Energy Efficiency of the Vulcanization Process of a Bicycle Tyre

The production of tyres is one of the most energy consuming manufacturing activities in the rubber sector. In the production cycle of a tyre, the curing operation has the maximum energy loss. This is mostly due to the extensive use of steam as a source of heat and pressure in the vulcanization process. To the author’s knowledge, no scientific work is available in the literature where the energy efficiency of a tyre vulcanization press is estimated by means of a comprehensive model of all main components, including the moulds, the press with its heated plates, the bladder and, of course, the tyre. The present work aims at filling this gap. First, the press used for developing the model is described, along with its components and its typical product, a bicycle tyre. The instruments used for measuring flow rates, temperatures and pressures are also listed. Then, a numerical model is presented, that predicts the energy transfers occurring in the vulcanization press during a full process cycle. The numerical model, developed with the software Simcenter Amesim 2021.1, has been validated by means of measurements taken at the press. The results indicate that the amount of energy which is actually consumed by the tyre for its reticulation process amounts to less than 1% of the total energy expenditure. The paper demonstrates that the tyre industry is in urgent need of an electrification conversion of the traditional steam-based processes

BREATH HOLDING TIME AND OXYGEN SATURATION IN COVID AFFECTED NURSING STUDENTS-A COMPARATIVE STUDY

Objective: The present study is based on a novel approach of validated breath-holding technique and efficiency of SpO2 in the adverse COVID-19 outcomes and comparison with normal subjects. Methods: It is a prospective observational study conducted in residential/private nursing colleges, St. Luke’s School and College of Nursing and Smt. Vijaya Luke’s College of Nursing, Visakhapatnam during the period July 2021. Fifty-three student nurses affected with mild COVID-19, 35 student nurses affected with moderate COVID-19, aged 18–23 years were enrolled after taking thorough history about COVID-19 that is after 2 months of complete recovery. They were classified based on the symptom history in which the subjects without symptoms or mild symptoms were taken as mildly affected, whereas subjects with severe symptoms with mild fluctuations in SpO2 who didn’t require hospitalization were classified as moderately affected. The study included 109 normal control cases who are never affected with COVID-19 viral infection. In all the subjects, the oxygen saturation was measured using pulse oxymeter and their Breath holding times were also measured using standard protocols. Results: The mean value of BHT was significantly reduced from normal 16.7339±3.4 to 12.8571±5.1 (p<0.05) in moderate cases. When oxygen saturation levels were compared before and after the breath holding in normal, mild and moderate cases the results were significant. However, when the oxygen saturation levels were compared between normal and mild COVID-19 cases the values were insignificant (p=0.4) and at the same time when the oxygen saturation levels were compared between normal and moderate COVID-19 cases the values were significant (p=0.0001). Conclusion: According to the findings, breath-holding does not need greater energy expenditure or cardiac output, and it eliminates walking and the related contamination of bystanders as occurring with pulse oximeter. Breath holding time is a determinant of respiratory capacity, when used as parameter helps in assessing the progression of lung injury, it gives an idea about respiratory fitness especially in this COVID era. Breath holding time and fluctuations in SpO2 when used conjointly we can assess degree of lung damage so that further treatment such as the continuity of medication, practicing of breathing exercises with or without medical treatment can be planned. This simple non-invasive tool can be used for the self-assessment of improvement in post-Covid patients. Future validation studies validate this hypothesis, measurement of these basic, innovative surrogates requires minimum inventory (i.e., a means to record oximetry and a timing device) and could feasibly provide a useful way to evaluate risks of future deterioration under under-resourced conditions

The Two Dimensional Nanomaterials Functionalized with Antimicrobial Peptides as a Novel Strategy to Combat Biofilms and its Associated Infections

The resilient and adaptive nature of biofilms and its associated infections pose a serious threat in the current state of play aiming the need for a promising strategy. The two-dimensional nanomaterials functionalized with antimicrobial peptides serve as a novel approach to combat biofilms and their related infections. This review article explains the current landscape of research in this field focusing on classification and physiochemical properties of two-dimensional (2D) nanomaterials and their exploitation as antimicrobial peptide delivery system. The review also offers insights into their potential application in various settings such as medical devices wound healing and water treatment. Additionally we discuss the challenges and future directions in the development and implementation of this innovative strategy, emphasizing the need for multidisciplinary approach that bridges the gap between fundamental research and practical applications. Through a comprehensive synthesis of current literature, this review aims to provide researchers, clinicians and industry professionals with a thorough understanding of promises and challenges, which aim in the development of advanced materials and strategies for combating microbial biofilms and improving industrial control measures

