can be influenced by host genetics, medications, diet, and lifestyle factors from preterm to aging. Aligning with precision nutrition, identifying a personalized microbiome mandates the provision of the right nutrients at the right time to the right patient. Thus, before prescribing a personalized treatment, it is crucial to monitor and count the gut flora as a focused biomarker. Many nutritional approaches that have been developed help in maintaining and restoring an optimal microbiome such as specific diet therapy, nutrition interventions, and customized eating patterns. One of these approaches is time-restricted feeding/eating (TRF/E), a type of intermittent fasting (IF) in which a subject abstains from food intake for a specific time window. Such a dietary modification might alter and restore the gut microbiome for proper alignment of cellular and molecular pathways throughout the lifespan. In this review, we have highlighted that the gut microbiota would be a targeted biomarker and TRF/E would be a targeted approach for restoring the gut-microbiome-associated molecular pathways such as hormonal signaling, the circadian system, metabolic regulators, neural responses, and immune-inflammatory pathways. Consequently, modulation of the gut microbiota through TRF/E could contribute to proper utilization and availability of the nutrients and in this way confer protection against diseases for harnessing personalized nutrition approaches to improve human health.

Background Mindsets are based on two basic assumptions: some people think that their intellectual abilities can be developed through hard work and instruction (i.e., a growth mindset), whereas others believe that nothing can change their level of intellectual ability (i.e., a fixed mindset). The association between mindsets and academic achievement has been examined in different academic subjects, such as biology and math. However, no previous study has examined the effects of language learning mindsets (LLMs) and math mindsets (MMs) on academic success in an English medium instruction (EMI) setting in which English, rather than the first language of the students, is used for teaching content (e.g., mechatronics engineering). Purpose/Hypothesis This study explores the relationship between Turkish mechatronics engineering undergraduate students' domain-specific mindsets, LLMs and MMs, and their academic success. Design/Method Student test scores for English medium and first-language medium courses were collected from fourth-year students studying mechatronics engineering (n = 68) at a public university in Turkey. Students also completed the LLM and MM inventories. Results Regression analyses revealed that growth LLM and MM were positive predictors of EMI and Turkish medium of instruction (TMI) academic success, whereas fixed LLM and MM were negative predictors of EMI and TMI academic success. Conclusions In both EMI and TMI courses, a growth mindset in math and language learning can profoundly predict students' academic achievement in a mechatronics engineering program. We argue that domain-specific mindsets can effectively explain the self-theories of intelligence and achievement.

The aim of this study was to determine the appetite-related responses to breaking up prolonged sitting with physical activity bouts differing in frequency and duration among adult females. Fourteen sedentary females aged 34 ± 13 years with a body mass index of 27.1 ± 6.3 kg/m2 (mean ± SD) took part in a randomised crossover trial with three, 7.5 h conditions: (1) uninterrupted sitting (SIT), (2) sitting with short frequent 2-min moderate-intensity walking breaks every 30 min (SHORT-BREAKS), and (3) sitting with longer duration, less frequent 10-min moderate-intensity walking breaks every 170–180 min (LONG-BREAKS). The intensity and total duration of physical activity was matched between the SHORT-BREAKS and LONG-BREAKS conditions. Linear mixed models were used to compare the outcomes between conditions with significance being accepted as p ≤ 0.05. There were no significant between-condition differences in hunger, satisfaction, prospective food consumption or overall appetite area under the curve (AUC) (all p ≥ 0.801). Absolute ad libitum energy intake and relative energy intake (REI) did not differ significantly between conditions (all p ≥ 0.420). Acylated ghrelin and total peptide YY incremental and total AUC did not differ significantly between conditions (all p ≥ 0.388). Yet, there was a medium effect size for the higher acylated ghrelin incremental AUC in SHORT-BREAKS versus SIT (d = 0.61); the reverse was seen for total AUC, which was lower in SHORT-BREAKS versus SIT (d = 0.69). These findings suggest that breaking up sitting does not lead to compensatory changes in appetite, appetite hormones or energy intake regardless of physical activity bout duration and frequency among adult females.

