Stable Period Research Articles

Quantile connectedness between China’s new energy market and other key financial markets

ABSTRACT This study utilizes data from the China Securities Index for the period from September 2017 to September 2022 and employs the quantile VAR model’s connectedness measurement method to examine the static and dynamic quantile connectedness between China’s new energy sector and other financial markets. The research findings reveal a significant correlation between China’s new energy market and other financial markets. During stable market periods, China’s new energy market exhibits strong predictive power over changes in other financial markets and acts as a net transmitter of systemic return shocks. The new energy, aviation, and agriculture sectors have a substantial impact on other financial markets. Extreme shocks significantly influence spillover effects, with total connectedness levels increasing with extreme downward and upward shocks. Furthermore, in the rolling window analysis, the total risk spillover index exhibits pronounced fluctuations during extreme market conditions, indicating that changes in investor sentiment and market expectations lead to greater market volatility and more significant information transmission effects. The new energy industry demonstrates predictable risk transmission characteristics, typically acting as a net transmitter of systemic risk in both normal and extreme market conditions.

Start-Up Performance and Process Kinetics of a Two-Stage Partial Nitrification–Anaerobic Ammonium Oxidation Reactor

The study of two-stage partial nitrification–anaerobic ammonium oxidation (PN/A) reactors, which are advantageous in engineering applications, still lacks research on process kinetics. Therefore, in this study, the start-up performance and process kinetics of a two-stage PN/A reactor were evaluated by controlling the reaction conditions, for which the two reactors were inoculated with sludge, incubated separately, and then operated in tandem. Increasing the ammonia load of the reactor during the 60 d stabilization period resulted in a nitrogen accumulation rate of 96.93% and a [NO2− − N]Eff/[NH4+ − N]Eff ratio of 1.33, which is close to the theoretical value of 1.32. Successful initiation of the A reactor was achieved after 55 d of operation by inoculating with anammox-activated sludge and granular activated carbon, and the PN and A reactors then successfully operated in combination for 20 d, with an average NH4+ − N efficiency of 99.04% and the NH4+ − N load of the A reactor showing an “S-shaped” curve. An analysis of the microbial growth kinetic models indicated that the removal of NH4+ − N could be successfully described by the logistic, modified logistic, modified Gompertz, and modified Boltzmann models. A strong association between the model and the dependent variable was observed. The process kinetic analysis showed that the removal of NH4+ − N from reactor A could be simulated under steady-state conditions, using the Grau second-order model. The parameters obtained from the model analysis are expected to help predict the denitrification performance of the reactor, facilitate operational management and control, and thus provide a promising research basis for the introduction of automated control systems.

HCEL: Hybrid Clustering Approach for Extending WBAN Lifetime

Wireless body area networks (WBANs) have emerged as a promising solution for addressing challenges faced by elderly individuals, limited medical facilities, and various chronic medical conditions. WBANs consist of wearable sensing and computing devices interconnected through wireless communication channels, enabling the collection and transmission of vital physiological data. However, the energy constraints of the battery-powered sensor nodes in WBANs pose a significant challenge to ensuring long-term operational efficiency. Two-hop routing protocols have been suggested to extend the stability period and maximize the network’s lifetime. These protocols select appropriate parent nodes or forwarders with a maximum of two hops to relay data from sensor nodes to the sink. While numerous energy-efficient routing solutions have been proposed for WBANs, reliability has often been overlooked. Our paper introduces an energy-efficient routing protocol called a Hybrid Clustering Approach for Extending WBAN Lifetime (HCEL) to address these limitations. HCEL leverages a utility function to select parent nodes based on residual energy (RE), proximity to the sink node, and the received signal strength indicator (RSSI). The parent node selection process also incorporates an energy threshold value and a constrained number of serving nodes. The main goal is to extend the overall lifetime of all nodes within the network. Through extensive simulations, the study shows that HCEL outperforms both Stable Increased Throughput Multihop Protocol for Link Efficiency (SIMPLE) and Energy-Efficient Reliable Routing Scheme (ERRS) protocols in several key performance metrics. The specific findings of our article highlight the superior performance of HCEL in terms of increased network stability, extended network lifetime, reduced energy consumption, improved data throughput, minimized delays, and improved link reliability.

