In present study, ZnFe2O4 nanoparticles were encapsulated into carbon (C) matrix to synthesize the superparamagnetic carbon/ZnFe2O4 (C/ZnFe2O4) nanocomposites by refluxing method. The microstructure ...and magnetic behavior of nanocomposites have been discussed using Fourier transform infrared spectrogram (FTIR), X-ray diffractometer (XRD), vibrating sample magnetometer (VSM), Brunauer-Emmett-Teller (BET) method, field emission scanning electron microscope (FESEM), high resolution transmission electron microscope (HRTEM) and electron dispersive X-ray (EDX) techniques. BET surface area and pore diameter of C/ZnFe2O4 nanocomposite was found to be 280.87m2/g and 2.0nm, respectively. The C/ZnFe2O4 nanocomposite has been explored as adsorbent for the amputation of naphthalene and 2-naphthol from aquatic system. The influence of various parameters were studied and optimized for maximum uptake of pollutants. The isotherms and kinetic models have been examined to correlate and linearly fitting the experimental data. Langmuir and pseudo-first-order model provides better linear fit (R2=0.99) as compared to other models. Furthermore, thermodynamic parameters such as ∆H°, ∆S° and ∆G° were calculated to determine the nature of adsorption. The adsorption of pollutants has found to be endothermic, feasible and spontaneous in nature. The four cycles of repetitive testing were attempted in different desorbing agents and C/ZnFe2O4 nanocomposite was efficiently regenerated using NaOH-ethanol. Thus, this work presents a neoteric benchmark for the sorption of poly-aromatic hydrocarbons (PAHs) and delivers a new perspective for eliminating PAHs from unhygienic water for environmental reclamation.
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•Carbon/ZnFe2O4 has been synthesized by facile refluxing scheme.•Bio-material employed as precursor for carbon•Carbon-nanocomposite is super-paramagnetic due to its negligible coercivity (Hc) and remanent magnetization (Mr).•The C/ZnFe2O4 acts as a virtuous adsorbent for PAHS pollutants.•NaOH-EtOH acts as good desorbing agent for PAHs.
Insufficiency of vitamin D, during pregnancy, is a common cause of various pregnancy-related complications. Despite such insufficiency being frequently reported among South Asian pregnant women, the ...absence of systematic review and meta-analysis renders the true extent of this problem being poorly characterised. In this systematic review, three main databases (PubMed, Scopus and Google Scholar) were searched for original studies. We included original studies published between 1January 2001 to 31 December 2019, conducted on pregnant women who lived in South Asian countries and reported the prevalence of vitamin D insufficiency among the study participants. Twenty studies with a total of 7804 participants from four South Asian countries finally met our selection criteria. Overall pooled prevalence of insufficiency was 65 % (95 % CI: 51 %, 78 %) with a significant heterogeneity (I
= 99·37 %;
= 0·00). The average level of vitamin D ranged from 9 ng/ml to 24·86 ng/ml with a weighted mean of 16·37 ng/ml (weighted standard deviation 7·13 ng/ml). The highest prevalence of insufficiency was found in Pakistan (76 %) followed by India (67 %), Bangladesh (64 %) and Nepal (14 %). Results obtained in this study suggest that vitamin D insufficiency is highly prevalent among South Asian pregnant women. Being the first systematic review in this region, findings from this study will help the future studies and strengthen the evidence for policymakers to develop effective mitigation strategies.
•Waste to Energy Recovery Assessment (WERA) framework stochastically analyzes waste-to-energy (WtE) systems feasibility.•Hybrid WtE can be feasible in Karachi (Pakistan) and in Delhi (India) with ...higher feed-in tariffs and waste collection fees.•Municipal waste (with recyclable paper and plastics removed) can generate up to 290 GWh in Karachi and 60 GWh in Delhi.•WtE social costs and benefits should be considered from the environment, public health, and waste management policy nexus.
Waste collection, treatment, and safe disposal systems are rare in developing countries as these processes and systems have been mostly viewed from a cost-centric perspective in conjunction with weak or non-existent environmental policies. Consequently, solid waste generation has turned into a problem of significant proportions in many countries with severe degradation of land, air, and water quality and adverse effects on environment and public health. New waste-to-energy (WtE) systems using municipal solid waste (MSW) to produce energy (based on emerging technologies beyond traditional incineration), can serve as a useful bridge towards sustainable waste management. In this paper, a quantitative Waste to Energy Recovery Assessment (WERA) framework is used to stochastically analyze the feasibility of WtE in selected cities in Asia. Future policy measures of feed-in tariffs, payments for avoided pollution, and higher waste collection fees are assessed to evaluate if WtE systems can be made self-sustaining investments. The results show that WtE systems can generate up to 290 GWh of electricity in Karachi, and up to 60 GWh in Delhi from municipal waste feedstock from which recyclables (such as paper and plastics) have been removed. Net Present Value (NPV) estimation shows that hybrid WtE technology systems can be feasible in Karachi and Delhi with policy support, however Jakarta’s case is challenging due to higher costs. Future investments for waste systems should use holistic evaluations that incorporate key social benefits and costs – not only of energy generation but also of emissions reductions and impacts on public health – and identify necessary policy support for ensuring viable and sustainable solutions.
