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ABSTRACTAdvertising budgets and related expenditures have been increasing every year. Companies, in the past, have used different tools to grab their customers’ attention and encourage them to buy their products. The purpose of this research is to introduce strategic self-anticonformity (SSA) as an effective tool in the advertising industry. This study demonstrates that SSA relates positively to attention, and ultimately to purchase intention. An experiment was conducted to manipulate the SSA condition. The study also shows that product involvement moderates the relationship between SSA and attention. In addition, attitude toward ad mediates the relationship between attention and purchase intention.

Power system operators require advanced applications in the control centers to tackle increasingly variable power transfers effectively. One urgently needed application concerns estimating the feasible available aggregated flexibility from a power system network, which can be effectively deployed to mitigate issues in interconnected networks. This paper proposes the TensorConvolution+ algorithm to address the above application. Unlike related literature approaches, TensorConvolution+ estimates the density of feasible flexibility combinations to reach a new operating point within the p-q flexibility area. This density can improve the decision-making of system operators for efficient and safe flexibility deployment. The proposed algorithm applies to radial and meshed networks, is adaptable to new operational conditions, and can consider scenarios with disconnected flexibility areas. Using convolutions and tensors, the algorithm efficiently aggregates the combinations of flexibility providers’ adjustable power output that can occur for each flexibility area set point. Simulations on the meshed Oberrhein and radial CIGRE test networks illustrate the effectiveness of TensorConvolution+ for flexibility estimation with high numerical confidence and a minor computing effort. Additional simulations highlight how system operators can interpret the estimated density of feasible flexibility combinations for decision-making purposes, the algorithm’s capability to estimate disconnected flexibility areas, and adapt to new operating conditions.

Cascading failures in power systems are extremely rare occurrences caused by a combination of multiple, low probability events. The looming threat of cyberattacks on power grids, however, may result in unprecedented large-scale cascading failures, leading to a blackout. Therefore, new analysis methods are needed to study such cyber induced phenomena. In this article, we propose a data-driven method for dynamical analysis of power system cascading failures caused by cyberattacks. We provide experimental proof on how attacks may accelerate the cascading failure mechanism, in comparison to historically observed blackouts. Using a dynamic power grid model, consisting of multiple, coordinated protection schemes, we define and analyze the point of no return in a cascading failure sequence by applying the Hilbert–Huang transform for time-frequency analysis. Numerical results indicate, cyberattacks may accelerate cascading failures at least by a factor of 3x. This is due to the excitation and non-damping of multiple frequency modes greater than 1 Hz in a short time span. The proposed method is tested using time domain simulations conducted through a modified IEEE 39-bus test system, which can simulate cascading outages using coordinated protection schemes.

Several statistical methods have been developed to decompose the phenotypic response based mainly on the general means, the effect of the genotype, and its interaction with the environment, treating the environmental variance as a confounding factor. However, the estimation of the environmental effect from the traits evaluated would establish a dependency on the genotype, resulting in a lower fit and predictive potential of the model. The integration of environmental covariates into the models that associate edaphoclimatic characteristics with the traits of interest has been proposed, with the purpose of increasing the predictive potential and the variance contained by the models. The aim of this study was to evaluate the sensitivity of the traits of interest in yellow diploid potato (Solanum tuberosumL. Group: Phureja) crops to environmental covariates, selecting the most relevant covariates as parameters in empirical multiple regression models based on environmental variance. The results showed high yield variability due to covariates of the water component, while the quality traits were mainly affected by traits of the energetic and physicochemical components of the soil. The adjusted models explained the variance intrinsically due to the environment, reaching adjustments greater than 20%. Therefore, it is concluded that the traits have a high phenotypic sensitivity, and the incorporation of environmental covariates into the genotype‐by‐environment interaction analysis models could improve the understanding of the stability and adaptability of cultivars from the data obtained in multi‐environment trials. Breeding programs treat the environment as a confounding factor that limits the predictive potential of the models.Integration of environmental covariates into regression models could increase accuracy in selecting superior genotypes.Markov chain Monte Carlo is an efficient tool for multi‐environment trials database processing and estimation of stability and adaptability parameters.Performance of genotypes could be observed as a linear function of environmental covariates.

