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In How Algorithm-Assisted Decisionmaking Is Influencing Environmental Law and Climate Adaptation, Prof. Sonya Ziaja provides a useful framework to analyze whether an algorithm-assisted decisionmaking (AADM) tool and its design process [...]

Given the recent state of affairs, many organizations have adopted remote working conditions as a norm. Various challenges affecting quality of life are impacted by working from home. The aim of this literature review is to provide further insight into the impacts that working from home (WFH) had on the productivity and quality of life of workers across occupations. Review of the literature showed that autonomy has a significant impact upon work engagement, which in turn leads to a significant positive association on worker happiness. In addition to autonomy and work engagement, research indicates that the convenience of WFH also is positively associated with work engagement. Since remote working conditions are likely to remain, it is important for organizations to understand the impact of remote conditions on the quality of life of employees.

How disorder affects magnetic ordering is always an intriguing question, and it becomes even more interesting in the recently rising high entropy oxides due to the extremely high disorder density. However, due to the lack of high-quality single crystal samples, the strong compositional disorder effect on magnetic transition has not been deeply investigated. In this work, we have successfully synthesized high-quality single crystalline high entropy spinel ferrites (Mg0.2Mn0.2Fe0.2Co0.2Ni0.2)xFe3-xO4. Our findings from high-temperature magnetization and neutron diffraction experiments showed ferrimagnetic transitions at 748, 694, and 674 K for xvalues of 1, 1.5, and 1.8, respectively. Notably, the magnetic transition almost showed no broadening for xvalues of 1 and 1.5, compared to Fe3O4. Extended X-ray absorption fine structure measurements provided insights into the elemental distribution among the octahedral and tetrahedral sites. The random distribution of elements across these sites reduced the formation of local clusters and short-range orders, enhancing sample homogeneity and preserving the sharpness of the magnetic transition, despite bond length variation. Our study not only marks the first successful synthesis of an HEO bulk single crystal exhibiting long-range magnetic order but also sheds light on the interaction between high configurational entropy and magnetic orderings. This opens new avenues for future research and applications of magnetic high entropy oxides.

The present study reports the complete mitogenome sequence of Indoplanorbis exustusfor the first time. The length of the mitogenome was 13,742 bp. It consisted of 13 Protein-coding genes (PCGs), 2 ribosomal RNAs, and 22 transfer RNAs. The longest intergenic spacer of 41 bp was seen between COX3and trnI. The heavy strand of the mitogenome had higher A + T content. trnQ, trnL, ATP8, trnN, ATP6, trnR, trnE, 12 S, trnM, ND3, trnS2, trnT, and COX3were encoded on the light strand. The remaining genes were encoded on the heavy strand. The PCGs utilized different start codons. Incomplete stop codons were present for CytB, ND4L, ATP8, ATP6, ND3, ND4, COX3, and ND2. There was a total of 12 intergenic spacers and 11 gene overlaps. Of the twenty-two tRNAs, trnV, trnA, trnD, trnC, trnF, trnP, trnH, trnQ, trnL2, trnN, trnR, trnM, trnT, trnI, and trnKshowed typical clover-leaf secondary structure.

Non-reciprocal charge transport has gained significant attention due to its potential in exploring quantum symmetry and its promising applications. Traditionally, non-reciprocal transport has been observed in the longitudinal direction, with non-reciprocal resistance being a small fraction of the ohmic resistance. Here we report a transverse non-reciprocal transport phenomenon featuring a quadratic current–voltage characteristic and divergent non-reciprocity, termed the non-reciprocal Hall effect. This effect is observed in microscale Hall devices fabricated from platinum (Pt) deposited by a focused ion beam on silicon substrates. The transverse non-reciprocal Hall effect arises from the geometrically asymmetric scattering of textured Pt nanoparticles within the focused-ion-beam-deposited Pt structures. Notably, the non-reciprocal Hall effect generated in focused-ion-beam-deposited Pt electrodes can propagate to adjacent conductors such as Au and NbP through Hall current injection. Additionally, this pronounced non-reciprocal Hall effect facilitates broadband frequency mixing. These findings not only validate the non-reciprocal Hall effect concept but also open avenues for its application in terahertz communication, imaging and energy harvesting.