Bipolar disorder, Deafness and Culturality in Psychiatric Home Hospitalization: A Clinical Case

IntroductionMental health in the deaf community is a complex issue. Challenges in diagnosis and treatment arise from a lack of experienced interpreters and difficulties in translating Sign Language to spoken language. Deaf individuals, due to auditory limitations, are more vulnerable to abuse, increasing their risk of mental health disorders, including bipolar affective disorder (BPAD). BPAD is a prevalent, debilitating condition with varied prevalence estimates. Managing it is tough due to its lifelong, unpredictable nature. A new approach called Psychiatric Home Hospitalization Unit aims to provide acute mental health care at home as an alternative to hospitalization.ObjectivesTo show the management of severe bipolar disorder with comorbidity from a Psychiatric Home Hospitalization UnitMethodsA clinical case of bipolar disorder with deafness attended at the Psychiatric Home Hospitalization Unit of our hospital is presented.ResultsA 24-year-old deaf woman borned in Pakistan and later moving to Catalonia, she faced educational challenges but ultimately completed her studies with sign language support. Afterward, she struggled to find suitable employment, and her family had a history of bipolar disorder.She exhibited a sudden change in behavior, characterized by irritability, paranoia, and distrust. Communication was challenging due to her speech difficulties, but assessments using sign language and observation were conducted. Her physical examination was normal, but her speech was disorganized and pressured, suggesting possible auditory hallucinations and thought disturbances. She was hospitalized and diagnosed with bipolar disorder with psychotic features.During her initial hospitalization, she received lithium, olanzapine, clotiapine and benzodiacepines. After discharge, she continued treatment through a home hospitalization service during almost 4 month. During follow-up she presented a course with high affective instability, rapid cycling alternating brief periods of stability with other presenting manic and mixed features with high disorganization.Due to the rapid cycling pattern Valproic acid was considered. Valproic acid was introduced up to 700 mg/d (97.1 mcg/mL). Treatment with lithium carbonate 800 mg/d (0.91 mEq/L) was maintained. Previous antipsychotic regimen was changed to quetiapine 400mg/d, olanzapine 5mg/d. Her condition improved significantly with the adjusted treatment regimen. She was discharged to an outpatient service.ConclusionsDiagnosing and treating bipolar affective disorder (BPAD) in a deaf and mute patient posed unique challenges. The rapid mood cycling pattern and complexity of her case made treatment challenging. Family information and interpreter support were vital. Cultural factors were considered, and home hospitalization was crucial in managing symptoms that lasted over four months.Disclosure of InterestNone Declared

Assessing Radiative Impacts of African Smoke Aerosols Over the Southeastern Atlantic Ocean

AbstractBiomass burning smoke aerosols are efficient at attenuating incoming solar radiation. The Layered Atlantic Smoke Interactions with Clouds campaign was conducted from June 2016 to October 2017. The U. S. Department of Energy mobile Atmospheric Radiation Measurement site located on Ascension Island (AMF‐ASI) identified several instances of smoke plume intrusions. Increases in surface and column measurements of aerosol loading were directly related to increases in fine mode fraction, number concentrations of aerosols (Na), and cloud condensation nuclei (NCCN). During periods of weak lower tropospheric stability, smoke particles were more likely to be advected downward either by boundary layer turbulence or cloud top entrainment under non‐overcast sky conditions. Backward trajectory analysis illustrated that smoke aerosols reaching the AMF‐ASI site were fine mode, less aged, strongly absorbing, and had shorter boundary layer trajectories while longer boundary layer trajectories denoted mixtures of weakly absorbing smoke and coarse mode marine aerosols. The most polluted smoke cases of August 2016 and 2017 revealed a notable contrast in radiative forcing per unit aerosol optical depth or radiative forcing efficiency (ΔFeff) at the top of the atmosphere (TOA) and near‐surface (BOA). The weakly (strongly) absorbing 2016 cases exhibited weaker (stronger) ΔFeff at the TOA and BOA suggesting a warming (cooling) effect within the boundary layer. The 2017 cases featured the strongest ΔFeff suggesting more of a cooling effect at the TOA and BOA due to mixing of fresh smoke with marine aerosols during transport.

