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AbstractThe impact of COVID-19 infection on individuals with small cell lung cancer (SCLC) poses a serious threat. Unfortunately, the molecular basis of this severe comorbidity has yet to be elucidated. The present study addresses this gap utilizing publicly available omics data of COVID-19 and SCLC to explore the key molecules and associated pathways involved in the convergence of these diseases. Findings revealed 402 genes, that exhibited differential expression patterns in SCLC patients and also play a pivotal role in COVID-19 pathogenesis. Subsequent functional enrichment analyses identified relevant ontologies and pathways that are significantly associated with these genes, revealing important insights into their potential biological, molecular and cellular functions. The protein-protein interaction network, constructed under four combinatorial topological assessments, highlighted SMAD3, CAV1, PIK3R1, and FN1 as the primary components to this comorbidity. Our results suggest that these components significantly regulate this cross-talk triggering the PI3K-AKT and TGF-β signaling pathways. Lastly, this study made a multi-step computational attempt and identified corylifol A and ginkgetin from natural sources that can potentially inhibit these components. Therefore, the outcomes of this study offer novel perspectives on the common molecular mechanisms underlying SCLC and COVID-19 and present future opportunities for drug development.Communicated by Ramaswamy H. Sarma

We examine the association between strategic deviation and investment inefficiency. We conceptualize strategic deviation as the extent to which the pattern of a firm’s resource allocation deviates from its industry peers. We posit that firms pursuing deviant strategies are prone to increased information asymmetry and hence, are able to engage in self-serving behaviour as manifested in inefficient investments. Our results suggest that deviant firms have sub-optimal investments. A battery of robustness tests validates our findings. We further provide evidence to suggest that weaker monitoring, high product market competition and a low-quality information environment moderate the relation between strategic deviation and investment inefficiency.JEL Classification: M41, G41

We investigate the association between business strategy and firm-level tournament incentives in China and find that business strategy is associated with tournament incentives positively. We further find that this positive relationship manifests itself in local, but not central, state-owned enterprises (SOEs). In addition, we also offer some evidence that foreign institutional investors play a moderating role on the positive association between business strategy and tournament incentives. Our study fills a gap in the existing tournament literature by incorporating business strategy as an important determinant of tournament incentives in China.JEL CLASSIFICATIONM10; G30; J33

The 1BL/1RS translocation is widespread in a large number of wheat varieties. In this study, we comprehensively evaluated the effects of the 1BL/1RS translocation on 24 traits in a recombinant inbred line population derived from the cross between 20828 and Chuannong16. The phenotypic data was from multiple environments and major loci for a given trait were excluded to avoid their interference with the effects of 1BL/1RS translocation. Comparison results showed that 1RS chromosome arm carried lines had positive effect on increasing maximum root length and spike density. While 1BS chromosome arm carried lines had positive effects on increasing plant height, grain number per spike, effective tiller, root tip number, and resistance to stripe rust. The stripe rust resistance genes, Yr15detected on 1BS in this study and QYr.sicau-1B.1identified previously on 1BL were both derived from 20828. These results revealed the genetic mechanism of near-immune resistance to stripe rust in 20828 that has been utilized as a breeding parent for over a decade, and thus possibly accelerate its breeding utilization. This study combined with previous studies indicated that 1BS chromosome arm is likely beneficial to yield increase, while 1RS is more helpful for drought tolerance improvement.

Improving encoding and decoding time in compression technique is a great demand to modern users. In bit level compression technique, it requires more time to encode or decode every single bit when a binary code is used. In this research, we develop a dictionary-based compression technique where we use a quaternary tree instead of a binary tree for construction of Huffman codes. Firstly, we explore the properties of quaternary tree structure mathematically for construction of Huffman codes. We study the terminology of new tree structure thoroughly and prove the results. Secondly, after a statistical analysis of English language, we design a variable length dictionary based on quaternary codes. Thirdly, we develop the encoding and decoding algorithms for the proposed technique. We compare the performance of the proposed technique with the existing popular techniques. The proposed technique performs better than the existing techniques with respect to decompression speed while the space requirement increases insignificantly.

Graphical Abstract: Synthesis, antibacterial, antioxidant and DFT computational studies of acetophenone-based chalcone derivatives

Major depressive disorder (MDD) is a chronic mental illness which affects people's well-being and is often detected at a later stage of depression with a likelihood of suicidal ideation. Early detection of MDD is thus necessary to reduce the impact, however, it requires monitoring vitals in daily living conditions. EEG is generally multi-channel and due to difficulty in signal acquisition, it is unsuitable for home-based monitoring, whereas, wearable sensors can collect single-channel ECG. Classical machine-learning based MDD detection studies commonly use various heart rate variability features. Feature generation, which requires domain knowledge, is often challenging, and requires computation power, often unsuitable for real time processing, MDDBranchNet is a proposed parallel-branch deep learning model for MDD binary classification from a single channel ECG which uses additional ECG-derived signals such as R-R signal and degree distribution time series of horizontal visibility graph. The use of derived branches was able to increase the model's accuracy by around 7%. An optimal 20-second overlapped segmentation of ECG recording was found to be beneficial with a 70% prediction threshold for maximum MDD detection with a minimum false positive rate. The proposed model evaluated MDD prediction from signal excerpts, irrespective of location (first, middle or last one-third of the recording), instead of considering the entire ECG signal with minimal performance variation stressing the idea that MDD phenomena are likely to manifest uniformly throughout the recording.