This study tackles the pressing issue of predicting suicidal tendencies on Twitter by introducing an inventive methodology that integrates Generative Adversarial Networks (GAN), Deep Learning methodologies, Word Embedding Fusion, and Genetic Algorithms. The framework is devised to capitalize on the unique strengths of each element, resulting in a more resilient and precise predictive model. The process initiates with the aggregation of Twitter posts, which undergo preprocessing and transformation into word embeddings. These embeddings establish the groundwork for subsequent stages. The utilization of GAN comes into play for generating synthetic data, enriching the dataset’s diversity and volume—an essential aspect for the effective training of deep learning models. Concurrently, a deep learning architecture is employed to decipher intricate patterns within the data. The harmonization of GAN-generated samples and genuine data optimizes the model's performance, ensuring a comprehensive comprehension of features indicative of suicidal ideation. The integration of Word Embedding Fusion further enhances the model by amalgamating information from diverse embedding techniques, leveraging their distinct perspectives. This step boosts the model’s capacity to interpret and generalize patterns, thereby contributing to an augmented prediction accuracy. The inclusion of Genetic Algorithms introduces an evolutionary optimization layer to the process. Genetic Algorithms play a crucial role in fine-tuning model parameters, optimizing overall performance by iteratively evolving candidate solutions. This not only enhances the model's predictive capabilities but also facilitates adaptability to the varied and dynamic linguistic expressions found on Twitter. Our work distinguishes itself from existing methodologies through this comprehensive approach that encompasses GAN, Deep Learning, Word Embedding Fusion, and Genetic Algorithm. The amalgamation of these techniques amplifies the predictive accuracy and resilience of the model, exhibiting promising results in the challenging task of predicting suicidal tendencies on Twitter. The adaptability of the proposed framework positions it as a potent tool for real-world applications, aiding in the timely identification and intervention in potential cases of self-harm.

COVID-19 caused a pathetic situation worldwide which led to public health crises, economic crises, employment losses, and mental anxiety. Social media websites are being inundated with reports on the virus, which has led to a variety of perspectives, thoughts, and emotions being expressed and experienced by social media sources. Taking advantage of the amount of information available, an analysis of sentiments user opinions expressed can be done on social networks. Sentiment Analysis is widely used in social media platforms for understanding the user’s expressions and sentiments. In this work, we extricate the information from Twitter utilizing search words, a python API called tweepy, pre-process it, and perform the word embedding process. The Word Embedding process is the replacement for the one-hot encoding technique, which converts the given into the form of vectors by tokenizing them as words and also spotting the relation among the words. Word Embedding Techniques such as Word2Vec, Glove, and FastText are used to convert the text into vectors which are then fed to the Artificial Neural Network (ANN) Models for training. Valance Aware Dictionary and sentiment Reasoner (VADER) are used to detecting suicide propensity in tweets as positive, negative, and neutral after which the user can be notified and solutions are provided. As a result, we will be able to figure out the user’s suicidal feelings and emotions during the pandemic situation. This research is used for comparing different word embedding techniques and predicting the suicide inclination of the tweets using the word embedding vectors and the neural network models.

This paper presents an experimental assessment of event-triggered sliding mode control (ET-SMC) on a Quadcopter for trajectory tracking. Sufficient triggering conditions using Lyapunov analysis and a lower bound of inter-event time to avoid Zeno behaviour are derived to ensure robust stability. Real-time flights are performed for tracking constant and time-varying trajectories. Results reveal that while using the proposed controller, there is a significant reduction in the number of updates implying a substantial saving in the computations.

Objectives. To assess whether the Affordable Care Act's (ACA) dependent coverage health insurance mandate had a spillover impact on young adult dental insurance coverage and whether any observed effects varied by household income. Data. Medical Expenditure Panel Surveys from 2006 through 2011. Study Design. We employed a difference-in-difference regression approach comparing changes in insurance rates for young adults ages 19-25 years to changes in insurance rates for adults ages 27-30 years. Separate regressions were estimated by categories of household income as a percentage of the Federal Poverty Level (FPL) to understand whether the mandate had heterogeneous spillover effects. Results. Private dental insurance increased by 6.7 percentage points among young adults compared to a control group of 27-30-year olds. Increases were concentrated at middle-income levels (125-400 percent FPL). Conclusions. The dependent coverage mandate provision of the Affordable Care Act has not only increased health insurance rates among young adults but also dental insurance coverage rates. Key Words. Affordable Care Act, dependent coverage mandate, dental insurance, The Patient Protection and Affordable Care Act (ACA) law that passed in 2010 includes many direct changes to the health insurance market and represents the most comprehensive overhaul of the [...]

Toward the goal of achieving superlubricity, or near-zero friction, in industrially relevant material systems, solution-processed multilayer Ti3C2Tx-MoS2blends are spray-coated onto rough 52100-grade steel surfaces as a solid lubricant. The tribological performance was assessed in a ball-on-disk configuration in a unidirectional sliding mode. The test results indicate that Ti3C2Tx-MoS2nanocomposites led to superlubricious states, which has hitherto been unreported for both individual pristine materials, MoS2and Ti3C2Tx, under macroscale sliding conditions, indicating a synergistic mechanism enabling the superlative performance. The processing, structure, and property correlation were studied to understand the underlying phenomena. Raman spectroscopy, scanning electron microscopy, and transmission electron microscopy revealed the formation of an in siturobust tribolayer that was responsible for the performance at high contact pressures (>1.1 GPa) and sliding speeds (0.1 m/s). This report presents the lowest friction obtained by either MoS2or MXene or any combination of the two so far.