Effects of the turbulent incoming flow condition on the wind–snow flow characteristics and accretion distribution in the cutting area of the high-speed railway

In addressing snowdrift disasters in high-speed railway cutting areas, this study utilized the improved delayed detached eddy simulation turbulence model, synthetic eddy method, and Eulerian two-phase flow model (Euler–Euler). Coupled with grid dynamic deformation techniques, the investigation facilitated extracting temporal variations in snow particle accumulation profiles within the cutting areas. The predicting accuracy of the numerical method was validated through the wind tunnel and wind–snow experimental data. Building upon this foundation, the study investigated how uniform and turbulent flow conditions impact snow distribution in the high-speed railway cutting areas. The analysis examined the turbulent flow structures, friction velocity distribution, and snow accretion contours within the cutting area. Findings indicate that the snow mass on the windward slope in the cutting area remains consistent under both flow conditions. However, there are significant differences in the rate of snow mass growth and the characteristics of snow accretion distribution. The disappearance of vortex structures at the base of the leeward slope is crucial for indicating the transition in the accumulation states of the surrounding snow particles. Under turbulent incoming flow conditions, the transition from large-scale vortex systems to vortex pairs on the leeward slope of the cutting is delayed, resulting in a postponed stable growth period for snow accretion. Additionally, strong erosion between the track bed and the leeward slope results in reduced snow accretion mass in these areas. In particular, at the simulation time of t = 150 min, under turbulent incoming flow conditions, the overall snow accumulation in the cutting decreased by 20.8% compared to the uniform incoming flow conditions. The snow mass in the leeward slope area decreased by 38.3%, and the track bed area experienced a 23.3% reduction in snow accumulation. In contrast, the snow quantity on the windward slope remained relatively consistent.

A New Visible Spectrophotometric Approach for Determination of Methyldopa in Pharmaceuticals

الهدف من البحث هو تطوير طريقة طيفية جديدة لتقدير عقار الميثيل دوبا بشكليه النقي والصيدلاني تعتمد الطريقة المقترحة على التفاعل بين المثيل دوبا و كاشف الانسدين بوجود نيتروبروسيد البوتاسيوم وهيدروكسيد الصوديوم لتكوين ناتج ملون تم دراسة تأثير العديد من العوامل المؤثرة على ناتج التفاعل تتضمن تركيز الكاشف و زمن التفاعل و استقرارية الناتج الملون مع ضبط هذه العوامل. متابعة التفاعل تمت بقياس الامتصاص عند 597 نانومتر للناتج الملون. في مدى من التركيز من (0.50 إلى 80.0) ميكروغرام.مل -1 كانت حساسية ساندل 0.0218 مايكروغرام.سم-1 و حد الكشف 0.0353 مايكروغرام.مل-1 و الحد الكمي 0.2691 مايكروغرام.مل-1. تم تطبيق الطريقة المقترحة بنجاح لتقدير المثيل دوبا في المستحضرات الصيدلانية.