Deep-learning-based QRS-detection algorithms often require essential post-processing to refine the output prediction-stream for R-peak localisation. The post-processing involves basic signal-processing tasks including the removal of random noise in the model's prediction stream using a basic Salt and Pepper filter, as well as, tasks that use domain-specific thresholds, including a minimum QRS size, and a minimum or maximum R-R distance. These thresholds were found to vary among QRS-detection studies and empirically determined for the target dataset, which may have implications if the target dataset differs such as the drop of performance in unknown test datasets. Moreover, these studies, in general, fail to identify the relative strengths of deep-learning models and the post-processing to weigh them appropriately. This study identifies the domain-specific post-processing, as found in the QRS-detection literature, as three steps based on the required domain knowledge. It was found that the use of minimal domain-specific post-processing is often sufficient for most of the cases and the use of additional domain-specific refinement ensures superior performance, however, it makes the process biased towards the training data and lacks generalisability. As a remedy, a domain-agnostic automated post-processing is introduced where a separate recurrent neural network (RNN)-based model learns required post-processing from the output generated from a QRS-segmenting deep learning model, which is, to the best of our knowledge, the first of its kind. The RNN-based post-processing shows superiority over the domain-specific post-processing for most of the cases (with shallow variants of the QRS-segmenting model and datasets like TWADB) and lags behind for others but with a small margin ($\leq$2%). The consistency of the RNN-based post-processor is an important characteristic which can be utilised in designing a stable and domain agnostic QRS detector.

Purpose: This study aims to examine the impact of different levels of required book-tax conformity (BTC) on audit clients' demand for auditor-provided tax services (APTS). In addition, the authors also investigate the effects of the European Union (EU) Regulation (2014). Design/methodology/approach: This study utilizes a sample of listed companies from 10 EU countries between 2010 and 2019. The final sample consists of 16,049 firm-year observations from 2,515 unique firms, and the authors use both probit and ordinary least square (OLS) regression models in this study. Findings: The main finding of this paper is that companies listed in countries with a higher level of BTC are less likely to purchase tax services from incumbent auditors and pay fewer auditor-provided tax service fees. Results from further analyses confirm that firms substantially reduced their purchase of APTS after the EU Regulation (2014) was implemented, but these reduced purchases were found to be more pronounced for firms located in countries with low BTC. Originality/value: This study advances the understanding of the determinants of APTS and the consequences of BTC. Specifically, the authors report that variation in a country-specific feature (i.e. BTC) also affects firms' decision to purchase APTS. Moreover, this paper provides some preliminary evidence of the new regulation and contributes to the literature on APTS regulation. The findings of this study have important policy implications for regulators and are also relevant for various capital market participants.

Purpose: This paper aims to examine the association between green innovation and the cost of equity in China. This study relies on the investors’ base perspective and shareholders’ perceived risk perspective to investigate the relation between green innovation and the cost of equity in China. Design/methodology/approach: The paper uses firm-fixed effect regression for a sample of Chinese public companies for the period 2008–2018. Findings: The authors find a negative relationship between green innovation and the cost of equity capital. This negative association is found to be more pronounced for less financially constrained firms, during periods of high economic policy uncertainty, and for firms with a strong internal control environment. Finally, the paper shows that the negative association became more pronounced after the passage of the Environmental Protection Law of China in 2012. The results remain robust to possible endogeneity concerns. Originality/value: This study contributes to the green innovation literature by documenting that shareholders favorably view firms implementing green innovation policies. The study also has policy implications for Chinese regulators in improving the green credit policy.

Capacitive deionization (CDI), an emerging and promising new method, is being utilized to remove ionic and polarizable species from water. The development of effective electrode materials has been the main driving force behind the increased interest in the CDI system for water purification because it is simple to use, affordable, and environmentally friendly compared to other traditional methods. Carbon electrodes made from biomass are often considered as low-cost, high-performance energy storage materials due to their abundance, simple synthesis methods, and high specific surface area. Herein, we developed materials from biowastes of banana plant leaves (B) and java black (J) that were hydrothermally carbonized. These materials were then chemically treated with KOH at a 1:4 ratio to produce extremely porous activated carbon from the biowastes of banana plant leaves (AC-B) and java black (AC-J). The surface areas of AC-B and AC-J were 84.155 and 295.517 m2g−1respectively, with high mesoporous properties. Poly(vinyl alcohol) (PVA) was employed as a binder to bind the synthetic activated carbons like AC-B and AC-J together in order to make electrodes. Despite the fact that PVA is hydrophilic by nature, the hydrophobic glutaraldehyde (GA) was used to cross-link the PVA molecules in order to increase the durability of the carbon material and produced AC-B-PVA-GA and AC-J-PVA-GA electrodes. X-ray diffraction, scanning electron microscopy, Fourier-transform infrared spectroscopy, Brunauer-Emmett-Teller, and cyclic voltammetry were used to characterize the synthesized carbon materials. The newly developed CDI electrodes, which demonstrated a variety of electrosorption capacities at different applied potentials, were used to investigate the effectiveness of the desalination process. The developed electrodes showed good stability under shear conditions, and the CDI process was repeatable and stable after around 10 electrosorption cycles. For example, the specific capacities of the AC-B-PVA-GA and AC-J-PVA-GA electrodes were 31.01 and 40.78 F/g, respectively in a 0.5 M NaCl aqueous solution. At 1.2 V, it was found that the AC-B-PVA-GA and AC-J-PVA-GA electrodes removed 2.41 and 3.64 mg g−1of salt, respectively. The findings obtained encourage the development of CDI systems for desalination and water treatment and provide essential information on ion electrosorption. It also demonstrates an effective method for environmental cleanup utilizing a basic CDI system.

Automatic sleep stage classification is vital for evaluating the quality of sleep. Conventionally, sleep is monitored using multiple physiological sensors that are uncomfortable for long-term monitoring and require expert intervention. In this study, we propose an automatic technique for multi-stage sleep classification using photoplethysmographic (PPG) signal. We have proposed a convolutional neural network (CNN) that learns directly from the PPG signal and classifies multiple sleep stages. We developed models for two- (Wake-Sleep), three- (Wake-NREM-REM) and four- (Wake-Light sleep-Deep sleep-REM) stages of sleep classification. Our proposed approach shows an average classification accuracy of 94.4%, 94.2%, and 92.9% for two, three, and four stages, respectively. Experimental results show that the proposed CNN model outperforms existing state-of-the-art models (classical and deep learning) in the literature.

