Alarm Clock Research Articles

Optimization strategy of computer numerical control machining process parameters in biomanufacturing mold

With the rapid development of biomanufacturing technology in the medical and pharmaceutical fields, the demand for high-precision and high-quality molds has surged. When Computer numerical control (CNC) machining biomanufacturing molds, the optimization of process parameters becomes the key to improve efficiency and quality. The purpose of this study is to explore the optimization strategy of CNC machining process parameters to achieve the best surface quality, dimensional accuracy and machining efficiency. Through literature review, the spindle speed, feed speed and cutting depth are selected as the key parameters, and the multi-objective optimization model is constructed by response surface method, which is solved by genetic algorithm. The experiment shows that the process parameters of CNC system in mold manufacturing are cutting speed 100 (m/min), feed rate 0.2 (mm/rev) and cutting depth 0.5 (mm), which will effectively reduce the manufacturing cost, and effectively control the alarm times within 35 times in different processing equipment, greatly reduce the risk. The optimization strategy can significantly improve the surface quality and productivity of the mold and reduce the cost. The comparative analysis verifies the effectiveness of the method, which provides new theoretical and technical support for CNC machining in the field of biomanufacturing.

Experimental investigation of natural gas leakage and dispersion characteristics in utility tunnels under the effects of real facility layout and forced ventilation

Natural gas leakage occurring in underground utility tunnels usually poses a significant threat to public safety. In order to prevent unexpected fires and explosions, the evolution mechanism of natural gas leakage and dispersion in utility tunnels is urgently needed. In this study, an experimental apparatus was built to facilitate the understanding of leakage and dispersion dynamics in utility tunnels. Methane with a purity of 99.9% is used as a surrogate for natural gas. A schlieren imaging system with a Z-shaped optical path was designed to visualize the high-speed gas jet. The concentration distribution, alarm time, dilution efficiency, and gas jet image were analyzed under the effect of various facility layouts, ventilation, and leakage rates. The results show that the gas leakage and dispersion process can be divided into three zones: upwind zone, leak zone, and downwind zone, characterized by complicated airflow collision, high-speed get jets, and stable dilution dispersion respectively. Scenario analysis highlights the significance of key facilities, such as cable brackets, in experimental and numerical modeling due to their impact on dispersion trajectories. Higher ventilation rates prove beneficial in reducing peak concentration, hazardous areas, and enhancing purge efficiency. Conversely, higher leakage rates exacerbate the likelihood and severity of gas explosions. Alarm time exhibits a V-shaped distribution relative to the leak point, while purge time correlates positively with sensor positions. These findings are of practical importance in enhancing quantitative risk assessment and designing mitigation strategies for gas leakage accidents, which helps to improve the safety-risk-control capabilities of utility tunnels.

Wake-up with no pain: The Impact of Different Wake-up Ringtones on Awakening Status

The awakening process sets the tone for daily performance. Traditional alarm sounds like radar or sirens, are often abrupt and startling, which can trigger stress response and emotional problems. Existing research that focuses on human physiological indicators during arousal has not reached the impact of wake-up alarms. This study aims to apply photoplethysmographic (PPG) and electrodermal activity (EDA) sensors to meticulously assess the physical and emotional impact triggered by different alarm tones during wake-up process. Those includes human stress responses such as heart rate, EDA, and emotional state. We selected four type of alarm clock sounds, bird singing, ocean sound, radar sound and old telephone. Participants in this study will first put on EDA and PPG sensors before they take a quick sleep. Then, they will be awakened by either natural or harsh wake-up alarms without knowing it in advance. During the experiment, EDA and PPG sensors were used to monitor their physiological states and the data will be analyzed to identify stress patterns and trends. We specially focus on the sudden change when the alarm goes off and the recovery process followed by. The results indicate that participants awaken to harsh alarms had a more intense change in heart rate and emotional stress, while the signal in group of natural sounds was smoother. Our findings provide empirical evidence on the relationship between wake-up alarm sounds and stress responses. There is strong evidence(p-value<0.025) that arousal with more natural sounds causes less heart rate and emotional changes.

The interplay among sleep patterns, social habits, and environmental cues: insights from the Spanish population and implications for aligning daily rhythms.