Digital loans and buy now pay later from LendTech versus bank loans in the era of ‘black swans’: Complementarity in the area of consumer financing

Research background: People who take non-banking loans are primarily perceived as excluded from accessing bank services. The growth of e-commerce and the increasing digitalisation of customer interactions with banks was particularly accelerated by the COVID-19 pandemic (the first ‘black swan’). These processes have also influenced the rapid growth of the LendTech (LT) sector within FinTech with its digital loans and buy-now-pay-later (BNPL) services. The war in Ukraine (the second ‘black swan’) has led to an energy crisis, increased inflation, interest rates and credit costs, and reduced credit accessibility. In this context, the following research questions are addressed: Are the LT and banking sectors complementary or substitutive in the area of consumer financing? Does complementarity apply to all customer segments and loan amounts? How does the extent of complementarity or substitutability of the LT sector depend on, and to what extent do changes in the regulatory and macroeconomic environment affect, the interaction between the banking and LT sectors? Purpose of the article: The aim of the article is to identify trends in the LT sector within FinTech in the context of assessing the scale and determinants of current and future complementarity of the non-bank sector and the banking sector in the area of consumer credit in time of black swans. An additional purpose of the article is to estimate revenues from the basic operating activities of companies from the on-line channel. Methods: The research process was multi-stage and the research procedure was structured. Due to the lack of a uniform source of data on LT products and services, the study used many data sources — data from the Credit Information Bureau, a primary nationwide survey on LT users a primary survey of people representing LT's managerial staff. The selection of LTs was carried out according to the concept of the monetary sampling unit. The Horvitz-Thompson estimator with Sen‐Yates‐Grundy variance form was used to estimate net operating income for LT from the online channel in 2021. Findings & value added: The LT companies surveyed state that black swans (the COVID-19 pandemic and the war in Ukraine) and the current macroeconomic situation have not significantly affected demand for non-banking loans. The reduction in the opportunities for the LT sector as a result of anti-usury regulations will only lead to a shift in consumer demand to the pawnshop sector and the shadow economy, which will be detrimental to consumers. Complementarity between LT and the banking sector is revealed especially in crisis situations, thus limiting the effects of market shock (limited supply of loans offered by banks). In periods of stabilisation, a rather clear division of preferences is noticeable – in the case of seniors and loans for higher amounts, banks dominate, while in the case of lower amounts and in younger age groups, non-bank institutions are more popular. The mechanism by which shrinking banking services are replaced by LT in short-term crises confirms the importance of LT in balancing the Consumer Finance market in the face of unstable periods. From a medium- and long-term perspective, it should be noted that inflation and rising interest rates will increase the scale of credit exclusion in commercial banks, shifting part of the demand to the non-bank sector. These phenomena have an international dimension. Similar observations were made already in 2012 by the CFPB in the USA and the British FTA, when analysing the consumer finance market immediately after the subprime crisis, emphasising the effects of limiting access to bank consumer loans and the resulting growth of the LT market (Gębski, 2013).

Assessing Machine Learning Techniques for Predicting Banking Crises in India

The historical prevalence of banking crises and their profound impact on global economies underscores the imperative for policy makers to refine their crisis forecasting frameworks. Against this backdrop, the present study endeavors to predict potential banking crises in India by leveraging a spectrum of artificial intelligence and machine learning techniques (AI-ML). These techniques encompass logistic regression, random forest, naïve Bayes, gradient boosting, support vector machine, neural networks, K-nearest neighbors, and decision trees. Initially, a banking fragility index was constructed utilizing monthly banking data spanning 2002 to 2023, demarcating the periods of crisis and stability. Subsequently, an extensive array of early warning indicators (EWIs) encompassing asset prices, macroeconomic factors, external influences, and credit-related variables were employed to forecast crisis periods. Our findings reveal that AI-ML models exhibit reasonable accuracy in predicting banking crises. Moreover, advanced model performance metrics highlight neural networks and random forest models as particularly effective in crisis prediction, surpassing other methodologies. Notably, among the EWIs, variables related to credit, interest rates, and liquidity emerge as possessing relatively higher information value in discerning fragilities within the Indian banking system. Importantly, the methodological framework presented herein can be extrapolated for banking crisis prediction in other economies.