Background Sarcopenia is a progressive and generalised loss of muscle mass and function with advancing age and is a major contributor to frailty. These conditions lead to functional disability, loss of independence, and lower quality of life. Sedentary behaviour is adversely associated with sarcopenia and frailty. Reducing and breaking up sitting should thus be explored as an intervention target for their management. The primary aim of this study, therefore, is to examine the feasibility, safety, and acceptability of conducting a randomised controlled trial (RCT) that evaluates a remotely delivered intervention to improve sarcopenia and independent living via reducing and breaking up sitting in frail older adults. Methods This mixed-methods randomised controlled feasibility trial will recruit 60 community-dwelling older adults aged ≥ 65 years with very mild or mild frailty. After baseline measures, participants will be randomised to receive the Frail-LESS (LEss Sitting and Sarcopenia in Frail older adults) intervention or serve as controls (usual care) for 6 months. Frail-LESS is a remotely delivered intervention comprising of tailored feedback on sitting, information on the health risks of excess sitting, supported goal setting and action planning, a wearable device that tracks inactive time and provides alerts to move, health coaching, and peer support. Feasibility will be assessed in terms of recruitment, retention, and data completion rates. A process evaluation will assess intervention acceptability, safety, and fidelity of the trial. The following measures will be taken at baseline, 3 months, and 6 months: sitting, standing, and stepping using a thigh-worn activPAL4 device, sarcopenia (via hand grip strength, muscle mass, and physical function), mood, wellbeing, and quality of life. Discussion This study will determine the feasibility, safety, and acceptability of evaluating a remote intervention to reduce and break up sitting to support improvements in sarcopenia and independent living in frail older adults. A future definitive RCT to determine intervention effectiveness will be informed by the study findings.

Depleting terrestrial deposits and rising demand for metals in this time of climate change are stimulating interest in the deep sea — the area of the ocean below 200m — with commercial mining of mineral deposits imminent. Environmental impact assessments, effective regulation and mitigation strategies are needed to limit the impacts of deep-sea mining. This is a potential catastrophe for marine biodiversity, and use of Big Data will be needed to follow mining activities as well as chart impacts on known and unknown marine species and their habitats.

Safety training enhances hazard awareness in the construction industry. Its effectiveness is a component of occupational safety and health. While face-to-face safety training has dominated in the past, the frequent lockdowns during COVID-19 have led us to rethink new solutions. A chatbot is messaging software that allows people to interact, obtain answers, and handle sales and inquiries through a computer algorithm. While chatbots have been used for language education, no study has investigated their usefulness for hazard awareness enhancement after chatbot training. In this regard, we developed four Telegram chatbots for construction safety training and designed the experiment as the treatment factor. Previous researchers utilized eye-tracking in the laboratory for construction safety research; most have adopted it for qualitative analyses such as heat maps or gaze plots to study visual paths or search strategies via eye-trackers, which only studied the impact of one factor. Our research has utilized an artificial intelligence-based eye-tracking tool. As hazard awareness can be affected by several factors, we filled this research void using 2-way interaction terms using the design of experiment (DOE) model. We designed an eye-tracking experiment to study the impact of site experience, Telegram chatbot safety training, and task complexity on hazard awareness, which is the first of its kind. The results showed that Telegram chatbot training enhanced the hazard awareness of participants with less onsite experience and in less complex scenarios. Low-cost chatbot safety training could improve site workers’ danger awareness, but the design needs to be adjusted according to participants’ experience. Our results o􀀀er insights to construction safety managers in safety knowledge sharing and safety training.

Rugby union is a high-intensity invasion game characterised by contact events (most frequently the tackle and ruck). Success in key defining moments (i.e. tackle breaks, turnovers, scrums) in elite level rugby union is therefore largely dependent on technical characteristics, and physical qualities including strength and speed (1). Understanding changes in force characteristics across the full English professional rugby union season is therefore important for creating and monitoring strength and conditioning programmes. The aim of this study was to examine changes in force output, rate of force development (RFD), and jump performance across the full season in elite male English rugby union players.

with leg asymmetry linked to this injury occurrence. Screening for balance deficits is used as a predictor of potential injury; therefore the aim of this study was to determine whether static and dynamic balance differs in elite soccer players preferred kicking and nonpreferred kicking legs. Fifteen male professional soccer players were tested for static balance; standing on one leg, and dynamic balance, a hop and hold task and a kicking task. Balance ability was assessed by measuring centre of pressure deviation. Results indicated that static balance and hop and hold tests were not significantly different (p>0.05) when dominant and non-dominant kicking legs were compared. The kicking balance task indicated a significant increase (p≤0.05) in balance ability for the player’s nondominant limbs. Further, left sided players had significantly better (p≤0.05) dominant leg balance when compared to right sided players. These findings suggest that the static and dynamic balance tasks employed in this study were not specific enough to establish possible balance asymmetries in professional elite soccer players, while the passing dynamic balance test seems to be sensitive enough to show dominant and non-dominant leg discrepancies. It is therefore suggested that balance tasks, used to screen players, need to mimic the actions linked to injuries within soccer in order to explore dominant and non-dominant asymmetry.