SYNTHESIS OF BIO – DEGRADABLE BANANA NANOFIBERS

The present work includes the development of composites in nano based, reinforced with natural fibers. The fibers to be studied come from mechanical extraction from banana. The process, in general, consists of mechanical extraction. Further, the fibers are cut, classified in the adequate mesh and later on undergoes a chemical pulping process. The pulp is hydrolized and filtered, in order to produce nanofibers. A great deal of attention has been paid recently to cellulosic nanofibrillar structures as components in nanocomposites. Present paper is aimed for production of Nano Banana fibers using high energy ball milling method. Banana stem powder was soaked in sodium hypochlorite solution for 24 h at room temperature then ball milled at variable milling time to produce banana stem powder dispersions with variable particle size. The effect of ball milling time on the particle size and morphology of the banana stem powder particles was examined. Results showed the mean particle size of the banana stem powder reduced progressively with milling time. The size of chemically treated fibers is reduced down to Nano crystalline level by high energy ball milling. Wet ball milling was carried out for the production of Banana Nano fibers. Wet milling with toluene as medium was carried out for different milling hours viz. 20, 40, 60 and 80 hours. The nanofibers are characterized by X-ray diffraction to measures the crystallinity

An observing system simulation experiment for Indian Ocean surface pCO2 measurements

An observing system simulation experiment (OSSE) is conducted to identify potential locations for making surface ocean pCO2 measurements in the Indian Ocean using the Bayesian Inversion method. As of the SOCATv3 release, the pCO2 data is limited in the Indian Ocean. To improve our modeling of this region, we need to identify where and what observation systems would produce the most good or benefit for their cost. The potential benefits of installing pCO2 sensors in the existing RAMA and OMNI moorings of the Indian Ocean, the potential of Bio-Argo floats (with pH measurements), and the implementation of the ship of opportunity program (SOOP) for underway sampling of pCO2 are evaluated. A cost function of dissolved inorganic carbon as a model state vector and CO2 flux mismatch as the source of error is minimized, and the basin-wide CO2 flux uncertainty reduction is estimated for different seasons. The maximum flux uncertainty reduction achievable by installing pCO2 sensors in the existing RAMA and OMNI moorings is limited to 30% during different seasons. One may consider that around 20 Bio-Argos are still the right choice over installing mooring based pCO2 sensors and achieve uncertainty reduction up to 50% with additional benefit of profiling the sub-surface upto 1000 & ndash;2000 m. However, a single track SOOP has the potential to reduce the uncertainty by approximately 62%. This study identifies vital RAMA and OMNI moorings and SOOP tracks for observing Indian Ocean pCO2. Plain Language Summary. Surface ocean partial pressure of CO2 (pCO2) information is vital for estimating sea-to-air CO2 exchanges. This parameter is least available from the Indian Ocean as compared to other global tropical and southern oceans. There has been no effort made so far to measure surface ocean pCO2 in the Indian Ocean with routine monitoring such as by mounting instruments to moorings or by underway sampling via any ship of opportunity program. Therefore there is a considerable demand to start pCO2 observations in the Indian Ocean. However, one key question that emerges is where to deploy pCO2 instruments in the Indian Ocean to learn the most with limited resources. This study addresses this question with inverse modeling techniques. The study finds that the existing moorings of the Indian Ocean are capable of hosting pCO2 sensors, and data from those are useful to reduce the uncertainty in the surface sea-to-air CO2 flux estimation by a quarter magnitude. In contrast, the Bio-Argo floats with pH sensors, and the ship of opportunity underway sampling of pCO2 may benefit from reducing the same up to 50% and 62%, respectively

Biological production in the Indian Ocean upwelling zones – Part 1: refined estimation via the use of a variable compensation depth in ocean carbon models