Simulation and experiment of air-duct heating equipment using electricity in a sheep barn using computational fluid dynamics

The temperature inside the sheep barn has a significant effect on sheep growth; therefore, providing a suitable thermal environment for the barn is essential. Considering the uneven heating problem of existing heating equipment in livestock barns, we designed an air-duct heating equipment using electricity to ensure a comfortable temperature for sheep with a suitable airflow rate. A computational fluid dynamics (CFD) method was used to simulate the temperature and velocity fields inside the sheep barn, check the heating effectiveness, and ensure uniformity. To determine the optimal opening direction and size of the heating equipment, simulation tests with various opening directions and sizes were conducted using the flow velocity and uniformity of the flow field as the key factors. The CFD simulation results showed that for the investigated sheep barn, a downward opening with diameter of 60 mm was the most effective for heating. Finally, in winter, a heating test was conducted during the decreasing, stable, and increasing periods of outdoor temperatures to verify the heating effectiveness in the experimental sheep barn. During the decreasing and stable periods of outdoor temperature, the indoor temperatures increased by 2 and 5 ℃, respectively, in 70 min. Conversely in the increasing period of outdoor temperature, the temperature inside the barn increased by 11 ℃ and continued to rise. Our results showed that the expected heating effect of sheep barns was achieved, which can provide a reference for the environmental regulation of livestock barns.

Food Insecurity and Mental Health Outcomes Among Transgender and Gender-Diverse Communities in the United States Post-COVID-19

A growing body of literature has shown that people in the transgender and gender-diverse (TGD) community have worse health outcomes than cisgender (cis) people, including higher rates of poor mental health. Additionally, during COVID-19, TGD persons experienced higher rates of food insecurity. In this article, we extend the literature by looking at new data in the post-COVID-19 period, a period of greater stability. Using data from the U.S. Census Household Pulse Survey (HPS), we explore the relationship between gender identity and health outcomes. The HPS began collecting data on gender identity of participants from July 2021. We analyze responses from 1.2 million survey participants between July 2021 and May 2023. Using an ordinary least squares regression model with state and week fixed effects, we show that, on average, TGD people are seven percentage points more likely to report experiencing food insecurity compared with cis persons. TGD persons also report more symptoms of depression (six percentage points) and anxiety (four percentage points) than cis persons. These results hold after controlling for the socioeconomic, demographic, and sexual identity characteristics of the individuals, suggesting that this gender identity imposes an additional cost that cannot be explained by social determinants of health. We find that health insurance and the Supplemental Nutrition Assistance Program do not provide very much protection to TGD individuals. In summary, our article suggests the need for safety nets that target specific contextual and institutional challenges faced by TGD communities to reduce health disparities across the country.

Could the HALP score serve as a biomarker of bronchiectasis exacerbation?

Bronchiectasis is a chronic inflammatory lung disease and patients may occasionally experience acute exacerbations. Our study aims to determine the relationship between exacerbation periods and HALP (hemoglobin, albumin, lymphocyte, platelet) scores in patients with bronchiectasis. Adult patients diagnosed with bronchiectasis and followed up in our clinic between 02.2020-12.2022 were retrospectively evaluated. After the examinations, the effect of bronchiectasis exacerbation on the HALP score was investigated. A total of 84 patients diagnosed with non-cystic fibrosis bronchiectasis were included in our study. 42 of the patients were male (50%), and 42 were female. The average age of all patients was 52.37 ± 16.2. 35 patients (41.7%) were in the exacerbation period, and 49 patients (58.3%) were in the stable period. The median values of leukocytes, neutrophils, and C-reactive protein (CRP) were significantly higher in patients during the exacerbation period compared to the stable period (respectively p= 0.00, p= 0.00, p= 0.00). The average values of FEV1% and FVC% in patients during the exacerbation period were significantly lower compared to the stable period (p= 0.03, p= 0.00, respectively). The HALP score was significantly lower in patients during the exacerbation period compared to the stable period (p= 0.00). A significant negative correlation was found between the HALP score and leukocytes, neutrophils, and CRP (p= 0.00, p= 0.00, p= 0.00, respectively). Also, a significant positive correlation was found between the HALP score and FEV1% and FVC% (p= 0.00, p= 0.00, respectively). Our study revealed that the HALP score is associated with infectious and pulmonary functional parameters in bronchiectasis patients in the exacerbation period. We propose that the HALP score could serve as a valuable biomarker during exacerbations.