The interplay among sleep patterns, social habits and environmental cues is becoming increasingly more important for public health and wellbeing due to its connection to circadian desynchronization. This paper explores said connections in Spain (which has an official and solar time mismatch), introducing the "Three Times Score" ‒which is based on questions widely used in the field‒ as a complementary tool for exploring the interplay of daily rhythms. The questionnaire covers sleep-related habits, social time, and environmental time. The study includes 9,947 participants (34.89 ± 12.15 y/o, mean ± SD; 5,561 women) from different Spanish regions. Sleep parameters were obtained for work and free days, as well as a modified version of the sleep-corrected midsleep on free days (MBFbc) and a parameter similar to social jet lag, both derived from bed time rather than sleep time. A number of indexes were computed to compare bed and work-related habits, together with natural light/dark cycle, along with the Three Times Score. Mixed-effect regression analysis was used to test whether the biological, social and environmental factors included in the study significantly predicted the sleep-related parameters: bedtime, wake-up time, time in bed and mid-bedtime. Temporal differences were found between work and free days, with waking-up occurring 2 h earlier on work days (7:10 ± 0:01) than on free days (9:15 ± 0:01). Bed times were 1 h earlier on work days (23:46 ± 0:01) than on free days (00:45 ± 0:01), whereas time in bed was over 1 h shorter on work (7 h 23 min) versus free (8 h 29 min) days. Strong correlations were found between work starting time and waking-up and bedtimes on workdays. Women went to bed earlier and woke up later, spending more time in bed. Differences in sleep habits were observed between work and free days across all age groups. The group of younger adults (18-30) reported going to bed later than older and younger groups, especially on free days. Adolescents and young adults also woke-up later than other age groups, especially on free days. Social jet lag (relative to bed time) and desynchronization indexes also varied with age, with younger adult participants exhibiting higher levels. Seasonal differences were limited, with minor variations between winter and summer. According to the multiple regression analysis, social (day type, work start time, alarm clock usage), biological (age, gender, in most cases related to sex) and environmental (sunset time) factors significantly contribute to predicting sleep/bed related schedules. This study provides insights into sleep habits in the Spanish population, introducing the Three Times Score as a complementary tool for exploring the interactions between sleep/bed-related habits, natural darkness and work-related schedules. Understanding this interplay is crucial for developing tailored interventions to improve sleep and wellbeing.

PROFILE OF PATIENTS WITH SLEEP COMPLAINTS IN A SECONDARY CARE HEALTH INSTITUTION IN THE CITY OF CAMPINAS, SÃO PAULO STATE

Objective: We report data of the profile of patients who sought our outpatient clinic for sleep disorders of the Faculty of Medicine of São Leopoldo Mandic Medical School, during the Week of Sleep, that took place in March, 2022. Methods: All participants responded to a form designed by the researcher, as well as to commonly used questionnaires in Sleep Research, such as the Epworth Sleepiness Scale (ESS), the Insomnia Severity Index (ISI), the Hospital Anxiety and Depression Scale, the STOP-BANG questionnaire for screening of apnea, and the WHO Quality of Life abbreviated questionnaire (WHOQOL-BREF). Results: 30 patients were evaluated, mean age 51.8 (± 14), 63% women. Main complaints were insomnia (63%), snore/apnea (23%) and excessive daytime sleepiness (10%). ESS scores were significantly higher among men, daytime nappers and alarm clock users. ISI scores were importantly associated with those who woke 2 or more times per night, while physically active, non-obese, normotensive people and those with Modified Mallampatti (MM) classes I and II scored significantly less in STOP-BANG. Obese, MM classes III-IV and people with abnormal cervical and abdominal circumferences performed markedly worse in Domain 1, while women, older people and alarm clock users went worse in Domain 4 of WHOQOL-BREF. Discussion: One or more sleep disturbances were detected in all seekers of Sleep Care, emphasizing the importance of these types of action.