High-performance energy storage devices (HPEDs) play a critical role in the realization of clean energy and thus enable the overarching pursuit of nonpolluting, green technologies. Supercapacitors are one class of such lucrative HPEDs; however, a serious limiting factor of supercapacitor technology is its sub-par energy density. This report presents hitherto unchartered pathway of physical deformation, chemical dealloying, and microstructure engineering to produce ultrahigh-capacitance, energy-dense NiMn alloy electrodes. The activated electrode delivered an ultrahigh specific-capacitance of 2700 F/cm3at 0.5 A/cm3. The symmetric device showcased an excellent energy density of 96.94 Wh/L and a remarkable cycle life of 95% retention after 10,000 cycles. Transmission electron microscopy and atom probe tomography studies revealed the evolution of a unique hierarchical microstructure comprising fine Ni/NiMnO3nanoligaments within MnO2-rich nanoflakes. Theoretical analysis using density functional theory showed semimetallic nature of the nanoscaled oxygen-vacancy-rich NiMnO3structure, highlighting enhanced carrier concentration and electronic conductivity of the active region. Furthermore, the geometrical model of NiMnO3crystals revealed relatively large voids, likely providing channels for the ion intercalation/de-intercalation. The current processing approach is highly adaptable and can be applied to a wide range of material systems for designing highly efficient electrodes for energy-storage devices.

The hybrid multiphase Fresnel lenses (H-MPFLs) were developed on silicon wafer at the selected frequency of 585 GHz. For this reason, the design of a standard MPFL was modified thoroughly in various outer zone areas in order to reduce the complexity and manufacturing time of the diffractive optical elements by employing the direct laser ablation processes. The phase offset was found by precise control over the phase shift of incoming radiation in steps of π/12, revealing its optimal value to be of +π/4 independently on the hybridization order of the lens, the focusing gain of which was found to be up to 10 % higher than that achieved with a standard design MPFL. The numerical modeling data were confirmed by experiments demonstrating the effective THz beam focusing with H-MPFL samples to the diffraction-limited spot size. The proposed development procedure can be further modified by scaling the hybrid lens design to other frequencies with different zone numbers and/or by employing other materials suitable for THz photonics integration on-chip with the semiconductor devices.

Iron-rich intermetallics in Al-Si alloys pose a major challenge in aluminum recycling. Virgin Al-Si alloys typically contain a minimal iron concentration which enhances properties like tensile strength and conductivity. Although aluminum is a recycling friendly metal, Fe impurity increases due to scrap contaminations, coatings and rust, which eventually leads to the evolution and growth of detrimental Fe-rich intermetallics. These Fe-rich particles exhibit platelet or needle-like morphologies, and their aspect ratios grow with higher Si and Fe concentrations. Among the identified βphases, β-Al5FeSi is predominantly known for its fragility and negative impact on the mechanical properties of the alloy. Two potential solutions to this problem are, removing Fe from Al-Si alloys or suppressing the formation of β-Al5FeSi. While the method of alloying additions is much more viable for industry scale. Current study is a critical review of morphological modification of Fe-rich intermetallics through alloying additions to Al-Si alloys. The independent mechanism(s) of suppression of β-Al5FeSi phase by Mn, Mo, V and Cr additions is discussed along with the challenges and future scope of this work are discussed in detail.

Graphical Abstract: Figures 1c and 2a, respectively, represent the SEM–EDS elemental mapping of Al3Nb particles found in the as-cast Al–Si–Fe alloy inoculated with Al–10Nb master alloy, while Figs. 1d and 2b show the SEM–EDS elemental mapping of Al3(FeNb)Si particles found in the as-cast Al–Si–Fe alloy inoculated with elemental Nb powder. Results show that Al3(FeNb)Si particles are absent in the as-cast Al–Si–Fe alloy inoculated with Al–10Nb master alloy.Fig. 1Scanning electron photomicrographs of the Al scrap alloy with the 1wt% addition of Nb in the form of aAl–10Nb master alloy (200×), bNb elemental powder (200×), cAl–10Nb master alloy (2000×), dNb elemental powder (2000×)Fig. 2SEM–EDS elemental mapping of the intermetallic phases shown in aFig. 1c and, bFig. 1d

•Calcium is an essential secondary messenger involved in both abiotic and biotic stresses.•Soybean is an important industrial legume.•Calmodulin (CaM) and CaM-binding proteins are involved in stress-mediated tolerance in soybean.

In this article, author explores ways to be more aware, take care and responsibility for self and others, and build community, along with explores how young people have been revolutionizing the world by educating themselves on issues pertaining to society as a whole.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jbankfin.2009.07.012 Byline: Meghana Ayyagari (a), Craig Doidge (b) Keywords: Cross-listing; Ownership structure Abstract: This paper examines whether controlling shareholders of foreign firms use a US cross-listing to facilitate changes in ownership and control. Prior to listing, about three quarters of the firms in our sample have a controlling shareholder. After listing, about half of the controlling shareholders' voting rights decrease, with an average decrease of 24% points that differs significantly from that of the controlling shareholders of benchmark firms that do not cross-list. Large decreases in voting rights are associated with controlling shareholder characteristics, domestic market constraints, and better stock market performance and liquidity. In addition, there is control change in 22% of the firms. Controlling shareholders are more likely to sell control, and are more likely to do so to a foreign buyer, than controlling shareholders of benchmark firms. The results suggest that controlling shareholders who want to sell shares or their control stake can use a US cross-listing to decrease the cost of transferring ownership. Author Affiliation: (a) Funger Hall 401, George Washington University, 2201 G Street NW, Washington, DC 20052, United States (b) Room #465, 105 St. George Street, Rotman School of Management, University of Toronto, Toronto, Ontario, Canada M5S 3E6 Article History: Received 13 February 2008; Accepted 19 July 2009