ABSTRACTThis research paper investigates the impact of surge pricing, a dynamic pricing strategy that adjusts prices based on real-time demand and supply, on customers’ perception of price fairness. We aim to provide insights for both academic and managerial audiences. Our study focuses on how businesses using surge pricing can minimize negative effects on customer behavior by properly communicating price changes. We conducted two experiments to examine customers’ fairness perception of surge pricing policies. Our findings revealed that customers generally perceive surge pricing as less fair. However, we also discovered that aligning the amount of information shared with the price increase can effectively improve these fairness perceptions. Our research contributes to the literature on price communication by exploring factors that influence consumers’ understanding and acceptance of price changes. Additionally, our findings offer practical guidance for businesses on how to communicate pricing information in a way that customers perceive as fair, ultimately benefiting both companies and their customers.

Context: African Americans (AA) may carry high risk Apolipoprotein L1 (APOL1) genetic variants that predispose them to significantly higher incidence of chronic kidney disease (CKD) and renal cell carcinoma (RCC).Objective: To study the role of APOL1risk alleles in patients of African descent with kidney neoplasms.Design: AA patients with nephrectomy procedure for kidney neoplasms were retrospectively studied for APOL1genotype. Non-AA patients with kidney neoplasm served as control group.Results: Thirty-six AA patients with kidney neoplasms were included. Sixteen (44%) patients carried no APOL1risk alleles; 13 (36%) patients carried one APOL1risk allele and 7 (19%) patients carried two APOL1risk alleles. Increased risk of end stage kidney disease (ESKD) was observed in patients with two APOL1risk alleles (OR = 3.45). We also observed a higher papillary carcinoma (pRCC) percentage in patients with two risk alleles. Five (71.4%) of the seven patients with two risk-alleles had pRCC. In patients with zero or one APOL1risk allele (n= 29), 8 (28%) had pRCC. However, in AA patients with ESKD (n= 6), only 2 (33%) had PRCC. Among the non-AA patients (n= 319), 7 (2.2%) patients presented with ESKD, of which 2 (33%) had pRCC.Conclusions: We observed a cluster phenomenon in APOL1 high-risk genotype, ESKD, and kidney neoplasm. We observed significantly more frequent papillary RCC prevalence in AA patients with high-risk APOL1genotype.

We report a simple approach to fabricate free-standing perforated 2D nanomembranes hosting well-ordered 1D metallic nanostructures to obtain hybrid materials with nanostructured surfaces for flexible electronics. Nanomembranes are formed by alternatively depositing perforated poly(lactic acid) (PLA) and poly(3,4-ethylenedioxythiophene) layers. Copper metallic nanowires (NWs) were incorporated into the nanoperforations of the top PLA layer by electrodeposition and further coated with silver via a transmetallation reaction. The combination of 2D polymeric nanomembranes and aligned 1D metallic NWs allows merging the flexibility and conformability of the ultrathin soft polymeric nanomembranes with the good electrical properties of metals for biointegrated electronic devices. Thus, we were able to tailor the nanomembrane surface chemistry as it was corroborated by SEM, EDX, XPS, CV, EIS and contact angle. The obtained hybrid nanomembranes were flexible and conformable showing sensing capacity towards H2O2with good linear concentration range (0.35–10 mM), sensitivity (120 µA cm−2mM−1) and limit of detection (7 μm). Moreover, the membranes showed good stability, reproducibility and selectivity towards H2O2.

Purpose: This study examines the use of dark humor in brand-to-brand communications on social media and its impact on consumers' brand perceptions. In particular, this study looks at roasting messages in which a brand humorously insults its peers. Design/methodology/approach: The authors used a sampling method to recruit 286 participants from the United States. They employed an ANOVA and Tukey's post hoc analysis to test the hypotheses, as well as Hayes' PROCESS to test the mediation and moderation effects, including Johnson–Neyman procedure. Findings: The authors found that not all customers find roasting messages funny. Rather, consumers' personality and age will influence their perceived humor of the messages and their brand evaluations. Customers who are young and extroverted are likely to believe roasting messages to be funny. They thus perceive the brand to be cooler and more sincere when using such a communication approach, compared to when the brand neutrally interacts with others. Meanwhile, brands may find less success with old and introverted customers. Originality/value: This research sheds light on how the consumers' perception of humor in a roasting type of brand-to-brand communication has an impact on consumers' psychological perceptions of brand coolness and brand sincerity. To guide practitioners, it explored how the interaction between a consumer's personality and age moderates the aforementioned relationship.

