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The current research analyzes cosmetic earnings management practices in emerging and developed markets before and after the global financial crisis. Using digital analysis, by applying Benford's Law the study analyzes the earnings adjustments that exceed a key reference point to determine whether earnings management anomaly exists or not? Based on a sample of 87165 firm-year observations of UK, US, Brazil, Russia, India, China and Pakistan listed corporations. Findings show that the managers of emerging markets have more incentive to manipulate earnings than their counterparts from developed markets. Further, the implementation of strict governance and legislative measures after the global financial crisis have significantly reduced the opportunistic behaviour of managers to manipulate earnings. However, the impact is lesser in emerging markets as compared to UK and US. The empirical findings of this research are useful for policy making and regulatory authorities, investors and other stakeholders as our findings shed light on the restriction of cosmetic earnings management practices. First study that tried to capture the cosmetic earnings management practices in both emerging and developed countries and in both pre and post financial crisis scenario.

This paper aims to develop a machine learning and deep learning-based real-time framework for detecting and recognizing human faces in closed-circuit television (CCTV) images. The traditional CCTV system needs a human for 24/7 monitoring, which is costly and insufficient. The automatic recognition system of faces in CCTV images with minimum human intervention and reduced cost can help many organizations, such as law enforcement, identifying the suspects, missing people, and people entering a restricted territory. However, image-based recognition has many issues, such as scaling, rotation, cluttered backgrounds, and variation in light intensity. This paper aims to develop a CCTV image-based human face recognition system using different techniques for feature extraction and face recognition. The proposed system includes image acquisition from CCTV, image preprocessing, face detection, localization, extraction from the acquired images, and recognition. We use two feature extraction algorithms, principal component analysis (PCA) and convolutional neural network (CNN). We use and compare the performance of the algorithms K-nearest neighbor (KNN), decision tree, random forest, and CNN. The recognition is done by applying these techniques to the dataset with more than 40K acquired real-time images at different settings such as light level, rotation, and scaling for simulation and performance evaluation. Finally, we recognized faces with a minimum computing time and an accuracy of more than 90%.

Extrapulmonary tuberculosis (EPTB) has received less attention than pulmonary tuberculosis due to its non-contagious nature. EPTB can affect any organ and is more prevalent in people living with HIV. Low- and middle-income countries are now facing the double burden of non-communicable diseases (NCDs) and HIV, complicating the management of patients with symptoms that could be compatible with both EPTB and NCDs. Little is known about the risk of death of patients presenting with symptoms compatible with EPTB. We included patients with a clinical suspicion of EPTB from a tertiary level hospital in Mbeya, Tanzania, to assess their risk of dying. A total of 113 (61%) patients were classified as having EPTB, and 72 (39%) as having non-TB, with corresponding mortality rates of 40% and 41%. Associated factors for mortality in the TB groups was hospitalization and male sex. Risk factors for hospitalization was having disease manifestation at any site other than lymph nodes, and comorbidities. Our results imply that NCDs serve as significant comorbidities amplifying the mortality risk in EPTB. To strive towards universal health coverage, focus should be on building robust health systems that can tackle both infectious diseases, such as EPTB, and NCDs.

With the proportion of tuberculosis cases that are extrapulmonary tuberculosis (EPTB) increasing in recent years, understanding and addressing factors contributing to the prolonged time to diagnosis (TTD) of EPTB patients is vital. We enrolled presumptive EPTB patients for a cohort study from 2018-2020 in Ujjain, India. Based on a structured questionnaire, the patients were interviewed for socio-demographic and clinical information, including previously visited health facilities (HF) for this illness. We analysed patients' TTD, healthcare access, and referral pathways. EPTB (54%) and non-TB (58%) patients visited dispensaries during their first visit to a formal HF. Patients visited multiple HFs, including dispensaries (54%) and regional hospitals (32%), during 1-4 visits but did not receive an appropriate diagnosis. Less than 2% of the patients accessed private HFs. Most of the adult EPTB (83%) and non-TB (76%) patients were self-referred to our study site, where they were diagnosed. Our statistical models highlighted low-middle income groups, longer distances and longer travel time to HFs, and potentially less-empowered occupations as housewives with a prolonged TTD. Patients with a longer wait, including travel time, had a shorter TTD. We found individual, societal-level, and structural barriers to healthcare access and utilisation and their association with diagnostic delay among adult and paediatric EPTB patients.