Background: To improve the discriminatory power of the Gail model for predicting absolute risk of invasive breast cancer, we previously developed a relative risk model that incorporated mammographic density (DENSITY) from data on white women in the Breast Cancer Detection Demonstration Project (BCDDP). That model also included the variables age at birth of first live child (AGEFLB), number of affected mother or sisters (NUMREL), number of previous benign breast biopsy examinations (NBIOPS), and weight (WEIGHT). In this study, we developed the corresponding model for absolute risk. Methods: We combined the relative risk model with data on the distribution of the variables AGEFLB, NUMREL, NBIOPS, and WEIGHT from the 2000 National Health Interview Survey, with data on the conditional distribution of DENSITY given other risk factors in BCDDP, with breast cancer incidence rates from the Surveillance, Epidemiology, and End Results program of the National Cancer Institute, and with national mortality rates. Confidence intervals (CIs) accounted for variability of estimates of relative risks and of risk factor distributions. We compared the absolute 5-year risk projections from the new model with those from the Gail model on 1744 white women. Results: Attributable risks of breast cancer associated with DENSITY, AGEFLB, NUMREL, NBIOPS, and WEIGHT were 0.779 (95% CI = 0.733 to 0.819) and 0.747 (95% CI = 0.702 to 0.788) for women younger than 50 years and 50 years or older, respectively. The model predicted higher risks than the Gail model for women with a high percentage of dense breast area. However, the average risk projections from the new model in various age groups were similar to those from the Gail model, suggesting that the new model is well calibrated. Conclusions: This new model for absolute invasive breast cancer risk in white women promises modest improvements in discriminatory power compared with the Gail model but needs to be validated with independent data.

Human organoids have the potential to revolutionize in vitro disease modeling by providing multicellular architecture and function that are similar to those in vivo. This innovative and evolving technology, however, still suffers from assay throughput and reproducibility to enable high‐throughput screening (HTS) of compounds due to cumbersome organoid differentiation processes and difficulty in scale‐up and quality control. Using organoids for HTS is further challenged by the lack of easy‐to‐use fluidic systems that are compatible with relatively large organoids. Here, these challenges are overcome by engineering “microarray three‐dimensional (3D) bioprinting” technology and associated pillar and perfusion plates for human organoid culture and analysis. High‐precision, high‐throughput stem cell printing, and encapsulation techniques are demonstrated on a pillar plate, which is coupled with a complementary deep well plate and a perfusion well plate for static and dynamic organoid culture. Bioprinted cells and spheroids in hydrogels are differentiated into liver and intestine organoids for in situ functional assays. The pillar/perfusion plates are compatible with standard 384‐well plates and HTS equipment, and thus may be easily adopted in current drug discovery efforts. A pillar/perfusion plate is developed to generate human organoids robustly by printing progenitor cells in hydrogels on pillars using a 3D bioprinter or transferring single spheroids to pillars via a sandwiching and inverting method. Organoid differentiation is performed in static and dynamic conditions by sandwiching the pillar plate onto a deep well plate or a perfusion well plate.

In this investigation, results of dielectric features of Li2O–Al2O3–SiO2(LAS) glass doped with 3.0 mol% of Cr2O3, MoO3, and WO3are presented. The investigation spans broad regions of frequency (ω) 10−2–106Hz and temperature (T) 20–240 °C. Initial characterization of the samples by means of optical absorption spectra reveals that Cr ions do persist in Cr3+oxidation state, whereas fractions of Mo and W ions do present in Mo5+and W5+states in addition to predominant presence Mo6+and W6 +ions, respectively. Infrared spectra suggest that Mo5+and W5+ions involve in modifying the network of the glass and induced structural disorder. Dielectric parameters and also σacare observed to be the largest for 40Li2O–5Al2O3–52SiO2:3.0 MoO3(LASMo) glass followed by 40Li2O–5Al2O3–52SiO2:3.0 WO3(LASW) and 40Li2O–5Al2O3–52SiO2:3.0 Cr2O3(LASCr) glasses. Analysis of dipolar relaxation phenomena are carried out using Cole–Cole plots. Analysis of the results of σacsuggests that polaronic conduction due to electron transfer between Mo5+↔ Mo6+and W5+↔ W6+is prevailed in case of LASMo and LASW glasses and these glasses are predicted to be useful as cathodes, whereas in LASCr glass, ionic conductivity is dominant and is suitable for electrolytes in ionic batteries. The dielectric properties of Li2O–Al2O3–SiO2glass system containing Cr2O3, MoO3, and WO3are investigated over wide ranges of frequency (10−2–106Hz) and temperature 20–240 °C. Quantitative analysis of these results suggests that MoO3and WO3doped glasses are promising electrode materials, while Cr2O3doped glasses are well suited for use as electrolytes in solid‐state batteries.