As the demand for wearable consumer and medical devices continues to grow, there is a pressing need for flexible and wearable means of storing electrical energy. This laboratory exercise provides an educational framework for teaching fundamental concepts in materials chemistry and electrochemistry through a practical, hands-on approach, focusing on the development of flexible energy storage devices. Fiber-based supercapacitors offer a promising solution due to their inherent flexibility compared to bulk materials, making them ideal candidates for the electrodes of flexible supercapacitors. In this module, students synthesize flexible fibers composed of carbon nanomaterials and chitosan using wet spinning and subsequently characterize these fibers using electrochemical techniques such as cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD). The final stage involves the fabrication of a solid-state supercapacitor, providing a realistic application of the concepts learned. This educational module bridges the gap between classroom learning and real-world applications, fostering a deeper understanding of advanced materials, electrochemistry, and energy storage technologies.

It is crucial to extend the electromagnetic compatibility (EMC) studies to the new frequency regions where modern telecommunication systems operate, specifically those related to the fifth-generation (5G) technology standard for broadband cellular networks. Electric autonomous vehicles (EAVs) are systems that feature 5G technology on board and for which it is essential to ensure the proper management of EMC to prevent malfunctions. Given the considerable development of the EAV-related sector, new materials and solutions for EMI shielding with properties that reduce interference in the frequency regions of 5G technology are being investigated. Today, meatal-based solutions are the most common EMI shielding materials used to mitigate EMC problems. Nevertheless, with the appearance of EAVs, it is needed the design of novel materials that provide a significant balance in terms of shielding effectiveness (SE) and mechanical properties. Thereby, carbon nanotubes (CNTs) are an attractive alternative to conventional EMI shielding materials due to their characteristics. The lightweight condition, flexibility, cost-effectiveness, easy processing, and resistance to corrosion made this new type of material perfect to be used in the field of EAVs. This contribution focuses on describing and characterizing three nanocomposite materials manufactured by loading a polymer matrix with 5%, 7%, and 10% CNT concentrations, respectively. The SE measurement is carried out with a coaxial sample holder based on the standard ASTM D4935-18. This measurement setup makes it possible to determine the performance of the three materials under test up to 18 GHz, covering part of the operation frequencies of 5G systems.

ABSTRACTThe job market puts pressure on marketing educators to adapt the content of their courses to current business events impacted by race, diversity, and gender issues. However, students may experience discomfort when learning about and discussing controversial topics that are not normally discussed in class. To provide tools for educators to tackle this problem, we conducted an experiment using online discussion boards, manipulating the sequence order of the questions asked to the students. A sentiment analysis offered evidence that a specific set of questions can trigger students’ personal relevance, reducing their racial priming. This will increase the students’ willingness to participate in an open discussion about race, diversity, and gender issues with their peers. The main contribution is a specific educational design that allows instructors to incorporate sensitive topics into their marketing courses without jeopardizing the classroom dynamic.