The diamondback moth, Plutella xylostella (Linnaeus) (Lepidoptera: Plutellidae), is a global pest of crucifer crops, mainly controlled with insecticides. However, this moth has shown populations from different geographical regions that are resistant to various synthetic insecticides, including organophosphates, pyrethroids, new molecules, and microbial-derived pesticides owing to repeated applications of these insecticides. This review is an effort to explore reported cases of insecticide resistance and mechanisms involved in P. xylostella throughout the world. It also includes a comprehensive overview of the mode of inheritance and fitness costs associated with the resistance of P. xylostella to different insecticides. Data from 20 research papers about field and laboratory resistance to various organochlorines and pyrethroids, and 54 papers on resistance to new chemical and microbial insecticides, showed the varying resistance levels in P. xylostella from different parts of the world. Cross-resistance results were also presented in 17 published papers. Moreover, the collected data of 25 research publications about resistance inheritance to various insecticides revealed that 84% of the published papers confirmed autosomal resistance, while sex-linked inheritance was confirmed in only 16% of the published literature. An association of high fitness costs with disadvantageous biological characteristics was evident from the summarized data of eight different studies. Studies about resistance mechanisms were presented in 32 published papers which depicted that metabolic resistance was prevalent over target sites. This effort will contribute to developing an effective management program to mitigate the resistance of P. xylostella to the main pest control strategies.

Choroidal neovascularisation (CNV) is a condition characterised by the proliferation of abnormal blood vessels within the choroid. These vessels tend to leak blood and fluid into the adjacent tissues, thereby causing harm to the retina and posing a threat to visual function. The infrequency of CNV in children can be attributed to its predominant association with age-related macular degeneration (AMD). The incidence of CNV in paediatric patients is generally considered to be very low, with rates often cited as being less than one case per 100,000 individuals annually. We present a 10-year-old female who was referred by an optician due to a one-month history of unilateral blurred vision in her left eye, leading to difficulties in reading the school board. The patient had no other past medical, trauma, or ocular history, and her family and developmental history were non-significant.  On examination, the patient's visual acuity measured 6/6 in the right eye and 6/9 in the left eye. Initial dilated fundal examination revealed a yellow hypopigmented, raised subfoveal lesion with irregular borders in her left eye; however, there was no evidence of neovascularisation or haemorrhage. The patient presented two weeks later with a sudden visual drop of 6/60. Fundal examination showed a new haemorrhage in the left eye, and subretinal fluid (SRF) was noted within the macula. Optical coherence tomography (OCT) and OCT angiography (OCT-A) identified an increase in SRF and confirmed a solitary CNV. The child received three loading doses of intravitreal anti-vascular endothelial growth factor (anti-VEGF) at one-month intervals, leading to complete resolution of SRF and haemorrhage on OCT. Consequently, the patient's visual acuity improved to 6/12. In summary, idiopathic CNV, although rare in paediatric patients, must be promptly diagnosed and adequately treated to guarantee resolution.

We investigate the empirical nexus between financial inclusion and economic growth for an extended sample of 21 Asian countries spanning over a period from 2004 to 2019. Further, we also conducted a sub-sample analysis by dividing the overall samples into developed and developing countries. Our results reveal a significant positive long-term impact of financial inclusion on economic growth in Asia. Our pair-wise causality test shows bidirectional causality between financial inclusion and economic development. Our robust results are consistent across various estimation techniques. Our findings suggest that the influence of financial inclusion on economic growth is more pronounced in developing countries compared to developed countries. Our results hold across subsamples. These findings posit important policy insights to enable the policy-makers in designing policies that ensure efficient and inclusive financial system on an equitable basis to achieve sustainable economic growth. JEL classification: O16; O57; C38; C33