AbstractIn the present study, one of the targets present on the envelopes of coronaviruses, membrane glycoprotein (M) was chosen for the design of a multi-epitope vaccine by Immunoinformatics approach. The B-cell and T-cell epitopes used for the construction of vaccine were antigenic, nonallergic and nontoxic. An adjuvant, β-defensin and PADRE sequence were included at the N-terminal end of the vaccine. All the epitopes were joined by linkers for decreasing the junctional immunogenicity. Various physicochemical parameters of the vaccine were evaluated. Secondary and tertiary structures were predicted for the vaccine construct. The tertiary structure was further refined, and various parameters related to the refinement of the protein structure were validated by using different tools. Humoral immunity induced by B-cells relies upon the identification of antigenic determinants on the surface of the vaccine construct. In this regard, the vaccine construct was found to consist of several B-cell epitopes in its three-dimensional conformation. Molecular docking of the vaccine was carried out with TLR-3 receptor to study their binding and its strength. Further, protein–protein interactions in the docked complex were visualized using LigPlot+. Population coverage analysis had shown that the multi-epitope vaccine covers 94.06% of the global population. The vaccine construct was successfully cloned in silicointo pET-28a (+). Immune simulation studies showed the induction of primary, secondary and tertiary immune responses marked by the increased levels of antibodies, INF-γ, IL-2, TGF-β, B- cells, CD4+ and CD8+ cells. Finally, the vaccine construct was able to elicit immune response as desired.Communicated by Ramaswamy H. Sarma

Formation of graded biomaterials to render shape-morphing scaffolds for 4D biofabrication holds great promise in fabrication of complex structures and the recapitulation of critical dynamics for tissue/organ regeneration. Here we describe a facile generation of an adjustable and robust gradient using a single- or multi-material one-step fabrication strategy for 4D biofabrication. By simply photocrosslinking a mixed solution of a photocrosslinkable polymer macromer, photoinitiator (PI), UV absorber and live cells, a cell-laden gradient hydrogel with pre-programmable deformation can be generated. Gradient formation was demonstrated in various polymers including poly(ethylene glycol) (PEG), alginate, and gelatin derivatives using various UV absorbers that present overlap in UV spectrum with that of the PI UV absorbance spectrum. Moreover, this simple and effective method was used as a universal platform to integrate with other hydrogel-engineering techniques such as photomask-aided microfabrication, photo-patterning, ion-transfer printing, and 3D bioprinting to fabricate more advanced cell-laden scaffold structures. Lastly, proof-of-concept 4D tissue engineering was demonstrated in a study of 4D bone-like tissue formation. The strategy's simplicity along with its versatility paves a new way in solving the hurdle of achieving temporal shape changes in cell-laden single-component hydrogel scaffolds and may expedite the development of 4D biofabricated constructs for biological applications.