8654 Real-World Performance Of The Medtronic Extended Infusion Set In The United States

Abstract Disclosure: T. Kwa: Employee; Self; Medtronic Minimed. G. Zhang: Employee; Self; Medtronic Minimed. J. Kiehl: Employee; Self; Medtronic Minimed. V. Putcha: Employee; Self; Medtronic Minimed. A. Patel: Employee; Self; Medtronic Minimed. S. Chattaraj: Employee; Self; Medtronic Minimed. O. Cohen: Employee; Self; Medtronic Minimed. R.A. Vigersky: Employee; Self; Medtronic Minimed. Real-World Performance of the Medtronic Extended Infusion Set in the United States Objective: The Medtronic extended infusion set (EIS) is the first and only infusion set approved for up to 7-day use and its pivotal trial established clinical safety and efficacy.[1] The purpose of this retrospective analysis was to assess real-world EIS performance and overall glycemic outcomes based on United States (US) data uploaded by MiniMed™ 770G system (MM770G) users at an aggregate level. Methods: Infusion set occlusion alarm events and time in (TIR, 70-180 mg/dL), below (TBR, <70 mg/dL) and above (TAR, >180 mg/dL) range of EIS-MM770G users (N=393) with >30-day device use in the U.S. were analyzed and compared against the data of a cohort of the same median age of 50 years (N=77219) using the MM770G with a standard 2/3-day infusion set (at an aggregate level). Results: EIS users experienced a lower occlusion alarm rate (median 0.011 alerts/patient day) compared to 0.016 alerts/patient day with the standard set (p = 0.005). TIR for EIS users was 69.4%, which was numerically greater than the 69.1% for standard set users (p = 0.258). While TAR was not significantly different (28.9% for EIS and 29.0% for standard set, p = 0.995), TBR was significantly lower (0.5% for EIS and 1.3% for standard set, p = 0.000). The difference in the total daily dose (TDD) of insulin between the two groups (53.0 units for EIS, 49.4 units for standard set) was not statistically significant (p = 0.961). Conclusion: Since the U.S. launch, the EIS has continued to perform similarly to the pivotal trial results and an early real-world analysis of EIS use outside of the US.2 The decreased burden of fewer set changes comes with a lower occlusion alarm rate and does not compromise time spent in target range.

7067 A Pilot Study on Levothyroxine Administration- Understanding the Effects on Thyroid Hormone Levels and Patient Compliance Without Restrictions on Food or Time

Abstract Disclosure: R. Patel: None. K. Pandya: None. D. Olson: None. Background- Hypothyroidism is one of the most common treatable endocrinological disorders that can be managed by replacement therapy. In most cases, compliance is a major hindrance for maintenance medications to express the intended effect. Thus, prescribing medications in a more convenient way would make it easier for the patients to remember and hence amplify compliance. Traditional practice dictates thyroid replacement medication to be administered early in the morning on an empty stomach for optimum absorption. This mandates some patients to set an alarm clock for early morning to take their thyroid medication, which can not just be cumbersome but also increase the chances of having a fall and can alter sleep hygiene as well. We aimed to identify if allowing patients with a more lenient approach in medication timing can help increase compliance while still maintaining thyroid hormone levels with fewer side effects. Methods- As an initial single-arm pilot study, we retrospectively looked at thirteen patients from a single center, for whom patient preference was respected in allowing them to take thyroid replacement in conjunction with any other medication, food, coffee, or any combination of those, as long as it was consistently taken the same way and at the same time each day. In this study, the patient population ranged in age from 44 to 95, with a mean age of 77.38. Most of these patients had follow-ups for over a decade while their TSH levels were observed with minimum follow-up duration being 4 years. Results- On the serial measurement of TSH on this patient cohort, it was discovered that patients were still euthyroid, ranging from 0.36 to 5.28 with a mean of 2.654. This euthyroid state was achieved without requiring any frequent monitoring or extraordinarily high doses of thyroid supplement hormones compared to patients following traditional measures for the same. The highest dose required to achieve Euthyroid status was no more than 125 mcg once/day without any major hormonal fluctuations or adverse events during their treatment course. Thus, indicating that the proposed amendment to thyroid replacement instructions did not negatively impact thyroid function Conclusion- Hence, we propose a more lenient approach to taking Thyroids supplements allowing the patients to take them more conveniently and hence improving the compliance, improving overall outcomes. This can primarily be applied to the elderly population, minimising potential harm, i.e., falls, and other limitations in an attempt to take it consistently. However, this will be further investigated through a clinical trial to gather more comprehensive data on outcomes as well as identify any potential limitations of this concept. Presentation: 6/2/2024

