Miracle-dz/UniFAR-FTUs huggingface dataset:
A Negative Control Outcome Regression Accounting for Unobserved Confounding and Lagged Causal Effects

Background: Epidemiologists are increasingly interested in using negative controls to eliminate unobserved confounding. Particularly, difference-in-differences method, which uses pre-exposure outcomes as negative control outcomes, is widely used. However, it obtains biased estimations when pre-exposure outcome has lagged causal effect on post-exposure outcome.Methods: Taking advantage of pre-exposure outcomes as negative control outcomes, Negative Control Outcome Regression (NCOR) is proposed to eliminate unobserved confounding. The intercept term of NCOR provides an unbiased causal effect estimate of exposure on post-exposure outcome, and the slope minus 1 denotes the lagged causal effect estimation of pre-exposure outcome on post-exposure outcome. We then illustrate the potential of NCOR in a challenging application to estimate the causal association of PM₂. ₅ on all-cause mortality rates (AMR) and lagged causal effect of pre AMR on post AMR.Results: Both theoretical justifications and simulation studies validate that the causal effect of exposure on outcome, along with the lagged causal effect of outcomes are identifiable and can be estimated by proposed NCOR model. The application results demonstrate that the previously estimated association between PM₂. ₅ and AMR can be attributed to the unobserved confounding. Furthermore, the NCOR model reveal that pre AMR has no causal association with post AMR.Conclusion: The proposed NCOR model can obtain unbiased and robust causal effect estimation of exposure on outcome, and the lagged causal effect of outcomes. The proposed NCOR is implemented as an R package, called NCOR, and is freely available on GitHub.
An Open-Source Soft-Microcontroller Implementation Using an ARM Cortex-M0 on FPGA

There is a myriad of projects that could be deployed on FPGA for architectural exploration. However, open-source platforms are scarce, and one with embedded software and operating system support to the application-specific hardware could not be found in the literature. We present an open-source soft-microcontroller architecture based on an ARM Cortex-M0, adaptable to different amounts of cores or new components, supporting an end-to-end deployment from code compilation using arm-gcc to loading the binary into the HDL memory cores. The proposed design is validated through simulation and implementation on a KC705 development kit, demonstrating busy-wait polling, DMA transfer, and deterministic real-time processing through FreeRTOS.
Elaboração de um serviço de Recomendação Híbrido Ponderado e Misto implantado em Webservice RESTful

Os sistemas de recomendação possuem o objetivo de sugerir aos seus usuário itens, produtos ou informações de acordo com seus interesses, fazendo com que sua utilização seja cada vez mais difundida, tanto no mercado como em processos de tomada de decisão. Com base no contexto descrito, esse trabalho busca disponibilizar um serviço de recomendação híbrido implantado sobre a estrutura de um WebService RESTful, focado na estruturação dos resultados obtidos em algoritmos de recomendação baseados em filtragem colaborativa, conteúdo e hébrida (utilizando as abordagens ponderada e mista). Foi elaborado um estudo de caso baseado em avaliações de musicas dos mais variados gêneros. O algoritmo de filtragem híbrida ponderada obteve os melhores resultados com 81,4% de acerto nas recomendações, bem como, media das recomendações estatisticamente iguais as medias de avaliações, com base no teste de T.
A multiple convex Lyapunov function for asynchronous control of discrete-time switched systems

In this paper, the problem of asynchronous control for a class of discrete-time switched systems is investigated under mode-dependent integrated dwell time (MDIDT) switching. By constructing a time-dependent convex function, a multiple convex Lyapunov function (MCLF) is firstly proposed for the asynchronous control of the switched systems. Under the MDIDT switching strategy, the matching interval is divided reasonably, and the convex function combination is constructed on the partitioned interval. Under asynchronous switching, the Lyapunov function is continuous when the subsystem mode is switched, but discrete when the controller mode is changed. Then, the increase of the Lyapunov function in the mismatched interval will be offset by the attenuation in the matched interval. In light of these merits, the stability results of the system are deduced, and the asynchronous controller is devised to guarantee the globally uniformly exponentially stability of the closed-loop system. Comparing with the traditional asynchronous control methods, the proposed method has less conservative results and larger stability regions. Finally, a numerical example and an application example are demonstrated to verify the validity and superiority of the asynchronous control scheme.
Host–Guest Inclusion Complexes of Essential Oils with Strong Antibacterial and Antifungal Features in Beta-Cyclodextrin for Solid-State Pharmaceutical Applications