Over the past few years, the application and usage of Machine Learning (ML) techniques have increased exponentially due to continuously increasing the size of data and computing capacity. Despite the popularity of ML techniques, only a few research studies have focused on the application of ML especially supervised learning techniques in Requirement Engineering (RE) activities to solve the problems that occur in RE activities. The authors focus on the systematic mapping of past work to investigate those studies that focused on the application of supervised learning techniques in RE activities between the period of 2002–2023. The authors aim to investigate the research trends, main RE activities, ML algorithms, and data sources that were studied during this period. Forty‐five research studies were selected based on our exclusion and inclusion criteria. The results show that the scientific community used 57 algorithms. Among those algorithms, researchers mostly used the five following ML algorithms in RE activities: Decision Tree, Support Vector Machine, Naïve Bayes, K‐nearest neighbour Classifier, and Random Forest. The results show that researchers used these algorithms in eight major RE activities. Those activities are requirements analysis, failure prediction, effort estimation, quality, traceability, business rules identification, content classification, and detection of problems in requirements written in natural language. Our selected research studies used 32 private and 41 public data sources. The most popular data sources that were detected in selected studies are the Metric Data Programme from NASA, Predictor Models in Software Engineering, and iTrust Electronic Health Care System.

Graphene twistronics have recently gained significant attention due their superconductive behavior as a consequence of their tunable electronic properties. Although the electronic properties of twisted graphene have been extensively studied, the mechanical properties and integrity of twisted trilayer graphene (tTLG) under loading is still elusive. We investigated the fracture mechanics of tTLG with a twist angle of ±1.53° utilizing molecular dynamics simulation. This twist angle was chosen because it is known to exhibit highly superconductive behavior. The results indicate that tTLG does not preserve the excellent mechanical properties typically associated with graphene, with toughness and fracture strain values much lower in comparison. The Young’s modulus was an exception with values relatively close to pristine graphene, whereas the tensile strength was found to be roughly half of the intrinsic strength of graphene. The fracture toughness, fracture strain and strength converge as the crack length increases, reaching 0.26 J/m3, 0.0217 and 39.9 GPa at a crack length of 8 nm, respectively. The Griffth critical strain energy is 19.98 J/m2 and the critical stress intensity factor Kc is 4.47 MPa M1/2, in good agreement with that of monolayer graphene in the experiment. Our atomic insights might be helpful in the material design of twisted trilayer graphene-based electronics.

Background The economic crisis that began in 2008 has severely affected Southern (Greece, Italy, Portugal, Spain) Western European (SWE) countries of Western Europe (WE) and may have affected ongoing efforts to eliminate viral hepatitis. This study was conducted to investigate the impact of the economic crisis on the burden of HBV and HCV disease. Methods Global Burden of Diseases 2019 data were used to analyse the rates of epidemiological metrics of HBV and HCV acute and chronic infections in SWE and WE. Time series modelling was performed to quantify the impact of healthcare expenditure on the time trend of HBV and HCV disease burden in 2000–2019. Results Declining trends in incidence and prevalence rates of acute HBV (aHBV) and chronic HBV were observed in SWE and WE, with the pace of decline being slower in the post-austerity period (2010–2019) and mortality due to HBV stabilised in SWE. Acute HCV (aHCV) metrics and chronic HCV incidence and mortality showed a stable trend in SWE and WE, whereas the prevalence of chronic HCV showed an oscillating trend, decreasing in WE in 2010–2019 ( p  < 0.001). Liver cancer due to both hepatitis infections showed a stagnant burden over time. An inverse association was observed between health expenditure and metrics of both acute and chronic HBV and HCV. Conclusions Epidemiological metrics for HBV and HCV showed a slower pace of decline in the post-austerity period with better improvement for HBV, a stabilisation of mortality and a stagnant burden for liver cancer due to both hepatitis infections. The economic crisis of 2008 had a negative impact on the burden of hepatitis B and C. Elimination of HBV and HCV by 2030 will be a major challenge in the SWE countries.