Benefits of hamstring lengthening surgery on the sagittal plane in children with cerebral palsy have been previously demonstrated, but there is limited information on its effects on the transverse plane. This study compared the effects of medial hamstring lengthening (MHL) with those of medial and lateral hamstring lengthening (MLHL) procedures in the transverse plane. Children with gross motor function classification system (GMFCS) levels I–III who had MHL or MLHL were included. Baseline, short- (1–2 years), and long-term (3+ years) postoperative three-dimensional gait analysis outcomes were compared using analysis of variance. Children were excluded if they had concurrent osteotomies or tendon transfers. One hundred fifty children (235 limbs) were included, with 110 limbs in the MHL group (age 8.5 ± 4.1 years, GMFCS I-27%, II-52%, and III-21%) and 125 limbs in the MLHL group (age 10.0 ± 4.0 years, GMFCS I-23%, II-41%, and III-37%). Time between surgery and short- and long-term follow-up gait analysis was 1.5 ± 0.6 years and 6.6 ± 2.9 years, respectively. Transmalleolar axis became more external after MHL at both short and long terms (P< 0.05), whereas there were only significant differences at long term in MLHL (P< 0.05). Although hamstring lengthening has a positive impact on stance phase knee extension in children with cerebral palsy, intact lateral hamstrings after MHL likely contribute to increased tibial external rotation after surgery. Significant increases in external rotation at the knee in the long term are likely related to a trend present with growth in children with cerebral palsy rather than a direct result of surgical intervention.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.infoecopol.2009.07.001 Byline: Diego Martinez (a), Jesus Rodriguez (a), Jose L. Torres (b) Keywords: New economy; Information and communication technologies; Specific technological change; Neutral technological change Abstract: This paper studies the impact of information and communication technologies (ICT) on US economic growth using a dynamic general equilibrium approach. A production function with six different capital inputs is used, three of them corresponding to ICT assets and the other three to non-ICT assets. The technological change embedded in hardware equipment is found to be the main leading non-neutral force in US productivity growth, accounting for about one quarter of total growth during the period 1980-2004. As a whole, ICT-specific technological change accounts for about 35% of total growth in labor productivity. Author Affiliation: (a) Universidad Pablo Olavide, Department of Economics, Ctra Utrera, 1, 41013 Seville, Spain (b) Universidad de Malaga, Department of Economics, Campus El Ejido, 29013 Malaga, Spain Article History: Received 12 March 2008; Revised 29 June 2009; Accepted 7 July 2009

The prediction of structural performance plays a significant role in damage assessment of glass fiber reinforcement polymer (GFRP) elastic gridshell structures. Machine learning (ML) approaches are implemented in this study, to predict maximum stress and displacement of GFRP elastic gridshell structures. Several ML algorithms, including linear regression (LR), ridge regression (RR), support vector regression (SVR), K-nearest neighbors (KNN), decision tree (DT), random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), category boosting (CatBoost), and light gradient boosting machine (LightGBM), are implemented in this study. Output features of structural performance considered in this study are the maximum stress as f1(x) and the maximum displacement to self-weight ratio as f2(x). A comparative study is conducted and the Catboost model presents the highest prediction accuracy. Finally, interpretable ML approaches, including shapely additive explanations (SHAP), partial dependence plot (PDP), and accumulated local effects (ALE), are applied to explain the predictions. SHAP is employed to describe the importance of each variable to structural performance both locally and globally. The results of sensitivity analysis (SA), feature importance of the CatBoost model and SHAP approach indicate the same parameters as the most significant variables for f1(x) and f2(x).

We report the development of an open-source experimental design via Bayesian optimization platform for multi-objective reaction optimization. Using high-throughput experimentation (HTE) and virtual screening data sets containing high-dimensional continuous and discrete variables, we optimized the performance of the platform by fine-tuning the algorithm components such as reaction encodings, surrogate model parameters, and initialization techniques. Having established the framework, we applied the optimizer to real-world test scenarios for the simultaneous optimization of the reaction yield and enantioselectivity in a Ni/photoredox-catalyzed enantioselective cross-electrophile coupling of styrene oxide with two different aryl iodide substrates. Starting with no previous experimental data, the Bayesian optimizer identified reaction conditions that surpassed the previously human-driven optimization campaigns within 15 and 24 experiments, for each substrate, among 1728 possible configurations available in each optimization. To make the platform more accessible to nonexperts, we developed a graphical user interface (GUI) that can be accessed online through a web-based application and incorporated features such as condition modification on the fly and data visualization. This web application does not require software installation, removing any programming barrier to use the platform, which enables chemists to integrate Bayesian optimization routines into their everyday laboratory practices.