Essential oils are widely recognized as natural alternatives to pharmaceutical antibacterial and antifungal agents. With respect to standard pharmaceutics, the advantages of essential oils are their (i) low production costs, (ii) lack of chemical and biochemical drawbacks that are intrinsic to the synthetic production process and (iii) good tolerance by humans. On the other hand, the liquid nature of essential oils poses concerns about their actual application in different therapeutic issues regarding their persistence and the ability to control or prolong drug release. In this study, two essential oils from oregano and winter savory showing antibacterial and antifungal features were complexed in a solid state with beta-cyclodextrin. Host–guest inclusion complexes were characterized using FT-IR spectroscopy, ESI-MS and GC-MS techniques. Manyfold terpenic and non-terpenic components of the oils could be observed and unambiguously identified as being included inside the carbohydrate hosts. Many of them provided a specific biocidal action. Indeed, essential oil host–guest inclusion products were tested against two Candida species and an S. aureus reference strain, showing that the oils effectively maintained their liquid performances. Solid-state tablets of the essential oil inclusion complexes embedded in polyvinylpyrrolidone could be obtained. These results pave the way for the solid-state application of essential oils in antibacterial and antifungal pharmaceutical treatments.
Monolithically Integrating Non-Volatile Main Memory over the Last-Level Cache

Many emerging non-volatile memories are compatible with CMOS logic, potentially enabling their integration into a CPU’s die. This article investigates such monolithically integrated CPU–main memory chips. We exploit non-volatile memories employing 3D crosspoint subarrays, such as resistive RAM (ReRAM), and integrate them over the CPU’s last-level cache (LLC). The regular structure of cache arrays enables co-design of the LLC and ReRAM main memory for area efficiency. We also develop a streamlined LLC/main memory interface that employs a single shared internal interconnect for both the cache and main memory arrays, and uses a unified controller to service both LLC and main memory requests. We apply our monolithic design ideas to a many-core CPU by integrating 3D ReRAM over each core’s LLC slice. We find that co-design of the LLC and ReRAM saves 27% of the total LLC–main memory area at the expense of slight increases in delay and energy. The streamlined LLC/main memory interface saves an additional 12% in area. Our simulation results show monolithic integration of CPU and main memory improves performance by 5.3× and 1.7× over HBM2 DRAM for several graph and streaming kernels, respectively. It also reduces the memory system’s energy by 6.0× and 1.7×, respectively. Moreover, we show that the area savings of co-design permits the CPU to have 23% more cores and main memory, and that streamlining the LLC/main memory interface incurs a small 4% performance penalty.
A gender wise correlation analysis between glycated hemoglobin level and estimated glomerular filtration rate among type 2 diabetes patients