Introduction: Fervourous investigation and dialogue surrounding the true number of SARS-CoV-2-related deaths and implied infection fatality rates in India have been ongoing throughout the pandemic, and especially pronounced during the nation’s devastating second wave. We aim to synthesize the existing literature on the true SARS-CoV-2 excess deaths and infection fatality rates (IFR) in India through a systematic search followed by viable meta-analysis. We then provide updated epidemiological model-based estimates of the wave 1, wave 2 and combined IFRs using an extension of the Susceptible-Exposed-Infected-Removed (SEIR) model, using data from 1 April 2020 to 30 June 2021.Methods: Following PRISMA guidelines, the databases PubMed, Embase, Global Index Medicus, as well as BioRxiv, MedRxiv and SSRN for preprints (accessed through iSearch), were searched on 3 July 2021 (with results verified through 15 August 2021). Altogether, using a two-step approach, 4,765 initial citations were screened, resulting in 37 citations included in the narrative review and 19 studies with 41datapoints included in the quantitative synthesis. Using a random effects model with DerSimonian-Laird estimation, we meta-analysed IFR1, which is defined as the ratio of the total number of observed reported deaths divided by the total number of estimated infections, and IFR2(which accounts for death underreporting in the numerator of IFR1). For the latter, we provided lower and upper bounds based on the available range of estimates of death undercounting, often arising from an excess death calculation. The primary focus is to estimate pooled nationwide estimates of IFRs with the secondary goal of estimating pooled regional and state-specific estimates for SARS-CoV-2-related IFRs in India. We also tried to stratify our empirical results across the first and second waves. In tandem, we presented updated SEIR model estimates of IFRs for waves 1, 2, and combined across the waves with observed case and death count data from 1 April 2020 to 30 June 2021.Results: For India, countrywide, the underreporting factors (URF) for cases (sourced from serosurveys) range from 14.3 to 29.1 in the four nationwide serosurveys; URFs for deaths (sourced from excess deaths reports) range from 4.4 to 11.9 with cumulative excess deaths ranging from 1.79 to 4.9 million (as of June 2021). Nationwide pooled IFR1and IFR2estimates for India are 0.097% (95% confidence interval [CI]: 0.067–0.140) and 0.365% (95% CI: 0.264–0.504) to 0.485% (95% CI: 0.344–0.685), respectively, again noting that IFR2changes as excess deaths estimates vary. Among the included studies in this meta-analysis, IFR1generally appears to decrease over time from the earliest study end date to the latest study end date (from 4 June 2020 to 6 July 2021, IFR1changed from 0.199 to 0.055%), whereas a similar trend is not as readily evident for IFR2due to the wide variation in excess death estimates (from 4 June 2020 to 6 July 2021, IFR2ranged from (0.290–1.316) to (0.241–0.651)%). Nationwide SEIR model-based combined estimates for IFR1and IFR2are 0.101% (95% CI: 0.097–0.116) and 0.367% (95% CI: 0.358–0.383), respectively, which largely reconcile with the empirical findings and concur with the lower end of the excess death estimates. An advantage of such epidemiological models is the ability to produce daily estimates with updated data, with the disadvantage being that these estimates are subject to numerous assumptions, arduousness of validation and not directly using the available excess death data. Whether one uses empirical data or model-based estimation, it is evident that IFR2is at least 3.6 times more than IFR1.Conclusion: When incorporating case and death underreporting, the meta-analysed cumulative infection fatality rate in India varied from 0.36 to 0.48%, with a case underreporting factor ranging from 25 to 30 and a death underreporting factor ranging from 4 to 12. This implies, by 30 June 2021, India may have seen nearly 900 million infections and 1.7–4.9 million deaths when the reported numbers stood at 30.4 million cases and 412 thousand deaths (Coronavirus in India) with an observed case fatality rate (CFR) of 1.35%. We reiterate the need for timely and disaggregated infection and fatality data to examine the burden of the virus by age and other demographics. Large degrees of nationwide and state-specific death undercounting reinforce the call to improve death reporting within India. JEL Classifications:I15, I18

The COVID-19 pandemic has caused income loss for many households, disrupting food consumption patterns and contributing to weight loss for some, and weight gain for others. In this article, I build a dynamic theoretical model that explains those empirical facts. The novelty of this paper is to incorporate stress caused by a lower than ideal income (economic stress) in a model of optimal intertemporal food consumption decisions made by a rational eater. In this framework, economic stress causes disutility and individuals can cope by increasing high-calorie food consumption (stress eating). The limitation to this coping mechanism is that being overweight from excessive calorie intake also decreases utility. Thus, a decrease in income causes updates of the constraints faced by rational consumers of food, which are a budget constraint, a stress constraint and a weight gain constraint. As a consequence, the effect of a decrease in income on body weight reflects a competing income effect as well as two effects specific to economic stress, which are an intertemporal substitution effect and a stress eating effect. Those effects explain opposite weight patterns observed during the pandemic.JEL Classification:D11, D91, I12, I14

In the first month of the UK first lockdown, we studied the demand and willingness to pay (WTP) for hand sanitizer gel, disposable face masks and disposable gloves, and how information on tested people and coronavirus deaths explains the demand and WTP for these products. The specific hypotheses to test and concrete questions to study were pre-registered in AsPredicted (#38962) on 10 April 2020, and an online survey was launched in Prolific on a sample of the UK general population representative by age, sex and ethnicity on 11 April 2020. We find that there is a demand for these products, estimate the average WTP for them, and show that the provision of information affected the demand (and WTP) for disposable face masks. Providing information on the numbers of coronavirus cumulative tested people and coronavirus cumulative deaths increases the stated demand for disposable face masks by about 8 percentage points [95% CI: 0.8, 15.1] and 11 percentage points [95% CI: 3.7, 18.2], respectively.JEL Classifications:C99, D12, I12, I18

With more than 29 million confirmed cases of COVID-19 in the USA and 119 million cases worldwide, the pandemic has affected companies, households and the global economy. We explore the effect of the economic shock which resulted from this specific health event on labour market outcomes, and the changes in labour market disparities between ethnic groups and genders. The results provide evidence of an adverse effect of COVID-19 on labour market outcomes of all demographic groups, a widening gap between the employment prospects of minorities and whites, but no change in the earnings gaps between ethnic groups. We also do not find a deterioration of the differentials between genders, except the increase in the difference in the duration of unemployment between women and men with children. The findings have implications related to the priorities of policy decision-makers when implementing policies to combat ethnic and gender gaps in the labour market.JEL Classification:J70, J71, J01, J15, J23