Interpretability often seeks domain-specific facts, which is understandable to human, from deep-learning (DL) or other machine-learning (ML) models of black-box nature. This is particularly important to establish transparency in ML model’s inner-working and decision-making, so that a certain level of trust is achieved when a model is deployed in a sensitive and mission-critical context, such as health-care. Model-level transparency can be achieved when its components are transparent and are capable of explaining reason of a decision, for a given input, which can be linked to domain-knowledge. This article used convolutional neural network (CNN), with sinc-convolution as its constrained first-layer, to explore if such a model’s decision-making can be explained, for a given task, by observing the sinc-convolution’s sinc-kernels. These kernels work like band-pass filters, having only two parameters per kernel - lower and upper cutoff frequencies, and optimised through back-propagation. The optimised frequency-bands of sinc-kernels may provide domain-specific insights for a given task. For a given input instance, the effects of sinc-kernels was visualised by means of explanation vector, which may help to identify comparatively significant frequency-bands, that may provide domain-specific interpretation, for the given task. In addition, a CNN model was further optimised by considering the identified subset of prominent sinc frequency-bands as the constrained first-layer, which yielded comparable or better performance, as compared to its all sinc-bands counterpart, as well as, a classical CNN. A minimal CNN structure, achieved through such an optimisation process, may help design task-specific interpretable models. To the best of our knowledge, the idea of sinc-convolution layer’s task-specific significant sinc-kernel-based network optimisation is the first of its kind. Additionally, the idea of explanation-vector-based joint time-frequency representation to analyse time-series signals is rare in the literature. The above concept was validated for two tasks, ECG beat-classification (five-class classification task), and R-peak localisation (sample-wise segmentation task).

ALBATROSS is a European Funded project by the European Commission that addresses the needs of European Electric and Hybrid-Electric passenger vehicle market by overcoming driver concerns relating to battery range and anxiety, cost, long-term reliability, and excessive charging times. ALBATROSS will develop an integrated approach based on smart batteries combined with lightweight designs. Using innovative cooling technologies, we will achieve pack temperature range 5-40°C, with <3°C variation between battery cells and optimal operating temperature 20-23°C. The light weighting solutions, based on modular multi-material systems for battery modules and trays, will be fabricated and joined using cutting edge, fast and cost-effective processes, with disassembly, recycling and reuse designed in as a part of an eco-design approach. The modular approach provides solutions for BEVs and PHEVs.

This paper proposes a convolutional neural network-based deep learning model to classify and detect the infectious potato leaves suffering from late blight disease. The proposed model has two classifiers - the potato leaf classifier and the late blight disease classifier. Both healthy and diseased plant leaf images were taken from the plant. Village dataset and real-time images are used to train, validate and test the classifiers. A total of 4,680 and 1,470 plant leaf images are used for the two classifiers, respectively. The potato leaf classification accuracy of the proposed model is 97.12%. The proposed CNN model also provides an accuracy of 98.62% while identifying late blight disease. The ten-fold cross-validation technique is used to observe the performance of the proposed late blight classifier and then compared with other cutting-edge approaches. In observation, it has been shown that the proposed technique outperformed many other existing techniques.

The cloud environment is used by the application providers (APs) to host their applications in order to reduce procurement and management costs of the cloud resources. Moreover, the variation in the traffic load of the client applications and the appealing auto-scaling capability of the cloud resources have prompted application providers to seek ways to reduce the cost of their rented services. This paper describes a constructive auto-scaling mechanism based on the events in cloud systems fitted with heuristic predictors. The predictor examines historical data using these approaches: (1) Double Exponential Smoothing (DES), (2) Triple Exponential Smoothing (TES), (3) Weighted Moving Average (WMA) and (4) WMA with Fibonacci numbers. The outcomes of this model simulation in CloudSim indicate that the model can decrease the application provider's cost while preserving application user satisfaction.

AbstractThe MADS-box transcription factor family plays an important role in regulating growth and signal transduction in animals and plants. TaMADS32encodes a type II MADS-box transcription factor which is mainly expressed in wheat root system. In this study, we used bioinformatics methods to analyse TaMADS32, and investigate its function in plant root development and response to various abiotic stresses. We mapped TaMADS32on chromosome 2B of wheat. Both TaMADS32and its orthologs contained 7 exons and 6 introns and all the orthologous proteins have the MADS domains. Prokaryotic experiments showed that TaMADS32 could be expressed in prokaryotic cells. The predicted subcellular localization of TaMADS32 in plant cells was in the nucleus and in the cell membrane. Abiotic stresses (drought, heat and cold) can alter the expression of TaMADS32in transgenic Arabidopsis. Phenotypic analysis showed that overexpression of TaMADS32enhanced the tolerance of Arabidopsisto abiotic stresses. These results indicate that TaMADS32is probably involved in the adaptation of plants to abiotic stress environments.

Purpose: Higher real earnings management (REM) reduces financial reporting quality and increases the uncertainty of future cash flows and profitability among investors. This study asserts that REM-induced noise increases idiosyncratic return volatility (IVOL), aims to examine the association between REM and IVOL and further investigates whether information asymmetry, firm life cycle and economic policy uncertainty (EPU) moderate the association between REM and IVOL. Design/methodology/approach: The authors use 94,445 firm-year observations from the US over 1987 to 2019 and test this study’s hypotheses using ordinary least square regressions with robust standard errors clustered by firm. The authors use change analysis, two-stage models and the impact threshold of the confounding variable analysis to address endogeneity. Findings: The authors find that REM increases IVOL. This positive association is more pronounced for firms with more information asymmetry, for firms in the mature stage of the life cycle, compared with their growth-stage counterparts; and during periods of high EPU. Originality/value: Extant research suggests that accrual manipulation increases IVOL. However, the shift from accrual manipulation to REM and the managerial preference towards REM suggests that it is important to explore the impact of REM on IVOL. Thus, the authors enhance the understanding of the impact of earnings management on IVOL by documenting that REM-induced noise increases IVOL. The authors further extend the limited research on the consequences of REM and report an adverse consequence.