Modeling and assessment of hydrogen-blended natural gas releases from buried pipeline

Blending hydrogen into natural gas pipelines for transportation reduces costs but increases safety risks. The main objective of this work is to explore the evolution of leakage hazards in hydrogen-blended natural gas pipelines and quantify these risks. To achieve this, multi-stage coupling numerical models are developed to explore the leakage hazards in hydrogen-blended natural gas transportation. The results show that the proposed model accurately predicts leakage rates of hydrogen-blended natural gas pipelines in various soil types. The gas diffusion pattern shifts from spherical to hemispherical, with the hazardous volume increasing linearly overall. The influence of pressure on leakage is amplified in the soil, while the impact of the leakage aperture is diminished. Although increasing the hydrogen blending ratio reduces the leakage rate, it also enhances the hazard evolution. Burial depth primarily affects alarm time, while an increase in leakage angle within 90–180° significantly delays the hazard evolution. Moreover, higher soil resistance not only mitigates the leakage diffusion but also reduces the pressure differential. The leakage aperture exhibits the highest correlation with the hazard evolution.

IoT-Enabled Medication Reminder System with Alarm Delay Function

Medication compliance is essential to support the recovery of one's health. Prescribed medication for patients should be taken in accordance with the instructions, such as taking it after a meal, so patients should adhere to these guidelines for the medication to work optimally. Typically, medication reminder devices that have been designed continuously sound alarms until the user takes the medication. This allows users to meet the requirements before taking the medication, for example, having a meal if necessary. This medication reminder device is built with a snooze button that allows users to postpone the alarm so they can complete the necessary tasks before taking the medication. It also features LED lights to indicate the medication box that needs to be taken. The LCD displays real-time information, the next medication time, and the type of medication to be taken. The result of creating this device is that it can activate alarms according to the specified schedule and activate the LED lights corresponding to the medication box to be taken. The snooze function works when the snooze button is pressed and when the medication is not taken for 1 minute. After being postponed, the alarm will reactivate after 3 minutes. Additionally, notifications are also successfully sent to the Telegram application connected to the device. There is a delay of approximately 15-30 seconds when activating the alarm. Messages are sent to Telegram at three (3) times.

Improvements in daytime sleepiness and disrupted nighttime sleep with once-nightly sodium oxybate in people with narcolepsy type 1 and type 2: a plain language summary.

This is a plain language summary of a published article in the journal Sleep. Narcolepsy is a sleep condition that has 2 different subtypes: narcolepsy type 1 and narcolepsy type 2. These are called NT1 and NT2 for short. Sodium oxybate (SXB) is approved to treat excessive daytime sleepiness (EDS) and cataplexy. People with NT1 and NT2 both have EDS, but cataplexy is only present in people with NT1. Limited information is available about how SXB works in people with NT2. This is because previous trials have included only people with NT1 or people with unspecified narcolepsy. For more than 20years, the only available formulation of this medicine had to be given twice during the night. Many people with narcolepsy find that chronically waking up in the middle of the night for a second dose of SXB is disruptive to themselves or others in their household. People have also reported sleeping through alarm clocks, missing their second dose, and feeling worse the next day. Some people have accidentally taken the second dose too early, putting them at risk for serious adverse effects. These adverse effects may include slow breathing, low blood pressure, or sedation. The US Food and Drug Administration (FDA) approved a medicine called LUMRYZ™ (sodium oxybate) for extended-release oral suspension in May 2023. LUMRYZ is a once-nightly formulation of SXB (ON-SXB for short) and is taken as a single dose before bedtime. This medicine treats EDS and muscle weakness (also known as cataplexy) in people with narcolepsy. A clinical trial called REST-ON studied ON-SXB to find out if it was better at treating narcolepsy symptoms than a medicine with no active ingredients (placebo). This summary describes a study that tested whether ON-SXB was better than placebo at treating narcolepsy symptoms in people with NT1 or NT2. This study showed that compared to people who took placebo, people who took ON-SXB were able to stay awake longer during the day, felt less sleepy during the daytime, had less cataplexy, and had more improvements in their symptoms overall than people who took placebo. ON-SXB has been proven effective for people with NT1 or NT2. Unlike prior formulations of SXB, ON-SXB is taken once at bedtime, without requiring waking up in the middle of the night for a second dose.