Over the coming years, the next generation of bright young minds will have to confront climate change, humanitarian crises, income inequality, and the other great challenges of our age. But [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.compind.2006.09.001 Byline: Luis Iribarne (a), Jose Antonio Torres (b), Araceli PeA[+ or -]a (c) Keywords: Object-oriented techniques; Systems modeling; Simulation modeling; Greenhouse modeling; Multitunnel greenhouses Abstract: The importance of greenhouse construction in some parts of the south-east of Spain has led to the creation of a European Standard for the design and construction of greenhouses for commercial production (UNE-EN 13031-1). The design process of a tunnel greenhouse can be viewed as the construction of object-oriented programs. The idea behind this approach is to incorporate the characteristic of reusability into the greenhouse design process: this characteristic naturally reduces the cost of design of new programs, since the design costs are measured in time and the number of errors made and rectified. In this paper, we demonstrate modeling using object-oriented techniques (OOT) based upon standard UML and XML notations for simulating multitunnel greenhouses. These techniques facilitate identification of the actors involved, their roles, functions, interaction protocols and behavior. Some examples include the processes of greenhouse marketing, calculation of interdependencies and decomposition between the greenhouse structures. Author Affiliation: (a) Information Systems Group, University of Almeria, 04120 Almeria, Spain (b) Computers and Environmental Group, University of Almeria, 04120 Almeria, Spain (c) Rural Engineering Group, University of Almeria, 04120 Almeria, Spain Article History: Received 5 December 2005; Revised 20 July 2006; Accepted 1 September 2006

What do we know about drug use among inner-city gangs? Unfortunately, not too much. In an era when a 'war on drugs' drives public policy, social scientists ought to be [...], This study describes the patterns of substance use by male and female gang members in Milwaukee. Wisconsin, from their teenage years in the 1980s into adulthood. Milwaukee gangs started out as one form of neighborhood-based drug-using peer group. There was much variation in drug use, and family variables explained little of the variation. Male gang members raised in families with a history of gang involvement and drug use were more likely than other gang members to use cocaine and to use it seriously. On the other hand, severe family distress was not related to onset, duration, or seriousness of cocaine use in either males or females. Cocaine use for both males and females increased in adulthood. It appears that the etiology of adult and adolescent drug use may differ. Neither social control theory nor differential association theory is well suited to explain the variations in gang drug use by age or gender.

ABSTRACTThis paper studies the impact of the adoption of different management control practices (MCP) on the firms’ financial performance in Latin America. We use the perspective of the attention-based view theory to argue that firms adopting MCP that cover different areas are more likely to attain higher financial performance, as adopting a diverse set of control practices contributes to distributing managerial attention. Thus, relevant business areas are monitored more comprehensively. We compare the performance effect of seven MCP in three areas (monitoring, operations, and targets) alone and combined using a panel dataset on 57 Latin American firms from 1995 to 2016, finding support for our arguments. Moreover, we find that the firms’ strategy moderates the financial performance effect of the adoption of MCP.

Everybody seems to be talking about moving to Windows these days. Before you decide to port DOS applications to Windows, you should first consider the reasons why you want to […]

Validar ecuaciones de regresión que predicen el estado de madurez (EM) para evaluar el crecimiento físico y adiposidad corporal de niños y adolescentes chilenos.

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Multifunctional hydrogels are a class of materials offering new opportunities for interfacing living organisms with machines due to their mechanical compliance, biocompatibility, and capacity to be triggered by external stimuli. Here, we report a dual magnetic- and electric-stimuli-responsive hydrogel with the capacity to be disassembled and reassembled up to three times through reversible cross-links. This allows its use as an electronic device (e.g., temperature sensor) in the cross-linked state and spatiotemporal control through narrow channels in the disassembled state via the application of magnetic fields, followed by reassembly. The hydrogel consists of an interpenetrated polymer network of alginate (Alg) and poly(3,4-ethylenedioxythiophene) (PEDOT), which imparts mechanical and electrical properties, respectively. In addition, the incorporation of magnetite nanoparticles (Fe3O4NPs) endows the hydrogel with magnetic properties. After structural, (electro)chemical, and physical characterization, we successfully performed dynamic and continuous transport of the hydrogel through disassembly, transporting the polymer–Fe3O4NP aggregates toward a target using magnetic fields and its final reassembly to recover the multifunctional hydrogel in the cross-linked state. We also successfully tested the PEDOT/Alg/Fe3O4NP hydrogel for temperature sensing and magnetic hyperthermia after various disassembly/re-cross-linking cycles. The present methodology can pave the way to a new generation of soft electronic devices with the capacity to be remotely transported.