Background. Genetically engineered tumor vaccines are feasible for clinical trials in human prostate cancer, and Phase I testing has been approved. The Dunning rat prostate cancer model provides an opportunity for translational research to rationally design Phase II clinical studies testing efficacy. Methods. The Dunning R3327 MAT-LyLu subline was transduced with the retroviral vector MFG carrying the cytokine gene for human granulocyte-macrophage colony-stimulating factor (GM-CSF). Varying secretion rates of human GM-CSF were generated and tumor cell vaccines were formulated, consisting of 5 X [10.sup.6] lethally irradiated transduced cells. The vaccines were placed at a subcutaneous site opposite preestablished tumor of 1 x [10.sup.4] cells implanted 3 days earlier in Copenhagen rats. Trials were masked, randomized, and conducted over 6-week intervals using different treatment schedules, vaccine number, and varying doses of human GM-CSF secretion as well as appropriate controls. Results. Thirty percent of rats with long term follow-up can be cured of preestablished tumor burdens with human GM-CSF transduced tumor vaccines secreting greater than 140 ng/[10.sup.6] cells/24 hours of human GM-CSF. All studies evaluating more than one vaccine over a wide range of human GM-CSF secretion rates show significant delays in tumor appearance and progression. One vaccination is not curative. Vaccination with GM-CSF transduced tumor vaccines increased disease free survival and slowed tumor progression over animals vaccinated with irradiated tumor cells admixed with either soluble GM-CSF or with a nonspecific immune adjuvant (Corynebacterium parvum). The ability to cure animals and delay progression appears related to total duration of human GM-CSF secretion at the subcutaneous site. Systemic human GM-CSF could be detected in the serum of rats for at least 6 days after vaccination. Conclusions. These data have implications for the design of gene therapy trials in prostate cancer. Small androgen independent tumor burdens such as volumes seen in the adjuvant setting can be cured. Multiple vaccinations with adequate human GM-CSF secretion are required. At higher human GM-CSF secretion rates, systemic levels may be achievable, and patients should be evaluated closely for toxicity to and the pharmacokinetics of GM-CSF. Cancer 1995;75:2013-20.

AbstractIn the present study, we explored phytochemical constituents of Tinospora cordifoliain terms of its binding affinity targeting the active site pocket of the main protease (3CL pro) of SARS-CoV-2 using molecular docking study and assessed the stability of top docking complex of tinosponone and 3CL pro using molecular dynamics simulations with GROMACS 2020.2 version. Out of 11 curated screened compounds, we found the significant docking score for tinosponone, xanosporic acid, cardiofolioside B, tembetarine and berberine in Tinospora cordifolia. Based on the findings of the docking study, it was confirmed that tinosponone is the potent inhibitor of main protease of SARS-CoV-2 with the best binding affinity of −7.7 kcal/mol. Further, ADME along with toxicity analysis was studied to predict the pharmacokinetics and drug-likeness properties of five top hits compounds. The molecular dynamics simulation analysis confirmed the stability of tinosponone and 3CL pro complex with a random mean square deviation (RMSD) value of 0.1 nm. The computer-aided drug design approach proved that the compound tinosponone from T. cordifoliais a potent inhibitor of 3CL main protease of SARS-CoV-2. Further, the in vitroand in vivo-based testing will be required to confirm its inhibitory effect on SARS-CoV-2.Communicated by Ramaswamy H. Sarma

AbstractThe best therapeutic strategy to find an effective vaccine against SARS-CoV-2 is to explore the target structural protein. In the present study, a novel multi-epitope vaccine is designed using in silicotools that potentially trigger both CD4 and CD8 T-cell immune responses against the novel Coronavirus. The vaccine candidate was designed using B and T-cell epitopes that can act as an immunogen and elicits immune response in the host system. NCBI was used for the retrieval of surface spike glycoprotein, of novel corona virus (SARS-CoV-2) strains. VaxiJen server screens the most important immunogen of all the proteins and IEDB server gives the prediction and analysis of B and T cell epitopes. Final vaccine construct was designed in silicocomposed of 425 amino acids including the 50S ribosomal protein adjuvant and the construct was computationally validated in terms of antigenicity, allergenicity and stability on considering all critical parameters into consideration. The results subjected to the modeling and docking studies of vaccine were validated. Molecular docking study revealed the protein-protein binding interactions between the vaccine construct and TLR-3 immune receptor. The MD simulations confirmed stability of the binding pose. The immune simulation results showed significant response for immune cells. The findings of the study confirmed that the final vaccine construct of chimeric peptide could able to enhance the immune response against nCoV-19.

The 2003 Medicare Modernization Act introduced income-related premiums on Medicare coverage for professional services (Part B) for the first time. Beginning in 2007, higher-income households were required to pay higher premiums for Part B coverage, which raises the price of Medicare relative to employer-sponsored health insurance for these households. The authors exploit this exogenous change in Medicare policy to examine the impact of Part B premiums on the labor supply decisions of older adults. They find that higher Medicare premiums delay retirement. Findings have important implications for Medicare policy and labor markets.