This paper investigates the impact of earnings management on value relevance of accounting information in the context of Japan. Researchers carrying out earnings management research usually rely on the Jones (1991) or the modified Jones model (1995) to disaggregate accruals into its discretionary and non-discretionary components. However, because of criticisms leveled against extant models of discretionary accruals, this study instead uses earnings management measures constructed by Leuz et al. (2001) and Bhattacharya et al. (2001) and examines the relationship between these measures and their impact on the value-relevance of accounting information. The latter is operationalized by the explanatory power of book values and earnings (combined model) and earnings alone (earnings model) for stock price. Results based on 5,318 consolidated firm-year observations over 1992-1999 show that, both earnings management measures and aggregate earnings management measures (combination of both earnings smoothing and earnings management measures) are significantly negatively associated with the combined value relevance of book values of equity and earnings (combined model) and value relevance of earnings (earnings model).]

The current understanding of the legacy and emerging organic pollutants in the soil of Bangladesh remains limited. Inadequate disposal practices, particularly in e-waste, landfills, and industrial operations, may lead to the pervasive presence of persistent organic pollutants (POPs) and polycyclic aromatic hydrocarbons (PAHs) in the country. This study aimed to systematically investigate the concentrations, sources, and risk assessment of halogenated flame retardants (HFRs), polychlorinated biphenyls (PCBs), polychlorinated naphthalenes (PCNs), organochlorine pesticides (OCPs), chlorinated paraffins (CPs), and PAHs in the contaminated soil of Dhaka's dumpsites, e-waste, and industrial areas collected in 2017. The total concentration of investigated pollutants averaged at 4790 ± 4040 ng g−1dw, with the following order: ∑44CPs (4110 ± 4140 ng g−1dw) > ∑16PAHs (422 ± 491 ng g−1dw) > ∑16HFRs (190 ± 538 ng g−1dw) > ∑209PCBs (43.5 ± 73.5 ng g−1dw) > ∑50PCNs (17.7 ± 21.0 ng g−1dw) > ∑27OCPs (9.41 ± 9.61 ng g−1dw). The e-waste site exhibited the highest total concentration of the target pollutants, reaching 12,700 ng g−1dw. CPs were the predominant contributors, accounting for averages of 81.8%, 70.5%, and 68.5% to waste landfills, e-waste, and industrial sites, respectively. A comprehensive analysis of 209 PCB congeners revealed their primary origin from Aroclor PCBs, with minor contributions from unintentionally produced PCBs. The highest incremental lifetime carcinogenic risk (ILCR) occurred in e-waste sites, contributed by dioxin-like PCBs, with a maximum value of 5.9 × 10−5for adults, exceeding the limit 1.0 × 10−6set by the U.S. EPA. The non-carcinogenic hazard quotients (HQs) were much lower, suggesting no significant risk from the investigated pollutants. Our findings highlight the importance of proper waste management and regulated e-waste recycling to mitigate potential hazardous risks to the Bangladeshi population.

ABSTRACTWe investigate the effect of individual auditor industry specialization on stock price crash risk. Although research on individual auditors has been growing, we are not aware of any prior studies that investigate industry specialization at the individual auditor-level and crash risk. Using a large sample of Chinese stocks spanning the period 2003–2015, we find a statistically significant and negative association between individual auditor industry specialization and stock price crash risk after controlling the firm-level effect. Our mediation tests suggest that individual auditor industry specialization decreases the risk of price crash by mitigating earnings manipulation. We further document that the negative association is more pronounced for firms that switch from non-specialist to specialist auditors. We also find some evidence that an auditor’s personal characteristics moderate the association between auditor industry specialization and crash risk. Our results remain robust to alternative measures of individual auditor industry specialization and sensitivity checks.

Purpose: The purpose of this paper is to examine the relation between financial statement comparability and corporate investment efficiency of a large sample of US firms. Design/methodology/approach: The authors use a large sample of US-listed firms from 1981 to 2013. The authors use several econometric methods including ordinary least square, firms fixed effects and mediation effects regression. Sensitivity tests that include the use of alternative measures of both the dependent and independent variables provide results that are consistent with the authors’ baseline model results. Findings: The authors find that financial statement comparability mitigates risks associated with both under-investment and over-investment. They also find that product market competition mediates the relation between financial statement comparability and investment efficiency. The authors consider this to be a function of a competitive environment, whereby firms normally disclose less private information. This in turn reduces the effect of financial statement comparability on investment efficiency. Conversely, where there are higher levels of product market competition, it is less likely that firms will under-invest. Their results are consistent with these predictions. Originality/value: The authors contribute to this growing field of research by providing evidence that financial statement comparability does in fact improve firms’ investment efficiency. Findings enhance our understanding of the relation between investment efficiency and financial statement comparability which is likely to have flow-on effects in terms of financial reporting quality and firm value. This study also contributes to research that links agency theory to financial statement comparability through an analysis of moral hazard and adverse selection tenets, and how it leads to reduced levels of investment inefficiency in a firm.

Concepts adapted from radio frequency devices have brought forth subwavelength scale optical nanoantenna, enabling light localization below the diffraction limit. Beyond enhanced light–matter interactions, plasmonic nanostructures conjugated with active materials offer strong and tunable coupling between localized electric/electrochemical/mechanical phenomena and far-field radiation. During the last two decades, great strides have been made in development of active plasmonic nanoantenna (PNA) systems with unconventional and versatile optical functionalities that can be engineered with remarkable flexibility. In this review, we discuss fundamental characteristics of active PNAs and summarize recent progress in this burgeoning and challenging subfield of nano-optics. We introduce the underlying physical mechanisms underpinning dynamic reconfigurability and outline several promising approaches in realization of active PNAs with novel characteristics. We envision that this review will provide unambiguous insights and guidelines in building high-performance active PNAs for a plethora of emerging applications, including ultrabroadband sensors and detectors, dynamic switches, and large-scale electrophysiological recordings for neuroscience applications.