Background: Studies found inconsistent relationship between glycated hemoglobin (HbA1C) and estimated glomerular filtration rate (eGFR) in diabetes. Hence, population based studies are warranted. This study was aimed to find out the prevalence of good glycemic control and correlation of HbA1c level with eGFR in male and female type 2 diabetes patients. Methods: A cross sectional study was designed among type 2 diabetes patients. Medical records of patients’ in the inclusion criteria were abstracted for demographic characteristics, HbA1c and serum creatinine level. Patients were grouped into male and female and further sub grouped as with or without good glycemic control (HbA1c ≤ 7%). Data were statistically analyzed.Results: A total of 465 diabetes patients (186 males and 279 females) were included. Among the total, more female patients were in good glycemic (p=0.0008) control. Gender wise comparison showed that HbA1c level was statistically significant between male and female patients in age groups below 60 years (p<0.05). HbA1c level, at >7%, showed an inverse correlation with eGFR in both male (r=- 0.3208, p=0.0008) and female patients (r =-0.3680, p<0.0001). For every 1% rise in HbA1c, eGFR declined by 10 ml/min/1.73 m2 in males and 13 ml/min/1.73 m2 in females.Conclusions: More female patients were in good glycemic control. HbA1c level above 7% showed an inverse correlation with eGFR in both male and female patients. For every 1% rise in HbA1c, the eGFR declined by 10 ml/min/1.73 m2 in male and 13 ml/min/1.73 m2 in female patients.
Assessment of total bacterial diversity in whiteleg shrimps and its aquaculture environment in Pangkajene and Banyuwangi, Indonesia

Detection of bacterial diversity in whiteleg shrimps and its rearing water is a vital first step in monitoring aquaculture activities. Bacterial community imbalance in whiteleg shrimps and its rearing water influences the quality and quantity of shrimp production. Identifying the bacterial community provides basic information related to dominant bacterial groups in whiteleg shrimps and environments, providing recommendations for proper environmental monitoring and management. In this study, we investigated bacterial community structure in the rearing water and intestinal tract of whiteleg shrimp (Litopenaeus vannamei) collected from two sites, i.e., Pangkajene, South Sulawesi (SU) and Banyuwangi, East Java (BW), Indonesia. The bacterial community was analyzed using amplicon sequencing with Illumina sequencing platform based on the V3-V4 region of the 16S rRNA genes. Bacterial diversity and composition were found differed between the rearing water and the shrimps’ intestines. Bacterial diversity in the rearing water of Banyuwangi (W.BW) was higher than that of Pangkajene (W.SU). Proteobacteria, Bacteroidetes, and Firmicutes were found as the most dominant phyla in rearing water from both farms, while distinct bacterial composition was observed in the shrimps’ intestines. The shrimp intestine from Banyuwangi (U.BW) was dominated by Firmicutes (22.36%), Proteobacteria (22.33%), and Verrucomicrobia (21.11%). In contrast, the shrimp intestine from Pangkajene (U.SU) was highly dominated by Tenericutes (88.54%), followed by Proteobacteria (4.66%), and Firmicutes (2.27%). The difference in bacterial community structure between the rearing water and shrimps’ intestines suggested that the host intestinal environment might have greater selective pressure for bacterial composition inhabiting L.vannamei intestines. Our observations suggest that the shrimps cultured in the rearing water with the similar dominant bacterial group have specific intestinal bacterial diversity.
A Note on the Multi-Colored Bipartite Ramsey Number for Paths

For bipartite graphs [Formula: see text], the bipartite Ramsey number [Formula: see text] is the least positive integer [Formula: see text] so that any coloring of the edges of [Formula: see text] with [Formula: see text] colors will result in a copy of [Formula: see text] in the [Formula: see text]th color for some [Formula: see text]. In this paper, we get the exact value of [Formula: see text], and obtain the upper and lower bounds of [Formula: see text], where [Formula: see text] denotes a path with [Formula: see text] vertices.
Intelligent approach for optimal sizing in photovoltaic panel-battery system and optimizing smart grid energy

Renewable energy plays a very important role in solving energy problems, and solar energy is one of the most important renewable sources, especially in sunny countries. This paper deals with two problems: The first one is about optimal sizing in a photovoltaic panel (PVP)-battery system, and the second consists in energy management in smart grids. To achieve the first objective, an adaptive neuro-fuzzy inference system (ANFIS) estimation algorithm is developed in order to estimate a database of instantaneous photovoltaic power. The estimated instantaneous photovoltaic power is used in an optimal algorithm to size a PVP-battery power station to supply a 1.5 kW AC load. For the second objective, a deep learning forecasting algorithm is realized to estimate the smart grid parameters so as to optimize the consumption energy. All results are checked carrying out Matlab simulation using real weather data. The simulation results give a good performance of our proposed sizing and management systems.
Towards (Hyper)Local Public Sphere: Comparison of Civic Engagement across the Global North