Should we stop hitting the snooze button on wearable sleep technology?

Should we stop hitting the snooze button on wearable sleep technology?

Voltage fault diagnosis and prognostic of lithium-ion batteries in electric scooters based on hybrid neural network and multiple thresholds

Voltage fault diagnosis and prognostics of lithium-ion batteries (LIBs) are critical in ensuring their safe and reliable operation, and timely voltage prediction can help detect the oncoming fault of LIBs effectively. To this end, this study develops an efficient voltage fault diagnosis and prognostic method for LIBs based on voltage prediction and multiple thresholds. Firstly, a hybrid neural network integrating convolutional neural network and gated recurrent unit is established to extract both temporal and spatial features from the current operation data and predict voltage. Then, a residual calculator is devised to generate the voltage residuals, and the maximum voltage residuals of the fault-free data during charge and discharge operations are leveraged to constitute the multiple thresholds of fault diagnosis and prognostics strategy. The robustness, reliability and feasibility of voltage prediction are validated under the conditions of different driving scenarios, different dynamic temperature and real-world operation data. Moreover, the validation results on the fault electric scooter reveals that the proposed method can reliably diagnose the battery over-voltage and under-voltage faults and their alarm levels. Additionally, the warning moment by this method is at least 630s earlier than the alarm time in the battery management system, highlighting its efficient prognostic functionality.

Using the near real-time effective reproduction number rt as an early-warning tool for seasonal bronchiolitis and influenza-like illness epidemics.

Yearly bronchiolitis and influenza-like illness epidemics in France often involve high morbidity and mortality, which severely impacts healthcare. Epidemics are declared by the French National Institute of Public Health based on syndromic surveillance of primary care and emergency departments (ED), using statistics-based alarms. Although the effective reproduction number (Rt) is used to monitor the dynamics of epidemics, it has never been used as an early warning tool for bronchiolitis or influenza-like illness epidemics in France.We assessed whether Rt is useful for detecting seasonal epidemics by comparing it to the tool currently used (MASS) by epidemiologists to declare epidemic phases. We used anonymized ED syndromic data from the Île-de-France region in France from 2010 to 2022. We estimated Rt and compared the indication of accelerated transmission (Rt >1) to the MASS epidemic alarm time points. We computed the difference between those two time points, time to epidemic peak, and the daily cases documented at first indication and peak. Rt provided alarms for influenza-like illness and bronchiolitis epidemics that were, respectively, 6 days (IQR[4;8]) and 64 days (IQR[52;80]) - in median - earlier than the alarms provided by MASS. Rt detected earlier signals of bronchiolitis and influenza-like illness epidemics. Using this early-warning indicator in combination with others to declare an annual epidemic could provide opportunities to improve healthcare system readiness.

FPGA in hardware description language based digital clock alarm system with 24-hr format

Currently, digital clock adapts microprocessor or microcontroller system. Performance of speed and reconfigurability issue become a main concern in digital clocks. New additional feature may be introduced in digital clocks in the future. Field programmable gate array (FPGA) offer better performance of speed and reconfiguration features. Based on these advantages, it is essential to study or explore the digital clock with FPGA design. The objective in this study is to create a hardware description language (HDL)- based digital clock with alarm system and implement it onto the Altera DE2- 115 board. Using Verilog HDL language in Quartus Prime 20.1 Lite Edition software, all submodule components is developed and being test benched using ModelSim-Altera Starter Edition 13.1 to ensure the correct functionality. Then all inputs and outputs will be assigned through pin assignment in the software. For verification purpose, it will be downloaded to the Altera DE2-115 board. In conclusion, the file has been successfully implemented to the board and the digital clock with alarm is fully functional as expected. This was proved by the alarm signal, time adjustment and display of the three-display mode which is clock, alarm, and input where each mode carries their own functions as expected.