Polychlorinated naphthalenes (PCNs) are globally transported, carcinogenic, persistent organic pollutants (POPs) that were recently added to the Stockholm Convention with 184 parties. The Tibetan Plateau plays an important role in the global transportation and distribution of POPs. Knowledge of PCN sources and transportation on the Tibetan Plateau is important for their control globally. In this study, we quantified the congener-specific concentrations of PCNs in lichen, moss, soil, and air samples collected on the Tibetan plateau and found that common lichens were effective biomonitors for predicting atmospheric PCNs in this area. The physiochemical properties of the PCNs, the temperatures, and the lichen lipid contents were identified as important factors influencing PCN partitioning between lichens and air. Lichen–air partitioning equations were established and used to predict PCN concentrations in air in Southeast Tibet. The lichens could be used as PCN biomonitors to clarify their spatial variations, sources, and transportation in the southeast of the plateau. PCN concentrations in lichens increased with altitude, suggesting that high-mountain cold-trapping influenced the PCN transportation behavior. Principal component analysis and linear discriminant analysis showed that the major source of PCNs in this region was long-range atmospheric transportation via the Indian monsoon in summer and wind from Southwest Asia in winter. This study provides a novel method using PCN congener profiles as fingerprints and statistical models for studying the geochemical effects of conditions in high-mountain regions on the contamination behaviors of 75 congeners of the notorious PCNs.

In the recent years, air pollution has become an alarming issue for human health in many rapidly growing megacities including Dhaka and Narayanganj. Herein, pollution status and health risk have been assessed by the road dusts collected from landfills in Dhaka and Narayanganj through determination of heavy metals including Pb, Cd, Cr, As, Cu, Ni, Zn and Mn using atomic absorption spectroscopy. The collected dust samples have been grouped into three sizes, for example, <300−>150, <150−>75 and < 75 μm, to assess the degree of heavy metal accumulation in the dust particles. The dust particles were accumulated with high concentrations of Pb and As at Matuail landfills, whereas Cd, Cr, Zn, and Mn concentrations were highest at Narayanganj landfills. The finer particles, for example 75 μm, accumulated substantial concentrations of heavy metals. Pollution index and pollution load index (PLI) results revealed that all of the sites were deteriorated by Pb, Cd, Cu, Zn and Ni. PLI results exhibited that the quality of the Matuail landfill area was severely deteriorated. In terms of non-carcinogenic health risk, the values of hazard quotient for ingestion were greater than those for inhalation and dermal pathways. For adult groups, hazard index values for the Matuail landfills and medical waste incineration sites were greater than 1, while for the children groups, the values for the same areas, including the Narayanganj landfills, were also larger than 1. These values were at least one order of magnitude higher for the children groups than for the adult groups. Given the results, it would be reasonable to draw the conclusion that non-carcinogenic health risks for children may be more prevalent in the relevant areas.

We examine whether regional social capital has any impact on idiosyncratic return volatility. Using US data, we find that firms headquartered in high social capital counties exhibit significantly lower idiosyncratic return volatility. This effect is more pronounced in the presence of financial reporting quality and corporate social responsibility. When we estimate the direct and indirect effects of social capital, our study reveals that the direct effect of social capital captures around 80% of the total effect. These findings suggest that firm-specific variables do not explain all of a firm’s idiosyncratic return volatility, but regional social capital also plays a role.JEL classification: G10, G12, G30, M14

The disposal of banana pseudostem waste creates substantial environmental concerns. To address this issue, it is crucial to explore the potential of converting this abundant waste into valuable industrial products. Therefore, this research was designed to explore the utilization of banana pseudostem fiber waste (BPW) in the development of a textile binder. Solvothermal digestion of pseudostem fibers into ammonia followed by neutralization with sulfuric acid resulted in viscous gel which was tested as a binder (BPW-binder) for the pigment dying process. Various parameters, including curing, washing fastness, tensile strength, stiffness, and light fastness, were examined to compare the performance of the two binders. The results showed that the BPW-binder performed similarly to the commercial Halzarin binder in terms of washing fastness and did not leave any stains on the multifibre strip. Both binders demonstrated excellent light fastness, with a rating of 8 on the blue wool scale for both cotton and cotton-polyester fabrics. However, there were slight variations in elongation and stiffness between the two binders with values ranging from 9.41 to 28.26% and 1.5 to 1.9 CMS across different fabric types, which were dependent on the fabric. Fourier transform infrared analysis revealed lignin amine salt peaks in the banana pseudostem-based BPW-binder, while scanning electron microscope images of BPW-binder treated fabrics confirmed suitable binder properties with a rough and ordered lamellar surface. This study demonstrates the potential of transforming banana pseudostem fiber waste into a sustainable textile binder through an efficient and straightforward process. The BPW-binder showed comparable performance to the synthetic commercial binder, indicating its potential as a sustainable replacement in the industry.

Bangladesh is one of the most populated countries in the world. More than 200 air quality index values were recorded in January and February since 2017, indicating that the air quality was unhealthy to very unhealthy. In this work, water-soluble inorganic anions (WSIAs) in fine particulate matter (PM2.5) in Dhaka, the capital of Bangladesh with a population of around 21 million, were evaluated. Accordingly, PM2.5was collected using a quartz filter coupled with an active air sampler set in Dhaka University campus, Bangladesh, during February 2023, to analyze WSIAs. The 24-h average PM2.5mass, 156?±?44.8?µg/m3, was almost nine times higher than the WHO limit values of 15.0?µg/m3and about three times higher than the Bangladesh Department of Environment limits of 65.0?µg/m3. Fluoride, chloride, bromide, nitrite, nitrate, phosphate, and sulfate were among the water-soluble ions that were determined using ion chromatography. While bromide and nitrite were found to be below the detection limit, the mean concentrations of fluoride, chloride, nitrate, phosphate, and sulfate were determined to be 0.086?±?0.010, 2.27?±?0.332, 10.2?±?1.29, 2.23?±?0.424, and 11.0?±?1.45?µg/m3, respectively. The highest levels of PM2.5and the relevant anions were determined to be present during February 9-10, 2023. Sulfate accounted for almost 43% of the anions in the overall PM2.5. According to the results of the statistical analysis, the high concentrations of sulfate and nitrate in PM2.5in Dhaka, Bangladesh, were primarily caused by sulfur-containing fossil fuels, especially sulfur-containing diesel, coal, and unfit automobiles, while the main sources of fluoride and chloride were fire retardants, burning of textile, and municipal solid wastes. All of these sources have the ability to produce PM2.5.