Histone protein modifications control fate determination during normal development and dedifferentiation during disease. Here, we set out to determine the extent to which dynamic changes to histones ...affect the differentiated phenotype of ordinarily quiescent adult glomerular podocytes. To do this, we examined the consequences of shifting the balance of the repressive histone H3 lysine 27 trimethylation (H3K27me3) mark in podocytes. Adriamycin nephrotoxicity and subtotal nephrectomy (SNx) studies indicated that deletion of the histone methylating enzyme EZH2 from podocytes decreased H3K27me3 levels and sensitized mice to glomerular disease. H3K27me3 was enriched at the promoter region of the Notch ligand Jag1 in podocytes, and derepression of Jag1 by EZH2 inhibition or knockdown facilitated podocyte dedifferentiation. Conversely, inhibition of the Jumonji C domain-containing demethylases Jmjd3 and UTX increased the H3K27me3 content of podocytes and attenuated glomerular disease in adriamycin nephrotoxicity, SNx, and diabetes. Podocytes in glomeruli from humans with focal segmental glomerulosclerosis or diabetic nephropathy exhibited diminished H3K27me3 and heightened UTX content. Analogous to human disease, inhibition of Jmjd3 and UTX abated nephropathy progression in mice with established glomerular injury and reduced H3K27me3 levels. Together, these findings indicate that ostensibly stable chromatin modifications can be dynamically regulated in quiescent cells and that epigenetic reprogramming can improve outcomes in glomerular disease by repressing the reactivation of developmental pathways.
Backscatter communication holds potential for ubiquitous and low-cost connectivity among low-power IoT devices. To avoid interference between the carrier signal and the backscatter signal, recent ...works propose a frequency-shifting technique to separate these two signals in the frequency domain. Such proposals, however, have to occupy the precious wireless spectrum that is already overcrowded, and increase the power, cost, and complexity of the backscatter tag. In this paper, we revisit the classic ON-OFF Keying (OOK) modulation and propose Aloba, a backscatter system that takes the ambient LoRa transmissions as the excitation and piggybacks the in- band OOK modulated signals over the LoRa transmissions. Our design enables the backscatter signal to work in the same frequency band of the carrier signal, meanwhile achieving flexible data rate at different transmission range. The key contributions of Aloba include: i) the design of a low-power backscatter tag that can pick up the ambient LoRa signals from other signals; ii) a novel decoding algorithm to demodulate both the carrier signal and the backscatter signal from their superposition. We further adopt link coding mechanism and interleave operation to enhance the reliability of backscatter signal decoding. We implement Aloba and conduct head-to-head comparison with the state-of-the-art LoRa backscatter system PLoRa in various settings. The experiment results show Aloba can achieve 39.5-199.4 Kbps data rate at various distances, 10.4-<inline-formula> <tex-math notation="LaTeX">52.4\times </tex-math></inline-formula> higher than PLoRa.
ObjectivesEssential healthcare workers (HCW) uniquely serve as both COVID-19 healers and, potentially, as carriers of SARS-CoV-2. We assessed COVID-19-related stigma and bullying against HCW ...controlling for social, psychological, medical and community variables.DesignWe nested an analytical cross-sectional study of COVID-19-related stigma and bullying among HCW within a larger mixed-methods effort assessing COVID-19-related lived experience and impact. Adjusted OR (aOR) and 95% CIs evaluated the association between working in healthcare settings and experience of COVID-19-related bullying and stigma, controlling for confounders. Thematic qualitative analysis provided insight into lived experience of COVID-19-related bullying.SettingWe recruited potential participants in four languages (English, Spanish, French, Italian) through Amazon Mechanical Turk’s online workforce and Facebook.ParticipantsOur sample included 7411 people from 173 countries who were aged 18 years or over.FindingsHCW significantly experienced more COVID-19-related bullying after controlling for the confounding effects of job-related, personal, geographic and sociocultural variables (aOR: 1.5; 95% CI 1.2 to 2.0). HCW more frequently believed that people gossip about others with COVID-19 (OR: 2.2; 95% CI 1.9 to 2.6) and that people with COVID-19 lose respect in the community (OR: 2.3; 95% CI 2.0 to 2.7), both which elevate bullying risk (OR: 2.7; 95% CI 2.3 to 3.2, and OR: 3.5; 95% CI 2.9 to 4.2, respectively). The lived experience of COVID-19-related bullying relates frequently to public identities as HCW traverse through the community, intersecting with other domains (eg, police, racism, violence).InterpretationAfter controlling for a range of confounding factors, HCW are significantly more likely to experience COVID-19-related stigma and bullying, often in the intersectional context of racism, violence and police involvement in community settings.