Unraveling the effect mechanism of sulfamethoxazole on nitrogen biotransformation in a PHBV supported denitrifying granular sludge

Sulfamethoxazole (SMX) is prevalent as one of the most frequently detected antibiotics in rivers worldwide, and is listed as one of the priority antibiotics in China based on the persistence, bioaccumulation, toxicity and resistance. Recently, the effect of SMX on aerobic granular sludge has attracted increasing interest. However, how SMX influences the biodegradable polymer supported denitrifying granular sludge is still obscure. Herein, two groups with or without exposure to 1 mg/L SMX with initial nitrate concentrations of 15, 30, and 50 mg/L were constructed. Results showed that there was a negligible difference on nitrate removal efficiencies between two groups under stable period (all exceeded 95 %) in batch bioreactors with an HRT of 24 h, supported by an insignificance difference (p > 0.05). However, the decline in the first-order decay kinetic constants of nitrate removal rate, NAR and NIR activities verified a slight inhibition of SMX on denitrification. Meanwhile, SMX also had an impact on the chemical and microbial properties on granular sludge. SMX boosted the EPS secretion with more humic acid, a delicate rise in PN/PS ratios and a decrease in zeta potential of EPS all favored the microbes' survival under SMX stress. SMX shifted the microbial compositions, namely, the microbes directly involving in PHBV degradation (Caldimonas, denitrificans Comamonas/Diaphorobacter) were enriched instead of some denitrifying microorganism that could not directly utilize PHBV (Denitratisoma, Azospira). Additionally, even though sul1 and sul2 were enriched, which was not readily accessible to receiving waters due to a good settling properties of granular sludge. This work contributes to a deeper understanding of the impact of SMX on this system, and is of great significance for the operation of granular sludge system for nitrate removal under antibiotic's stress.

Downside risk in Dow Jones equity markets: hedging and portfolio management during COVID-19 pandemic and the Russia–Ukraine war

PurposeThis paper aims to examine the dynamic conditional correlation (DCC) and hedging ratios between Dow Jones markets and oil, gold and bitcoin. Using daily data, including the COVID-19 pandemic and the Russia–Ukraine war. We employ the DCC-generalized autoregressive conditional heteroskedasticity (GARCH) and asymmetric DCC (ADCC)-GARCH models.Design/methodology/approachDCC-GARCH and ADCC-GARCH models.FindingsThe most of DCCs among market pairs are positive during COVID-19 period, implying the existence of volatility spillovers (Contagion-effects). This implies the lack of additional economic gains of diversification. So, COVID-19 represents a systematic risk that resists diversification. However, during the Russia–Ukraine war the DCCs are negative for most pairs that include Oil and Gold, implying investors may benefit from portfolio-diversification. Our hedging analysis carries significant implications for investors seeking higher returns while hedging their Dow Jones portfolios: keeping their portfolios unhedged is better than hedging them. This is because Islamic stocks have the ability to mitigate risks.Originality/valueOur paper may make a valuable contribution to the existing literature by examining the hedging of financial assets, including both conventional and Islamic assets, during periods of stability and crisis, such as the COVID-19 pandemic and the Russia–Ukraine war.

Synchrotron radiation SAXS study of the species structure evolution in the synthesis process of MCM-56 zeolite