This article investigates whether the presence of advisory directors and monitoring directors varies across firm life cycle stages. We follow a parsimonious life cycle proxy based on the predicted behaviour of operating, investing and financing cash flows across the different life cycle stages that result from firm performance and the allocation of resources. Using an Australian sample, this study shows that compared to mature-stage firms, firms in the introduction, shake-out and decline stages have more advisory directors. With respect to the demand for monitoring directors, we find that compared to mature-stage firms, firms in the introduction, shake-out and decline stages have fewer monitoring directors on the board. We contribute to the literature on boards of directors by documenting that firms choose an optimal board structure based on their economic characteristics.JEL Classification: D22, G38, M14

Alzheimer’s Disease (AD) is the leading cause of dementia in the elderly. In healthy individuals, amyloid precursor protein (APP) is cleaved by α-secretase, generating soluble α-amyloid precursor protein (sAPPα), which contributes neuroprotective functions in the neuronal environment. In contrast, in the neurodegenerative environment of AD patients, amyloid-β-peptide (Aβ) of either 40 or 42 residues are generated by increased activity of β- and γ-secretase. These proteins amalgamate in specific regions of the brain, which disrupts neuronal functions and leads to cognitive impairment. Human umbilical cord blood cells (HUCBC) have proven useful as potential immunomodulatory therapies in various models of neurodegenerative diseases, including AD. Our most recent work studied the impact of umbilical cord blood serum (CBS) on modulation of sAPPα production. Heat-sensitive CBS significantly promoted sAPPα production, indicating that heat-sensitive factor(s) play(s) a role in this process. Liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis was used to determine the molecular source of α-secretase in purified CBS and aged blood serum (AgBS) fraction. Of the proteins identified, the subunits of C1 complex (C1q, C1r, and C1s) and alpha-2-macroglobulin showed significantly greater levels in purified α-CBS fraction (α-CBSF) compared with the AgBS fraction (AgBSF). Specifically, C1 markedly increased sAPPα and alpha-carboxyl-terminal fragment (α-CTF) production in a dose-dependent fashion, whereas C1q alone only minimally increased and C3 did not increase sAPPα production in the absence of sera. Furthermore, C1q markedly increased sAPPα and α-CTF, while decreasing Aβ, in CHO/APPwt cells cultured in the presence of whole sera. These results confirm our initial assumption that APP α-secretase activity in human blood serum is mediated by complement C1, opening a potential therapeutic modality for the future of AD.

Alzheimer’s disease (AD) is an age-related disorder that affects cognition. Our previous studies showed that the neuroprotective fragment of amyloid procurer protein (APP) metabolite, soluble APPα (sAPPα), interferes with β-site APP-cleaving enzyme 1 (BACE1, β-secretase) cleavage and reduces amyloid-β (Aβ) generation. In an attempt to identify approaches to restore sAPPα levels, we found that human cord blood serum (CBS) significantly promotes sAPPα production compared with adult blood serum (ABS) and aged blood serum (AgBS) in Chinese hamster ovary cells stably expressing wild-type human APP. Interestingly, CBS selectively mediated the α-secretase cleavage of human neuron-specific recombinant APP695in a cell-free system independent of tumor necrosis factor-α converting enzyme (TACE; a disintegrin and metalloproteinase domain-containing protein 17 [ADAM17]) and ADAM. Subsequently, using 3-step chromatographic separation techniques (i.e., diethylaminoethanol, size-exclusion, and ion-exchange chromatography), we purified and ultimately identified a CBS-specific fraction with enhanced α-secretase catalytic activity (termed αCBSF) and found that αCBSF has more than 3,000-fold increased α-secretase catalytic activity compared with the original pooled CBS. Furthermore, intracerebroventricular injection of αCBSF markedly increased cerebral sAPPα levels together with significant decreases in cerebral Aβ production and abnormal tau (Thr231) phosphorylation compared with the AgBS fraction with enhanced α-secretase activity (AgBSF) treatment in triple transgenic Alzheimer’s disease (3xTg-AD) mice. Moreover, AgBSF administered intraperitoneally to transgenic mice with five familial Alzheimer’s disease mutations (5XFAD) viaan osmotic mini pump for 6 weeks (wk) ameliorated β-amyloid plaques and reversed cognitive impairment measures. Together, our results propose the necessity for further study aimed at identification and characterization of α-secretase in CBS for novel and effective AD therapy.

Surface water is significantly contaminated by different dyes and pigments around the world due to rapid industrialization, especially textile/dyeing. Bangladesh's export-driven textile industry has grown dramatically over the past few decades, severely contaminating the nearby waterways. In this study, nano-zinc oxide was synthesized through precipitation method in the presence of PEG 400. SEM, XRD, and FTIR techniques were used to characterize the synthesized ZnO and revealed that it was pure, fiber-like, and essentially wurtzite. Nano-ZnO was used to remove the ionic dye acid blue 92 (AB 92) from aqueous solution in order to test its effectiveness as an adsorbent. The effects of pH, adsorbent dosage, AB 92 concentration, and contact time were investigated in order to optimize the adsorption process. According to correlation coefficients (R2) and the Redlich-Peterson model's fitting, the adsorption process followed the Freundlich isotherm at higher temperature and the Langmuir isotherm at lower temperature. The adsorption process was found to be endothermic and spontaneous. For adsorption thermodynamics, ΔH was found to be +20.32 kJmol-1, and ΔG was varied from −1.86 to −3.84 kJmol-1as the temperature increased from 291 to 317 K. The adsorption kinetics exhibited pseudo second order. The Temkin isotherm and Elovich kinetic models suggested that the process was chemisorption. The nano-ZnO showed tremendous re-usability as an adsorbent for the removal of AB 92. The results are suggesting for designing nano-ZnO-based methods to remove organic pollutants efficiently from industrial effluents for ecological and sustainable development. The mechanism of formation of nano-ZnO fiber and adsorption of anionic dye on nano-ZnO are also explored.