Burst suppression (BS) is an electroencephalography (EEG) pattern in which there are isoelectric periods interspersed with bursts of cortical activity. Targeting BS through anaesthetic administration ...is used as a tool in the neuro-intensive care unit but its relationship with cerebral blood flow (CBF) and cerebral autoregulation (CA) is unclear. We performed a systematic scoping review investigating the effect of BS on CBF and CA in animals and humans.
We searched MEDLINE, BIOSIS, EMBASE, SCOPUS and Cochrane library from inception to August 2022. The data that were collected included study population, methods to induce and measure BS, and the effect on CBF and CA.
Overall, there were 66 studies that were included in the final results, 41 of which examined animals, 24 of which examined humans, and 1 of which examined both. In almost all the studies, BS was induced using an anaesthetic. In most of the animal and human studies, BS was associated with a decrease in CBF and cerebral metabolism, even if the mean arterial pressure remained constant. The effect on CA during periods of stress (hypercapnia, hypothermia, etc.) was variable.
BS is associated with a reduction in cerebral metabolic demand and CBF, which may explain its usefulness in patients with brain injury. More evidence is needed to elucidate the connection between BS and CA.
Nine neurodegenerative diseases are caused by expanded polyglutamine (polyQ) tracts in different proteins, such as huntingtin in Huntington's disease and ataxin 3 in spinocerebellar ataxia type 3 ...(SCA3). Age at onset of disease decreases with increasing polyglutamine length in these proteins and the normal length also varies. PolyQ expansions drive pathogenesis in these diseases, as isolated polyQ tracts are toxic, and an N-terminal huntingtin fragment comprising exon 1, which occurs in vivo as a result of alternative splicing, causes toxicity. Although such mutant proteins are prone to aggregation, toxicity is also associated with soluble forms of the proteins. The function of the polyQ tracts in many normal cytoplasmic proteins is unclear. One such protein is the deubiquitinating enzyme ataxin 3 (refs 7, 8), which is widely expressed in the brain. Here we show that the polyQ domain enables wild-type ataxin 3 to interact with beclin 1, a key initiator of autophagy. This interaction allows the deubiquitinase activity of ataxin 3 to protect beclin 1 from proteasome-mediated degradation and thereby enables autophagy. Starvation-induced autophagy, which is regulated by beclin 1, was particularly inhibited in ataxin-3-depleted human cell lines and mouse primary neurons, and in vivo in mice. This activity of ataxin 3 and its polyQ-mediated interaction with beclin 1 was competed for by other soluble proteins with polyQ tracts in a length-dependent fashion. This competition resulted in impairment of starvation-induced autophagy in cells expressing mutant huntingtin exon 1, and this impairment was recapitulated in the brains of a mouse model of Huntington's disease and in cells from patients. A similar phenomenon was also seen with other polyQ disease proteins, including mutant ataxin 3 itself. Our data thus describe a specific function for a wild-type polyQ tract that is abrogated by a competing longer polyQ mutation in a disease protein, and identify a deleterious function of such mutations distinct from their propensity to aggregate.
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate environment model, and then ...plan to maximize reward. Unfortunately, learning algorithms often recover a model that is too inaccurate to support planning or too large and complex for planning to succeed; or they require excessive prior domain knowledge or fail to provide guarantees such as statistical consistency. To address this gap, we propose a novel algorithm which provably learns a compact, accurate model directly from sequences of action-observation pairs. We then evaluate the learner by closing the loop from observations to actions. In more detail, we present a spectral algorithm for learning a predictive state representation (PSR), and evaluate it in a simulated, vision-based mobile robot planning task, showing that the learned PSR captures the essential features of the environment and enables successful and efficient planning. Our algorithm has several benefits which have not appeared together in any previous PSR learner: it is computationally efficient and statistically consistent; it handles high-dimensional observations and long time horizons; and, our close-the-loop experiments provide an end-to-end practical test.
This paper presents an accurate and robust real-time FER system. In this system, an unsupervised technique based on active contour (AC) model is adopted in order to detect and extract the human faces ...automatically from the facial expression frames. In this model, the combination of two energy functions like Chan-Vese (CV) energy and Bhattacharyya distance functions were exploited that not only minimize the dissimilarities within the object (face) but also maximize the distance between the object (face) and background. Moreover, we extracted the facial features by proposing a new feature extraction method in order to solve the limitations of the previous works of the feature extraction. Similarly, in this system, we also proposed the usage of a robust non-linear feature selection method called stepwise linear discriminant analysis (SWLDA) that focuses on selecting localized features from facial expression images and discriminating their classes based on regression values (i.e., partial
F-test
). Finally, the system has been trained by employing hidden Markov model (HMM) to label the expressions. Unlike most of the previous works that were evaluated using a single dataset in a controlled environment, the performance of the proposed system have been assessed by employing three different spontaneous datasets that have been collected in naturalistic environments. 10–fold cross validation rule has been exploited for the whole experiments. In last, a set of experiments were also performed to assess the effectiveness of each module of the proposed approaches separately. The proposed system achieved weighted average recognition rate (95%) across three different YouTube-based datasets against the existing state-of-the-art methods.
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