In the process of synthesizing zeolite, the evolution behavior of aluminosilicate species is crucial for investigating the crystallization mechanism and controlling the structure of desired zeolite. Herein, the synthesis process of MCM-56 zeolite was investigated by using the synchrotron radiation Small Angle X-ray Scattering (SAXS) technique. Based on the distance distribution function curves and Porod analysis, the particle distribution of the sol in the synthesis system transformed from a monodisperse spherical particle to a polydisperse lamellar structure. The results indicated that the particle size distribution, fractal dimension, and the evolution behavior of particles in sol vary with the variation of crystallization time. Specifically, the initial step involves the depolymerization of particles forming small particles approximately 1 nm. Subsequently, these small particles polymerize to form structural units ranging in size from 1 to 5 nm, and finally grow to form MCM-56 zeolite crystal by consuming aluminosilicate species. The SAXS results in conjunction with the XRD, SEM, FT-IR, and N2 adsorption-desorption analysis elucidate the evolution of aluminosilicate species and the crystallization process of MCM-56 zeolite at three stages, including the induction/nucleation period (0–84 h), the crystal growth period (84–108 h) and the crystal stability period (108–168 h). By virtue of the understanding for the structural evolution of the sol species, this work is expected to highlight the controllable synthesis of MCM-56 zeolite.

The Treatment of Refractory Vitiligo With Autologous Cultured Epithelium Grafting: A Real-World Retrospective Cohort Study.

Surgical intervention is the main therapy for refractory vitiligo. We developed a modified autologous cultured epithelial grafting (ACEG) technique for vitiligo treatment. Between January 2015 and June 2019, a total of 726 patients with vitiligo underwent ACEG in China, with patient characteristics and clinical factors being meticulously documented. Using a generalized linear mixed model, we were able to assess the association between these characteristics and the repigmentation rate. ACEG demonstrated a total efficacy rate of 82.81% (1754/2118) in treating 726 patients, with a higher repigmentation rate of 64.87% compared to conventional surgery at 52.69%. Notably, ACEG showed a better response in treating segmental vitiligo, lesions on lower limbs, age ≤ 18, and stable period > 3 years. A keratinocyte:melanocyte ratio below 25 was found to be advantageous too. Single-cell RNA sequencing analysis revealed an increase in melanocyte count and 2 subclusters of keratinocytes after ACEG, which remained higher in repigmented sites even after 1 year. ACEG is a promising therapy for refractory vitiligo. Patient age, clinical type, lesion site, and stability before surgery influence repigmentation in ACEG. The mechanism of repigmentation after ACEG treatment is likely not confined to the restoration of melanocyte populations. It may also involve an increase in the number of keratinocytes that support melanocyte function within the affected area. These keratinocytes may aid the post-transplant survival and function of melanocytes by secreting cytokines and extracellular matrix components. registered with Chictr.org.cn (ChiCTR2100051405).

Modelling of anaerobic digestion of microalgae biomass: Effect of overloading perturbation

Anaerobic digestion (AD) of microalgae is an intriguing approach for bioenergy production. The scaling-up of AD presents a significant challenge due to the systematic efficiency losses related to process instabilities. To gain a comprehensive understanding of AD behavior, this study assessed a modified version of the anaerobic digestion model No1 (ADM1) + Contois kinetics to represent microalgae AD impacted by overloading. To this end, two new inhibition functions were implemented: inhibition by acetate for acidogenesis/acetogenesis and total volatile fatty acids for hydrolysis. This proposed ADM1 modification (including Contois kinetics) simulated AD behavior during the stable, disturbed and recovery periods, showing that the inhibition functions described in the original ADM1 cannot explain the AD performance under one of the most common perturbations at industrial scale (overloading). The findings underscore the importance of refining the inhibitions present in original ADM1 to better capture and predict the complexities of microalgae AD against overloading.

Distinct oxygenation modes of the Gulf of Oman over the past 43 000 years – a multi-proxy approach