The role of hyperlocal media is of increasing relevance as traditional local journalism experiences a decline due to centralisation and consolidation. The affordances of Internet and digital technologies also enable hyperlocal initiatives to enhance civic engagement in localities and serve as a place and resource for local deliberative processes. This study examines how the aims, perceptions and practices of hyperlocal media vary in three countries of the Global North—Sweden, Finland and Russia—and what implications this has for connectedness and civic engagement in local public spheres. The context of different media systems and local political regimes help to explore possibilities and limitations of hyperlocals as agents of place-oriented civic engagement. The data includes interviews with practitioners and analysis of selected hyperlocal media. Our results indicate that hyperlocal media practitioners in all three countries aim to provide local people and communities with a voice, and to enhance resident engagement in local life. We reveal three civic roles of hyperlocal media: (i) information provider, (ii) community builder, and (iii) civic mediator. Practices of civic engagement used by hyperlocal media range from relying on civic journalism to fostering civic debates and can be classified in two main categories: civic information and civic debate and interaction. The perceptions and practices of these hyperlocal media are, to some extent, similar because of comparable changes and challenges regarding the local media and public spheres. At the same time, the perceptions of civic roles vary, reflecting both the developments and differences in the countries’ media spheres and political regimes. This research raises a critical question about hyperlocal practitioners’ understanding of their own roles and aims, and in addition, how differences in media cultures and local regimes affect their performance as agents of local public spheres.
Synthesizing Realistic Human Dance Motions Conditioned by Musical Data using Graph Convolutional Networks

Learning to move naturally from music, i.e., to dance, is one of the most complex motions humans often perform effortlessly. Existing techniques of automatic dance generation with classical CNN and RNN models undergo training and variability issues due to the non-Euclidean geometry of the motion manifold. We design a novel method based on GCNs to tackle the problem of automatic dance generation from audio. Our method uses an adversarial learning scheme conditioned on the input music audios to create natural motions. The results demonstrate that the proposed GCN model outperforms the state-of-the-art in different experiments. Visual results of the motion generation and explanation can be visualized through the link: http://youtu.be/fGDK6UkKzvA
Impacts of the internet on perceptions of governance at the community level: the case of Jiangqiao Township in Shanghai, China

PurposeThe rate of urbanisation in China has accelerated community heterogeneity, and yet it has also led to challenges and problems in community governance. This trend has been accompanied by the rapid expansion of information and communication technology (ICT) and online activities. Based on the example of Jiangqiao Township in Shanghai, this paper aims to probe the link between online participation using the internet and its impacts on social capital formation and community development.Design/methodology/approachA literature review was conducted, and a case study method based on quantitative data was applied to test the theoretical framework in the interactions of users’ online participation and perceptions of community governance.FindingsParticipation in an online community through the internet was found to foster new social capital. Distributed social capital had a positive impact on perceptions of governance at the community level, which was due to the resulting network density and social trust of the locality.Originality/valueThis study offers an expanded perspective on the impact of the internet on the behaviour of netizens in China in the context of community governance in new settlements and townships. During the COVID-19 pandemic, it is interesting to investigate how the use of mass communication channels, such as the internet and other digital platforms, affects social behaviour and generates new social norms. This study offers quantitative evidence from China to support the theory of Putnam (1993; 1995a). It thus extends beyond the field of sociology to the fields of public administration and urban development.
Vine Copula Graphical Models in the Construction of Biological Networks