The impact of forced awakening on morning blood pressure surge

BackgroundPoor sleep quality can cause an increase in morning blood pressure surge (MBPS), an independent risk factor of cardiovascular disease (CVD) events. Awakening induced by external factors such as alarm clocks, may also contribute to increased MBPS. ObjectivesTo (1) compare the MBPS and sleep quality parameters between natural and forced awakenings and (2) examine the potential impact of forced awakening on MBPS, independent of sleep quality. MethodsThirty-two healthy adults participated in this pilot study, which included one night of natural awakening and one night of forced awakening (i.e., sleep was interrupted by an alarm after five hours). Objective and self-reported sleep quality parameters were measured using a multisensory wristband and sleep diaries, respectively, and beat-to-beat blood pressure variability was assessed using a continuous blood pressure monitor. Analyses included a paired t-test (objective 1) and linear mixed models (objective 2). ResultsParticipants predominantly consisted of young, healthy, and highly educated Asian adults. During the night of sleep with forced awakening, significantly higher MBPS, lower objective wakefulness after sleep onset, and lower self-reported sleep latency were observed, compared to the night with natural awakening. Forced awakening was significantly associated with increased MBPS after controlling for age, sex, mean arterial pressure, and sleep quality. ConclusionsForced awakening may significantly increase MBPS, consequently heightening the risk of CVD events. Study findings should be validated in a larger sample. Further research is also warranted to examine the impact of forced awakening on MBPS in individuals with CVD.

Sleep patterns and quality in university students: characteristics and associated factors

Background: Sleep is vital and influenced by factors such as age, lifestyle, and mental health. College students are always faced with challenges that negatively compromise their sleep and well-being. Objective: To evaluate sleep quality and associated factors among university students. Methods: This was a cross-sectional and quantitative study with 294 students from a public university in northeastern Brazil. Questionnaires on social and health characteristics, the Pittsburgh Sleep Quality Index, the Munich Chronotype Questionnaire, and the Perceived Stress Scale were used for data collection. Results: The study included 294 students with an average age of 21.5 years, 52.7% female, 43.7% from the health field, and 56% from the daytime shift. There was a prevalence of 76.5% of poor sleep quality, with the most impacted components being sleep latency, daytime dysfunction, sleep disturbances, and subjective sleep quality. The average sleep duration on school days was 416 min ± 88min, with 69.4% using an alarm clock. The students exhibited a slightly evening chronotype, correlating with greater social jetlag (r = 0.510; p < 0.001). Students who engaged in physical exercise had better sleep quality (7.9±3.5 vs 9.2±3.9; p = 0.005) and lower stress levels (22±6.1 vs 24.6±6.7; p < 0.001). Additionally, poor sleep quality was also correlated with higher stress (r = 0.326; p < 0.001) and eveningness (r = 0.244; p <0.01). Conclusion: The study highlights the high prevalence of poor sleep quality among university students, correlated with stress and eveningness. Physical exercise improves sleep quality and reduces stress, demonstrating its importance for student health.

Ultrastrong and Thermo‐Remoldable Lignin‐Based Polyurethane Foam Insulation with Active‐Passive Fire Resistance

AbstractFoam thermal insulators are indispensable for prevailing energy‐saving engineering, however their widespread use brings intractability such as unsustainability, “white pollution”, and fire hazards. The emergence of bio‐based foams is highly appreciated, but the fabrication approaches are economically unattractive and/or the product properties are inferior, making their large‐scale implementation unviable. Herein, a versatile, thermally remoldable phosphate‐containing polyurethane composite foam (LPU‐G) is constructed from natural lignin and expanded graphite flakes via an atmospheric pressure and scalable one‐pot strategy. The optimal LPU‐G exhibits exceptional mechanical strength, capable of supporting over 6000 times its weight without significant deformation. Moreover, the LPU‐G demonstrates the desired multifunctionality in handling extreme circumstances, including humidity‐tolerant thermal insulation, superb water vapor barrier, and withstanding ≈1200 °C flame without ignition. Based on the “expansion‐conductivity” micro‐mechanism, LPU‐G is the first foam material to be constructed as a sensitive fire alarm system with an ultra‐long alarm time (>1800 s). Surprisingly, LPU‐G can be rapidly upcycled into recyclable bulk composites for a second life through simple thermo‐molding processes rooted in the multi‐dynamic behavior of the phosphate, carbamate, and hydrogen bonds. The easy‐to‐scale LPU‐G represents a new generation of thermal insulators that address concerns regarding unsustainability, high cost, fire risk, and inferior mechanical properties.