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In the present study, we sought to better characterize the patients with coronavirus disease 2019 (COVID-19) most at risk of severe, outpatient thrombosis by defining the patients hospitalized with COVID-19 with arterial or venous thrombosis diagnosed at admission.

Introduction: The prevalence of chronic kidney disease (CKD) is high among kidney neoplasm patients because of the overlapping risk factors. Our purpose is to identify kidney cancer survivors with higher CKD risk.Methods: We studied a retrospective cohort of 361 kidney tumor patients with partial or radical nephrectomy. Linear mixed model was performed.Results: Of patients with follow-up >3 months, 84% were identified retrospectively to fulfill criteria for CKD diagnosis, although CKD was documented in only 15%. Urinalysis was performed in 205 (57%) patients at the time of nephrectomy. Multivariate analysis showed interstitial fibrosis and tubular atrophy (IFTA) >25% (p= 0.005), severe arteriolar sclerosis (p= 0.013), female gender (p= 0.024), older age (p= 0.012), BMI ⩾ 25 kg/m2(p< 0.001), documented CKD (p< 0.001), baseline eGFR ⩽ 60 ml/min/1.73 m2(p< 0.001), and radical nephrectomy (p< 0.001) were independent risk factors of lower eGFR at baseline and during follow-up. Average eGFR decreased within 3 months post nephrectomy. However, patients with different risk levels showed different eGFR time trend pattern at longer follow-ups. Multivariate analysis of time × risk factor interaction showed BMI, radical nephrectomy and baseline eGFR had time-dependent impact. BMI ⩾ 25 kg/m2and radical nephrectomy were associated with steeper eGFR decrease slope. In baseline eGFR > 90 ml/min/1.73 m2group, eGFR rebounded to pre-nephrectomy levels during extended follow-up. In partial nephrectomy patients with baseline eGFR ⩾ 90 ml/min/1.73 m2(n= 61), proteinuria (p< 0.001) and BMI (p< 0.001) were independent risk factors of decreased eGFR during follow up.Conclusions: As have been suggested by others and confirmed by our study, proteinuria and CKD are greatly under-recognized. Although self-evident as a minimum workup for nephrectomy patients to include SCr, eGFR, urinalysis, and proteinuria, the need for uniform applications of this practice should be reinforced. Non-neoplastic histology evaluation is valuable and should include an estimate of global sclerosis% (GS) and IFTA%. Patients with any proteinuria and/or eGFR ⩽ 60 at the time of nephrectomy or in follow-up with urologists, and/or >25% GS or IFTA, should be referred for early nephrology consultation.

Motion capturing systems produce a large amount of information on the motion of individuals. A growing number of data reduction techniques have been developed to reduce the amount of data while keeping relevant information. An overview that compares and identifies the advantages and disadvantages of these methods on cyclic motion data is, however, lacking. Therefore, this study aims to assess the features of different data reduction techniques by applying them to a large public gait data set. Due to the periodicity of cyclic data, an individual cycle can be isolated and analyzed. The analysis of single cycles requires preprocessing steps to segment and align the individual cycles. The latter is needed to isolate the amplitude variability. Three alignment procedures with different complexity, namely Linear Length Normalization (LLN), Piecewise LNN (PLLN) and Continuous Registration (CR), are assessed based on the amount of resulting variation. Subsequently three data reduction techniques (i.e. Principal Component Analysis (PCA), Principal Polynomial Analysis (PPA) and Multivariate Functional PCA (MFPCA)) are applied to the aligned single gait cycles. The data reduction techniques are evaluated based on the in-sample error, the out-of-sample error, the compactness and the computation time to produce a model. The curves aligned with CR have the lowest remaining variation and thus the lowest amount of remaining phase variation. The differences between the different data reduction techniques appear to be minimal. PPA shows to be the most compact and is therefore recommended when compactness is crucial and out-of-sample performance is less essential. The use of MFPCA is advised when one wants to include data from different sources. PCA is suggested when computation time is key.