The Gaussian copula graphical model (GCGM) is one of the major mathematical models for high dimensional biological networks. Basically, this model uses the lasso regression of the Gaussian graphical model (GGM) whose precision matrix is described by the Gaussian copula. In this way, it can overcome the dimensional limitation of GGM by partitioning the joint density into marginals and using the Bayesian inference for the model parameters. But from the application in bench-mark datasets, it is seen that although this model is successful in certain systems, it may not fit well for non-normal multivariate observations. Hence, here, we propose the vine copulas to relax the strict normality assumption of GCGM and describe networks from a variety of copulas’ alternates such as Frank and Gumbel besides Gaussian copulas. For this purpose, we evaluate the best fitted bivariate copula distribution for every pairwise gene and compute the estimated adjacency matrix which denotes the presence of edges. In this work, we assess the performance of our proposed approach in two biological network dataset and one economical binary data named Rochdale data set to compare the estimated systems via distinct accuracy measures. The data sets were analyzed by different copula vine types to see which type should be considered for data.
Pyro-catalytic hydrogen evolution by Ba0.7Sr0.3TiO3 nanoparticles: harvesting cold–hot alternation energy near room-temperature

Photocatalytic hydrogen evolution, as an environmental-friendly, energy-saving and simple process, has been widely reported. However, there are some important factors that prohibit practical application of photocatalytic hydrogen production, including the low efficiency of solar energy utilization, and the lack of response in the dark. Temperature fluctuation is a very common phenomenon in our daily life, which is rarely reported for use for hydrogen production. Here we demonstrate direct hydrogen evolution through the harvesting of cold–hot 298–323 K (25–50 °C) alternation energy by using pyroelectric nanomaterial Ba0.7Sr0. 3TiO3 (BST). The yield of hydrogen achieved was 46.89 μmol per gram of catalyst after 36 thermal cycles and the rate of hydrogen generation was up to 1.30 μmol g−1 per thermal cycle. The minimum of the conduction band of BST is more negative than the conduction band level of H+/H2, enabling the reduction of water to form hydrogen. This efficient and eco-friendly pyro-catalytic method provides a promising future for hydrogen evolution utilizing natural cold–hot temperature fluctuation energy.
Phylogenetic analysis and trait evolution of ant cocoons

Most ant species have lost the ability to spin cocoons. To explore the evolution of cocoon loss within Formicidae, we perform an ancestral state reconstruction of cocooned pupae across a genus-level phylogeny and use a sister clade analysis to determine the impact of cocoon evolution on ant speciation. Then, we fit models of correlated evolution between cocoon status and several other organismal traits. We find that the re-emergence of cocoons is rare and that “naked” lineages display an increased rate of speciation in 5 out of 9 sister group comparisons. Models of correlated evolution with cocoon status were favored for metapleural gland and worker polymorphism. Metapleural gland favored rates of evolution were inconclusive, while worker polymorphism displayed a higher transition rate towards polymorphism coupled with cocoon loss. These results suggest that cocoon loss may allow for other complex traits to develop and may represent a novel example of relaxed selection.
Measuring shallow convective mass flux profiles in the trade wind region

Mass flux is a key quantity in parameterizations of shallow convection. To estimate the shallow convective mass flux as accurately as possible, and to test these parameterizations, observations of this parameter are necessary. In this study, we show how much the mass flux varies and how this can be used to test factors that may be responsible for its variation. Therefore, we analyze long term Doppler radar and Doppler lidar measurements at the Barbados Cloud Observatory over a time period of 30 months, which results in a mean mass flux profile with a peak value of 0.03 kg m−2 s−1 at an altitude of ~730 m, similar to observations from Ghate et al. (2011) at the Azores Islands. By combining Doppler radar and Doppler lidar measurements, we find that the cloud base mass flux depends mainly on the cloud fraction and refutes an idea based on large eddy simulations, that the velocity scale is in major control of the shallow cumulus mass flux. This indicates that the large scale conditions might play a more important role than what one would deduce from simulations using prescribed large-scale forcings.