Alzheimer's disease (AD) is the fourth major cause of mortality in the elderly in the US and the leading cause of dementia worldwide. While pharmacological targets have been discovered, there are no true disease-modifying therapies. We have recently discovered that multiple low-dose infusions of human umbilical cord blood cells (HUCBCs) ameliorate cognitive impairments and reduce Aβ-associated neuropathology in PSAPP transgenic mice. However, the mechanism for these effects of HUCBCs remains unclear. In the present study, we examined whether monocytes, as important components of HUCBCs, would have beneficial outcomes on the reduction of AD-like pathology and associated cognitive impairments in PSAPP transgenic AD model mice. PSAPP mice and their wild-type littermates were treated monthly with an infusion of peripheral human umbilical cord blood cell (HUCBC)-derived monocytes over a period of 2 and 4 months, followed by behavioral evaluations, biochemical, and histological analyses. The principal findings of the present study confirmed that monocytes derived from HUCBCs (CB-M) play a central role in HUCBC-mediated cognition-enhancing and Aβ pathology-ameliorating activities. Most importantly, we found that compared with CB-M, aged monocytes showed an ineffective phagocytosis of Aβ, while exogenous soluble amyloid precursor protein α (sAPPα) could reverse this deficiency. Pretreating monocytes with sAPPα upregulates Aβ internalization. Our further studies suggested that sAPPα could form a heterodimer with Aβs, with the APP672-688(Aβ1-16) region being responsible for this effect. This in turn promoted binding of these heterodimers to monocyte scavenger receptors and thus promoted enhanced Aβ clearance. In summary, our findings suggest an interesting hypothesis that peripheral monocytes contribute to Aβ clearance through heterodimerization of sAPPα with Aβ. Further, declined or impaired sAPPaα production, or reduced heterodimerization with Aβ, would cause a deficiency in Aβ clearance and thus accelerate the pathogenesis of AD.

Induction of immunologic memory was assessed following primary vaccination with 10-valent pneumococcal nontypeable Haemophilus influenzaeprotein D conjugate vaccine (PHiD-CV).

DNA (pBluescript plasmid, 2.96 kbp) cleavage by Good’s buffers, which are extensively used in laboratories of chemistry, biochemistry, or biology, was studied by gel electrophoresis, CD spectra, ESR spectra, and CV in the presence of Au(III). Incubation of plasmid DNA with Good’s buffers and Au(III) resulted in DNA cleavage. DNA cleavage occurred due to the formation of nitrogen-centered cationic free radicals from the Good’s buffers in the presence of Au(III). The formation of the nitrogen-centered free radicals was confirmed by ESR spectroscopy. Gel electrophoresis results indicated that Form I and Form II were converted into Form III and a DNA fragment. The molecular weight of the DNA fragment was estimated ca. 1.47 kbp by DNA marker gel electrophoresis. ESR spectra were not observed from the Good’s buffers in the presence of other metal ions, such as Mn(II), Fe(III), Co(II), Ni(II), Zn(II), Pd(II), Cd(II), Hg(II), and Pb(II), resulting in no DNA cleavage. Gel electrophoresis results indicated a partial DNA cleavage during the incubation of DNA in the presence of Good’s buffers and Au(III). This is because the DNA cleavage reaction stopped at 15 min, since the radical lifetime is ca. 15 min. The intensities of the CD spectra at 270 nm decreased with time by 15 min upon the addition of Au(III), and a constant CD spectrum was observed after 15 min. Further addition of Au(III) showed an alternation of the CD spectra from positive ellipticity to negative ellipticity at 270 nm, suggesting significant DNA cleavage. The mechanism of DNA cleavage is discussed based on the gel electrophoresis, ESR, CD, and CV results.

Micropropagated potato plantlets (Solanum tuberosumcvs Acadia Russet, Red Gold, Red Pontiac, and Russet Burbank) were used to test the effects of exposure to ultra violet rays (UV) or inclusion of vitamin D3(cholecalciferol) in the test solution on plantlet calcium (Ca) uptake. Ca uptake was determined by measuring shoot tissue45Ca2+concentration inex vitroplantlets placed into test solutions containing radiolabelled calcium (45CaCl2). Shoot tissue45Ca2+concentration was very significantly increased in all cultivars exposed for 24 h to UV treatment compared with control plantlets. This increase in shoot45Ca2+concentration was similar (three cultivars) or greater (one cultivar) than that caused by 10 ing L−1vitamin D1in the test solution. When plantlets were exposed to UV, then placed for 24 h in the dark, significantly greater shoot45Ca2+concentrations occurred compared with plantlets tested immediately following treatment. This suggests that a change in the UV-elicited cellular product occurred during the dark interval that promoted more Ca uptake into plantlets.