Abstract. Changing climatic conditions can shape the strength and extent of the oxygen minimum zone (OMZ). The presence and variability of the OMZ in the Arabian Sea is of importance to the latter's ecosystem. The state of oxygenation has, for instance, an impact on the pelagic and benthic faunal community or the nitrogen and carbon cycles. It is important to understand the dynamics of the OMZ and related marine environmental conditions because of their climate feedbacks. In this study, we combined three independent proxies to reconstruct the oxygenation state of the water column and bottom water in the Gulf of Oman for the past 43 kyr approximately. This multi-proxy approach is done for the first time at the northeastern Oman margin located in the Gulf of Oman. We used bulk sedimentary nitrogen isotopes (δ15N) and the alkane ratio (lycopane +n-C35)/n-C31 and benthic foraminiferal faunal analysis to reconstruct the strength of the OMZ in the water column and bottom water oxygenation, respectively. Our results show that the Gulf of Oman experienced strong pronounced OMZ and bottom water deoxygenation during the Holocene. In contrast, during Marine Isotope Stage 2 (MIS 2), including the Last Glacial Maximum (LGM), the Gulf of Oman was very well ventilated, with a highly diverse benthic foraminiferal community. This may have been caused by stronger wind-induced mixing and better ventilation by oxygen-rich water masses. Our results also show moderate oxygenation during MIS 3, with deoxygenation events during most of the warmer Dansgaard–Oeschger (D–O) events. We propose two distinct oxygenation modes for the Gulf of Oman: (1) a stable period of either strongly pronounced water column OMZ and bottom water deoxygenation or well-oxygenated water column and bottom water conditions and (2) an unstable period of oscillating oxygenation states between moderately oxygenated (stadials) and deoxygenated (interstadials, D–O events) conditions. The unstable period may be triggered by an interstadial Atlantic meridional overturning circulation (AMOC) mode, which is required to initiate D–O events.

Energy aware and secure routing for hierarchical cluster through trust evaluation

With the rapid growth of technology advancement in wireless communication have resulted in interconnection of large number of devices covering wide range of application services. Wireless sensor network (WSN) have become popular and provide various benefits, including low-power smart computation, compact size, self organizing and ability to route via routing protocols. WSN covers a wide range of application services, including home automation, smart cities, fire detection, unmanned aerial vehicle (UAV), and object tacking. Sensor nodes are tiny, battery operated, and suffer from fundamental restrictions such as available bandwidth, memory space, power restrictions, and limited resources. Due to their communication characteristics and working environment, WSN faces energy optimization and secure data communication challenges to increase network lifetime and defend against malicious nodes. To overcome energy scarcity and consumption issues, clustering methods have proven smart and effective approaches to reduce energy consumption and extend network life. Low energy adaptive clustering hierarchy (LEACH), well-known clustering method, enhances energy efficiency by selecting cluster head (CH) on a rotation basis by employing random integer technique. To extend network stability period, extensions of LEACH was proposed. LEACH and its extensions mainly focus on optimal selection of CH and fail to concentrate on secure communication. Integration of blockchain and real-time message content validation (RMVC) in LEACH was modelled to detect malicious node through secure hash algorithm. However, existing scheme had complex cryptographic functions and higher computation overhead. In this paper, we present energy aware and secure routing (EASR) for hierarchical cluster based WSN. Existing LEACH is modified and an improved threshold value is adapted to select secure optimal CH and trust based routing model which combines direct and indirect trust opinion values to resist routing attacks for establishing trustworthy and reliable routes towards base station.

Review of the Evidence for Pulmonary Rehabilitation in COPD: Clinical Benefits and Cost-Effectiveness.

COPD is a common and lethal chronic condition, recognized as a leading cause of death worldwide. COPD is associated with significant morbidity and disability, particularly among older adults. The disease course is marked by periods of stability and disease exacerbations defined by worsening respiratory status resulting in a high burden of health care utilization and an increased risk of mortality. Treatment is focused on pharmacologic therapies, but these are not completely effective. Pulmonary rehabilitation (PR) represents a key medical intervention for patients with chronic respiratory diseases, including COPD. PR provides individualized and progressive exercise training, education, and self-management strategies through a comprehensive and multidisciplinary program. PR has been associated with improvement in exercise capacity, health-related quality of life, and dyspnea in patients living with COPD. Moreover, PR has been associated with improvements in hospital readmission and 1-y survival. In addition to the clinical benefits, PR is estimated to be a cost-effective medical intervention. Despite these benefits, participation in PR remains low. We will review the evidence for PR in each of these benefit domains among patients with stable COPD and in those recovering from a COPD exacerbation.