Background and Purpose: Hospital 30-day readmissions in patients with primary neurological problems are not well characterized. We sought to determine patient characteristics associated with readmission across 3 different inpatient neurology services at New York University Langone Hospital.Methods: We retrospectively reviewed all 30-day readmissions from the General Neurology, Epilepsy, and Stroke services at NYULH Brooklyn and Manhattan campuses from 2016-2017 and compared them to a random sample of non-readmitted neurology patients. We used univariate analyses to compare demographics, clinical characteristics, disease specific metrics, and discharge factors of non-readmitted and readmitted groups and binomial logistic regression to examine specific variables with adjustment for confounders.Results: We included 284 patients with 30-day readmissions and 306 control patients without readmissions matched by discharge location and service. After adjusting for confounders, we found that the following factors were associated with increased readmission risk: a recent hospital encounter increased risk for all services, increased number of medications at discharge, intensive care unit stay, higher length of stay, and prior history of seizure for the General Neurology Service, increased number of medications at discharge for the Epilepsy Service, and active malignancy and higher discharge modified Rankin Scale score for the Stroke Service.Conclusion: This study identifies potential risk factors for readmission in patients across multiple neurology services. Further research is needed to establish whether these risk factors hold across multiple institutions.

a) Establish reference values for bone parameters by using the speed of sound (SOS, m/s) of broadband ultrasound attenuation (BUA, dB/MHz) and establish a bone quality index (BQI=αSOS+βBUA) for children and adolescents living in a region of moderate altitude, b) compare bone parameters with an international standard (with different ethnic, socio-economic, and lifestyle backgrounds) by using ultrasound of the calcaneus (heel bone) (QUS).

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Stimuli-responsive biomaterials have attracted significant attention for the construction of on-demand drug release systems. The possibility of using external stimulation to trigger drug release is particularly enticing for hydrophobic compounds, which are not easily released by simple diffusion. In this work, an electrochemically active hydrogel, which has been prepared by gelling a mixture of poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) and alginate (Alg), has been loaded with curcumin (CUR), a hydrophobic drug with a wide spectrum of clinical applications. The PEDOT/Alg hydrogel is electrochemically active and organizes as segregated PEDOT- and Alg-rich domains, explaining its behavior as an electroresponsive drug delivery system. When loaded with CUR, the hydrogel demonstrates a controlled drug release upon application of a negative electrical voltage. Comparison with the release profiles obtained applying a positive voltage and in the absence of electrical stimuli indicates that the release mechanism dominating this system is complex because of not only the intermolecular interactions between the drug and the polymeric network but also the loading of a hydrophobic drug in a water-containing delivery system.

The discovery of high-performing and stable materials for sustainable energy applications is a pressing goal in catalysis and materials science. Understanding the relationship between a material’s structure and functionality is an important step in the process, such that viable polymorphs for a given chemical composition need to be identified. Machine-learning-based surrogate models have the potential to accelerate the search for polymorphs that target specific applications. Herein, we report a readily generalizable active-learning (AL) accelerated algorithm for identification of electrochemically stable iridium oxide polymorphs of IrO2and IrO3. The search is coupled to a subsequent analysis of the electrochemical stability of the discovered structures for the acidic oxygen evolution reaction (OER). Structural candidates are generated by identifying all 956 structurally unique AB2and AB3prototypes in existing materials databases (more than 38000). Next, using an active learning approach, we find 196 IrO2polymorphs within the thermodynamic amorphous synthesizability limit and reaffirm the global stability of the rutile structure. We find 75 synthesizable IrO3polymorphs and report a previously unknown FeF3-type structure as the most stable, termed α-IrO3. To test the algorithms performance, we compare to a random search of the candidate space and report at least a 2-fold increase in the rate of discovery. Additionally, the AL approach can acquire the most stable polymorphs of IrO2and IrO3with fewer than 30 density functional theory optimizations. Analysis of the structural properties of the discovered polymorphs reveals that octahedral local coordination environments are preferred for nearly all low-energy structures. Subsequent Pourbaix Ir–H2O analysis shows that α-IrO3is the globally stable solid phase under acidic OER conditions and supersedes the stability of rutile IrO2. Calculation of theoretical OER surface activities reveal ideal weaker binding of the OER intermediates on α-IrO3than on any other considered iridium oxide. We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.