The study developed a conceptual model of service innovation viewed through a service ecosystem lens, and empirically validated the model using data gathered from 334 managers in the tourism industry of the United Arab Emirates. A mixed methods approach was used. Three significant factors emerged as direct antecedents of innovation, namely dyadic interactions between: customers and employees, the firm and its partners, and the firm and its competitors. Further, two 'enablers', technological and organisational support, reinforced these interactions. This study contributes to the emerging literature in two ways - operationalising the service ecosystem construct and examining the impact of dyadic interactions between actors within the ecosystem on service innovation. The findings and discussions provide managers in the UAE tourism industry with a holistic view of the innovation trajectory, helping them to identify critical enablers and manage key actor interactions in the ecosystem.

Aim:To illustrate that bias associated with indirect treatment comparison and network meta-analyses can be reduced by adjusting for outcomes on common reference arms. Materials & methods:Approaches to adjusting for reference-arm effects are presented within a causal inference framework. Bayesian and Frequentist approaches are applied to three real data examples. Results:Reference-arm adjustment can significantly impact estimated treatment differences, improve model fit and align indirectly estimated treatment effects with those observed in randomized trials. Reference-arm adjustment can possibly reverse the direction of estimated treatment effects. Conclusion:Accumulating theoretical and empirical evidence underscores the importance of adjusting for reference-arm outcomes in indirect treatment comparison and network meta-analyses to make full use of data and reduce the risk of bias in estimated treatments effects.

Purpose: Consumers often encounter issues of perceived ambiguity and performance risk when attempting to evaluate experience goods being offered online. Sellers try to alleviate this knowledge gap often seen in a medium of low naturalness by engaging in effective compensatory adaptation. This research theoretically looks into three primary aspects of compensatory adaption and their potential in securing communication of high-quality information between the online seller and consumer. Design/methodology/approach: Utilizing survey data and structural equation modeling, this study tests the effectiveness of different aspects of compensatory adaption to alleviate the knowledge gap in a medium of low naturalness. Findings: Drawing on media naturalness theory and the tripartite model of attitude, this paper identifies three theoretical components that significantly affect the effectiveness of compensatory adaption. They are information retrieval capability from the cognitive/logical aspect, information richness from the affective/audiovisual aspect and interactivity from the behavioral aspect. The effectiveness of compensatory adaptation proves to have a positive impact on perceived information quality. Originality/value: To the best of our knowledge, this is the first paper in the information systems literature to examine the compensatory adaptation tools for effective transfer of information. This study contributes to the academics by providing three handles to improve effectiveness of compensatory adaptation toward information quality. We focus on three compensatory adaptation tools in cognitive/logical, affective/audiovisual and behavioral aspects, and this compensation perspective leads to three practical factors that affect effective transfer of information between online sellers and consumers. The result of this study complements the nomological network of the enablers and impediments of e-commerce.

AbstractAims:To evaluate the association of relapse and healthcare resource utilization in patients with schizophrenia (SZ), bipolar disorder (BD), or major depressive disorder (MDD) who switched antipsychotic medication versus those who did not.Materials and methods:Medicaid claims from six US states spanning six years were retrospectively analyzed for antipsychotic switching versus non-switching. For all patients with SZ, BD, or MDD, and for the subset of patients who also had ≥1 extrapyramidal symptoms (EPS) diagnosis at baseline, times to the following outcomes were analyzed: underlying disease relapse, other psychiatric relapse, all-cause emergency room (ER) visit, all-cause inpatient (IP) admission, and EPS diagnosis.Results:Switchers (N = 10,548) had a shorter time to disease relapse, other psychiatric relapse, IP admissions, ER visits, and EPS diagnosis (all, log-rank p < .001) than non-switchers (N = 31,644). Switchers reached the median for IP admission (21.50 months) vs non-switchers (not reached) and for ER visits (switchers, 9.07 months; non-switchers, 13.35 months). For disease relapse, other psychiatric relapse, and EPS diagnosis, <50% of patients had an event during the two-year study period. Subgroup analysis of those with ≥1 EPS diagnosis revealed similar associations.Limitations:Only association, not causation, may be inferred, and there may be differences between the patient groups in parameters not evaluated.Conclusions:These results show that disease and other psychiatric relapse, all-cause ER visits, IP admissions, and EPS diagnosis occurred earlier for patients who switched antipsychotics than for those who did not, suggesting that switching is associated with an increased risk of relapse in patients with SZ, BD, and MDD. This may be attributed to more-severely ill patients being less responsive than those with less-severe illness, which, in turn, may require more episodes of switching.

The study adopted a case methodology and used the service ecosystem lens to investigate how a public institution successfully supported interactions with its customers and partners to enable innovation and value co-creation. Data from secondary sources and two independent audit survey reports were examined. This analysis was complemented with in-depth interviews of employees at Dubai Corporation for Ambulance Services (DCAS), external experts and stakeholders. The findings demonstrated how DCAS created a conducive innovation ecosystem, supported by technology and organisational factors, and worked collaboratively and synergistically with a wide array of actors to successfully co-create value for patients. The case study provides useful insights into an innovation ecosystem fostered by public sector managers to help citizens and patients benefit from service excellence.

Patients who underwent prostate artery embolization were administered a median effective patient radiation dose of 17.8 mSv and reported no radiation-related adverse events at 90 days.