Biological modelling approach adopted by the Ocean Carbon-Cycle Model Intercomparison Project (OCMIP-II) provided amazingly simple but surprisingly accurate rendition of the annual mean carbon cycle for the global ocean. Nonetheless, OCMIP models are known to have seasonal biases which are typically attributed to their bulk parameterisation of compensation depth. Utilising the criteria of surface Chl a-based attenuation of solar radiation and the minimum solar radiation required for production, we have proposed a new parameterisation for a spatially and temporally varying compensation depth which captures the seasonality in the production zone reasonably well. This new parameterisation is shown to improve the seasonality of CO2 fluxes, surface ocean pCO2, biological export and new production in the major upwelling zones of the Indian Ocean. The seasonally varying compensation depth enriches the nutrient concentration in the upper ocean yielding more faithful biological exports which in turn leads to accurate seasonality in the carbon cycle. The export production strengthens by  ∼ 70 % over the western Arabian Sea during the monsoon period and achieves a good balance between export and new production in the model. This underscores the importance of having a seasonal balance in the model export and new productions for a better representation of the seasonality of the carbon cycle over upwelling regions. The study also implies that both the biological and solubility pumps play an important role in the Indian Ocean upwelling zones

Screening COVID-19 by Swaasa AI platform using cough sounds: a cross-sectional study

Abstract The Advent of Artificial Intelligence (AI) has led to the use of auditory data for detecting various diseases, including COVID-19. SARS-CoV-2 infection has claimed more than six million lives to date and therefore, needs a robust screening technique to control the disease spread. In the present study we created and validated the Swaasa AI platform, which uses the signature cough sound and symptoms presented by patients to screen and prioritize COVID-19 patients. We collected cough data from 234 COVID-19 suspects to validate our Convolutional Neural Network (CNN) architecture and Feedforward Artificial Neural Network (FFANN) (tabular features) based algorithm. The final output from both models was combined to predict the likelihood of having the disease. During the clinical validation phase, our model showed a 75.54% accuracy rate in detecting the likely presence of COVID-19, with 95.45% sensitivity and 73.46% specificity. We conducted pilot testing on 183 presumptive COVID subjects, of which 58 were truly COVID-19 positive, resulting in a Positive Predictive Value of 70.73%. Due to the high cost and technical expertise required for currently available rapid screening methods, there is a need for a cost-effective and remote monitoring tool that can serve as a preliminary screening method for potential COVID-19 subjects. Therefore, Swaasa would be highly beneficial in detecting the disease and could have a significant impact in reducing its spread

Diagnosis and Treatment of Incident Hypertension Among Patients with Diabetes: a U.S. Multi-Disciplinary Group Practice Observational Study

BACKGROUND: Early hypertension control reduces the risk of cardiovascular complications among patients with diabetes mellitus. There is a need to improve hypertension management among patients with diabetes mellitus. OBJECTIVE: We aimed to evaluate rates and associations of hypertension diagnosis and treatment among patients with diabetes mellitus and incident hypertension. DESIGN: This was a 4-year retrospective analysis of electronic health records. PARTICIPANTS: Adults ≥18 years old (n = 771) with diabetes mellitus, who met criteria for incident hypertension and received primary care at a large, Midwestern academic group practice from 2008 to 2011 were included MAIN MEASURES: Cut-points of 130/80 and 140/90 mmHg were used to identify incident cases of hypertension. Kaplan-Meier analysis estimated the probability of receiving: 1) an initial hypertension diagnosis and 2) antihypertensive medication at specific time points. Cox proportional-hazard frailty models (HR; 95 % CI) were fit to identify associations of time to hypertension diagnosis and treatment. KEY RESULTS: Among patients with diabetes mellitus who met clinical criteria for hypertension, 41 % received a diagnosis and 37 % received medication using the 130/80 mmHg cut-point. At the 140/90 mmHg cut-point, 52 % received a diagnosis and 49 % received medication. Atrial fibrillation (HR 2.18; 1.21–4.67) was associated with faster diagnosis rates; peripheral vascular disease (HR 0.18; 0.04–0.74) and fewer primary care visits (HR 0.93; 0.88–0.98) were associated with slower diagnosis rates. Atrial fibrillation (HR 3.07; 1.39–6.74) and ischemic heart disease/congestive heart failure (HR 2.16; 1.24–3.76) were associated with faster treatment rates; peripheral vascular disease (HR 0.16; 0.04–0.64) and fewer visits (HR 0.93; 0.88–0.98) predicted slower medication initiation. Diagnosis and treatment of incident hypertension were similar using cut-points of 130/80 and 140/90 mmHg. CONCLUSIONS: Among patients with diabetes mellitus, even using a cut-point of 140/90 mmHg, approximately 50 % remained undiagnosed and untreated for hypertension. Future interventions should target patients with multiple comorbidities to improve hypertension and diabetes clinical care