Cotton induced graphene-like carbon tubes as electrodes for ultrahigh-energy–density supercapacitors

Developing a simple, cost-effective method to synthesize carbon tubes with unique physicochemical properties is of great value for energy storage/conversion applications. In this study, cotton-induced O, N-doped graphene-like hierarchically structured porous carbon tubes (CTOs) were fabricated through a facile method and used as a supercapacitor electrode. The CTOs possessed enhanced porosity, a unique pore structure, and a large specific surface area (3,345.4 m2 g−1), and the electrode demonstrated an ultrahigh specific capacitance of 428.2 F g−1 at 1.0 A g−1 and remarkable cycle stability (93.3 % after 10,000 cycles). Density functional theory calculations confirmed that the high-level O, N-doped graphene-like hierarchically porous structures increased ion transfer efficiency and conductivity. When NiCo2S4/CTOs and CTOs were used as the positive and negative electrodes, respectively, the asymmetric supercapacitors (NiCo2S4/CTOs//CTOs) exhibited an extremely high specific capacitance of 180.8 F g−1 and a maximum energy density of 64.3 Wh kg−1. Moreover, two serially connected NiCo2S4/CTOs//CTOs capacitors could power a 9 W alarm clock for 26 min. The proposed approach enables the facile synthesis of superior carbon tubes using long-staple cotton, offering potential energy storage and conversion.

Novel stochastic descriptors of a Markovian SIRD model for the assessment of the severity behind epidemic outbreaks

In contemporary epidemiology, it is of paramount importance to effectively evaluate epidemic occurrences by employing novel approaches that yield dependable predictions for the progression of widespread outbreaks. The present paper focuses on proposing novel stochastic descriptors based on a Markovian SIRD (susceptible-infected-recovered-deceased) epidemiological scheme that accounts for multiple re-infections. A continuous-time, three-dimensional Markovian process is employed tailored to the characteristics of the presented SIRD model. Our study examines several new time- and especially size-related characteristics, including the final size of infections and deaths, the maximum number of concurrent infectious cases, and the alarm time associated with escalating numbers of infections or deaths. We present theorems and algorithms for the determination of the distributions and moments of key statistical measures. Additionally, we share further insights on effective computational techniques designed to enhance the efficiency of employing the suggested algorithms. Moreover, numerous illustrative instances, coupled with a thorough sensitivity analysis, demonstrate how system parameters affect the severity of epidemics. This not only bolsters the credibility of the outcomes, but also underscores the significance of the suggested stochastic descriptors when assessing real-life epidemics. At the same time, we examine the applicability of the proposed methodology to real Marburg fever data in Angola. Unlike other approaches that mainly concentrate on using mathematical models to fit the evolution of a disease, our goal is to complement these studies by emphasizing significant aspects that play an important role in assessing the seriousness of epidemics. The introduced epidemiological quantities can aid public health authorities in making well-informed choices, potentially leading to a substantial decrease in both mortality rates and socio-economic repercussions. MSC62G30, 60G10, 62P10, 62G32

A novel historical data-based method for predicting firefighters demand in urban fires

Urban fires are a prevalent type of fire that requires prompt and effective responses. Determining the appropriate number of firefighters at the alarm time is crucial, but it mostly relies on the experience of decision-makers. Due to the fuzziness and limitations of human knowledge, there is often a deviation between the number of firefighters dispatched relying on personal subjective experience and the realistic demand. This paper proposed a historical data-based method for predicting the demand number of firefighters in urban fire. Initially, the National Fire Incident Reporting System (NFIRS) data and Global Historical Climatology Network Daily (GHCN-D) weather data were combined to create a fused dataset. The dataset was subjected to anomaly detection and feature selection, then the processed data was used to predict the number of firefighters using artificial neural network (ANN). In this process, the Genetic Algorithm (GA) was applied to optimize ANN structure. Finally, comparative experiments were conducted to evaluate the performance of the proposed method, which demonstrated superior accuracy in comparison to common regression models and traditional ANN. This advancement brings the number of dispatched firefighters closer to the actual demand and contributes to ensuring an adequate allocation of firefighters for urban fires. Consequently, decision-makers can make more informed decisions regarding the number of firefighters to dispatch, leading to more effective responses to urban fires.