Background: We explored factors associated with admission and discharge code status after nontraumatic intracranial hemorrhage.Methods: We extracted data from patients admitted to our institution between January 1, 2013, and March 1, 2016 with nontraumatic intracerebral hemorrhage or subarachnoid hemorrhage who had a discharge modified Rankin Scale (mRS) of 4 to 6. We reviewed data based on admission and discharge code status.Results: Of 88 patients who met inclusion criteria, 6 (7%) were do not resuscitate (DNR) on admission (aDNR). Do not resuscitate on admission patients were significantly older than those who were full code on admission (P =0.04). There was no significant difference between admission code status and sex, marital status, active cancer, premorbid mRS, admission Glasgow Coma scale (GCS), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, or bleed severity. At discharge, 66 (75%) patients were full code (dFULL), 11 (13%) were DNR (dDNR), and 11 (13%) were comfort care. African American and Hispanic patients were significantly more likely to be dFULL than Asian or white patients (P =.01) and less likely to be seen by palliative care (P =.004). Patients with less aggressive code status had higher median APACHE II scores (P =.008) and were more likely to have active cancer (P =.06). There was no significant difference between discharge code status and sex, age, marital status, premorbid mRS, discharge GCS, or bleed severity.Conclusions: Limitation of code status after nontraumatic intracranial hemorrhage appears to be associated with older age, white race, worse APACHE II score, and active cancer. The role of palliative care after intracranial hemorrhage and the racial disparity in limitation and de-escalation of treatment deserves further exploration.

ABSTRACTMacroautophagy/autophagy is a multi-step process that leads to cargo degradation via the fusion of hydrolases-containing lysosomes with cargo-loaded autophagosomes. For this process to occur, autophagosomes are directionally transported by molecular motors toward the nucleus, where they fuse with lysosomes for cargo degradation. The molecular basis for this regulation, including the cell machinery required for this directional transport, has not been fully identified. Using a combination of proteomic and live-imaging approaches in mammalian cells, including primary neurons, we describe that the phosphorylation of the autophagosome protein Atg8/LC3B by the Hippo kinase STK4/MST1, an event we previously reported to be required for autophagy completion, reduces the binding of the transport-related protein FYCO1 to MAP1LC3B/LC3B. This event in turn allows the proficient microtubule-based transport of autophagosomes toward the perinuclear area, thus facilitating the contact of autophagosomes with lysosomes. In the absence of LC3B phosphorylation, autophagosomes undergo aberrant transport including increased movement toward the cell periphery resulting in reduced autophagosome-lysosome colocalization. Thus, LC3B phosphorylation modulates the directional transport of autophagosomes to meet with lysosomes in the perinuclear area, a crucial event in ensuring autophagic degradation of cargo.

In photocatalysis, surface engineered CeO2could be vital due to oxygen vacancies arise from multiple valency, i.e. Ce3+and Ce4+. This study reports photocatalytic properties of g-C3N4/CeO2composite synthesized by a facile method in the presence of l-arginine. Physicochemical properties of g-C3N4/CeO2material were analyzed through various characterization techniques such as XRD, UV–Vis, physisorption, etc., and correlated with its photocatalytic activity. Observed bandgap of the synthesized composite material was in the visible region, around 2.8eV which is less than that of typical ceria, but higher than bandgap of exfoliated g-C3N4. On the further side, N doping into CeO2was confirmed through XPS analysis. It is estimated that synthesis method aided for the N doping, which further played key role in lowering the bandgap of g-C3N4/CeO2composite. Finally, Photocatalytic activity of g-C3N4/CeO2composite was analyzed through degradation of an herbicide i.e. diuron, and the study revealed the good performance of the catalyst.