Gold nanoparticle formation was found from tetrachloroaurate(III) in the presence of Good’s Buffers, such as 2-morpholinoethanesulfonic acid (MES) and 2-[4-(2-hydroxyethyl)-1-piperazinyl]ethanesulfonic acid (HEPES), which are used widely in laboratories for studies of analytical, inorganic, physical, and bio-chemistry as well as biology. The obtained gold nanoparticles were examined by Ultraviolet–Visible Spectroscopy (UV–vis), Dynamic Light Scattering (DLS) and Electrophoretic Light Scattering (ELS) in an aqueous system and by transmission electron microscopy (TEM) for particle morphologies. UV–vis spectra showed absorption maxima at ∼530 and ∼750 nm, depending on the buffer reagents and their concentration, pH, and ionic strength. The size and the surface zeta potential of the formed nanoparticles were 23 to 73 nm and −30 to −12 mV, respectively. The TEM pictures clearly indicated the formation of finely dispersed, chained, or aggregated gold nanoparticles, depending on the experimental conditions. The mechanism of gold nanoparticle formation was studied by the measurements of cyclic voltammetry (CV) and electron spin resonance (ESR). MES and HEPES showed a positive anodic peak at approximately +800 mV vs Ag/AgCl electrode, which indicated that these buffering agents have mild reducing ability. ESR results indicated the generation of nitrogen-centered cationic free radicals from these Good’s Buffers in the presence of Au(III), resulting in the formation of gold nanoparticles. A reaction mechanism is proposed.

Liquid scintillation counting (LSC) was used to screen six potato cultivars (Alpha, Bintje, Green Mountain, Kennebec, Russet Burbank, and Shepody) and two wild species(S. microdontumandS. kurtzianum)for ability to take up the tracer45Ca2+from treatment solutions containing high (15 mM) or low (5 mM) Ca2+levels. In vitro potato micropropagation, microtuberization, and tissue calcium content, determined by flame atomic absorption spectrophotometry (FAAS), were compared for the six cultivars when Murashige-Skoog basal medium Ca2+level was increased from 3, to 5 or 15 mM. All aspects of growth were improved when medium Ca2+level was 15 mM. Microtuber induction occurred earlier, leading to improved yield (19–31%), and microtuber tissue Ca2+concentration was greater (38–226%). Cv. Bintje was the most efficient genotype at accumulating Ca2+from treatment solutions or growth media containing high or low Ca2+levels. It could be identified as a calcium-packer using either LSC or FAAS screening.

Calcium uptake into potato plants was examined using test solutions containing 5% safranin dye (C20H19N4C1 mw 350.85) and the radiotracer45CaCl2. When minitubers were suspended in test solutions for up to 5 days, safranin moved into the outer pith tissues while45Ca2+was located throughout the pith. Ca2+is apparently taken up directly from the tubersphere by a slow diffusion process. Plantlets with one microtuber were used to investigate calcium uptake via basal roots.45Ca2+was well ahead of the safranin dye front in all plantlet stems.45Ca2+in shoot tips was significantly greater than in microtubers and no safranin entered the microtubers. Greenhouse-grown ex vitro plantlets with minitubers attached were used to determine the relative uptake by basal and stolon roots. Basal root feeding contributed significantly more45Ca2+to shoot tips and tubers than stolon root feeding while combined feeding gave the greatest shoot tip and tuber45Ca2+levels.

This paper investigates the association between related-party transactions (RPTs) and stock price crash risk in China. Our investigation is motivated by the controversy in the RPT literature over whether RPTs are value enhancing or opportunistic. Through the lens of stock price crash risk, we reveal that RPTs may violate the arm’s-length assumption of regular market-based transactions, impairing the representational faithfulness and verifiability of accounting data and, consequently, increasing the risk of future price crash. Importantly, we find that this detrimental economic consequence of RPTs is driven by abnormal RPTs that are opportunistic in nature. Our analyses also extend to operating RPTs, related-party loans, and two types of opportunistic RPTs: tunneling and propping. The positive association between RPTs and stock price crash risk is not mediated by financial reporting quality, suggesting that the risk factors associated with RPTs are operational. Our main results remain robust to a series of tests done to address the potential endogeneity between RPTs and stock price crash risk.

This paper conducts a meta-analysis of 182 published archival accounting and auditing studies on the corporate governance determinants of financial restatements. We aim to provide a focused and systematic examination of various internal and external corporate governance factors that may predict financial restatements. We do so by aggregating results statistically across individual studies and correcting statistical artifacts, thereby we provide findings that are much more precise than those of narrative reviews. We categorize the chosen governance variables into (a) audit firm and audit engagement characteristics; (b) gender, board attributes, and audit committee attributes; (c) CEO related attributes; (d) ownership structure variables; and (e) external corporate governance variables, and thus we generate a total of 37 separate corporate governance variables. Our results reveal that the governance mechanisms of Big N auditor choice, types, and timeliness of audit opinions and board independence are significantly and negatively associated with the occurrence of financial restatements. However, economic bonding between auditors and their clients, insider ownership, and firm complexity all increase the likelihood of restatements significantly. We hope that our findings will make a meaningful contribution to the literature on financial restatements and corporate governance by providing insights for regulators on the governance mechanisms that may require further scrutiny in combating the occurrence of financial restatements.

The peripheral rivers of Dhaka city became highly polluted because of industrialization and urbanization to a greater extent in the last few decades. Thus, an attempt has been taken to measure 48 elements in water of the river Buriganga using the ICP-MS method for the first time. Accordingly, it could be the reference values for future research in Bangladesh. Out of the 48 elements, the following metals are given more attention because of their detrimental effects on living organisms and for discussing their aquatic chemistry in polluted water body: Be, Na, Al, Cr, Mn, Fe, Ni, Cu, Zn, Cd, Ba, Hg, Pb, Bi and U. Results revealed that metals’ concentrations in water in the monsoon were less than that of the winter, however, Cr and Fe were found at below detection limits in the winter that is unexpected. Physicochemical parameters of the river water such as pH, dissolved oxygen play vital roles for hydrolysis reactions in the stagnant water body. Hydrolyzed products of metal ions having low values of solubility products ( K sp ), for example, iron(III)hydroxide, chromium(III)hydroxide, phase out through precipitation reactions. This study also detects and quantifies total concentrations of Hg and U in water of the river Buriganga for the first time. PCA and correlation matrix results provided potential sources of the relevant metals. Mechanisms of hydrolysis and precipitation reactions for metal ions in the polluted river water are also discussed.