Miracle-dz/UniFAR-FTUs huggingface dataset:
Post-exercise Hypotension in Patients With Coronary Artery Disease

Background: Blood pressure (BP) and hemodynamic changes occurring in the recovery phase after a single bout of exercise have not been extensively studied in coronary artery patients, despite the potential clinical implications of reducing BP through exercise. This study aimed at investigating the hemodynamic and arterial baroreflex mechanisms possibly involved in post-exercise hypotension (PEH) in patients with coronary artery disease. Methods: In 42 normotensive coronary artery patients undergone a Cardiac Rehabilitation Program, we evaluated before and after their daily exercise training session: blood pressure (BP) and heart rate (HR). In a subgroup (n = 29), daily BP profile was also evaluated by ambulatory BP monitoring. In those patients showing PEH (n = 15), we evaluated: Cardiac Output (CO), Stroke Volume (SV), total peripheral resistances (TPR), forearm (FVR) and calf (CVR) vascular resistances, and spontaneous baroreflex sensitivity (BRS). Results: After exercise TPR was significantly reduced with a similar contribution from CVR and FVR, whereas CO and SV significantly increased. BRS showed a significant reduction mainly due to a BRS decrease in response to hypertensive stimuli. Systolic BP (SBP) was significantly reduced for 12 h after the end of a single exercise session. Conclusion: These findings indicate that in coronary artery patients, the recovery phase after exercise is characterized by PEH which is mediated mainly by a generalized peripheral vasodilation and appears to influence BP behavior throughout the daily life. Finally, the cardiac component of the arterial baroreflex seems to contribute indirectly to BP reduction occurring after exercise.
Integrative Analyses of Biochemical Properties and Transcriptome Reveal the Dynamic Changes in Leaf Senescence of Tobacco (Nicotiana tabacum L.)

Leaf senescence is an important process of growth and development in plant, and it is a programmed decline controlled by a series of genes. In this study, the biochemical properties and transcriptome at five maturity stages (M1∼M5) of tobacco leaves were analyzed to reveal the dynamic changes in leaf senescence of tobacco. A total of 722, 1,534, 3,723, and 6,933 genes were differentially expressed (DEG) between M1 and M2, M1 and M3, M1 and M4, and M1 and M5, respectively. Significant changes of nitrogen, sugars, and the DEGs related to metabolite accumulation were identified, suggesting the importance of energy metabolism during leaf senescence. Gene Ontology (GO) analysis found that DEGs were enriched in biosynthetic, metabolic, photosynthesis, and redox processes, and especially, the nitrogen metabolic pathways were closely related to the whole leaf senescence process (M1∼M5). All the DEGs were grouped into 12 expression profiles according to their distinct expression patterns based on Short Time-series Expression Miner (STEM) software analysis. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis found that these DEGs were enriched in pathways of carbon metabolism, starch and sucrose metabolism, nitrogen metabolism, and photosynthesis among these expression profiles. A total of 30 core genes were examined by Weight Gene Co-expression Network Analysis (WGCNA), and they appeared to play a crucial role in the regulatory of tobacco senescence. Our results provided valuable information for further functional investigation of leaf senescence in plants.
Feature Convolutional Networks

Convolutional neural networks are among the most successful deep learning models used for image processing, computer vision and natural language processing applications. In this paper, we define convolution operator for numerical tabular features and thus propose feature convolutional network model for machine learning tasks. Feature convolutional networks contain feature convolution layer to extract pairwise feature convolutions in the relational feature spaces. Compared with the baseline multi-layer neural network model, the feature convolutional network gains better performance among all the experiments. The experiments results suggest that feature convolutional networks can generate efficient features automatically and provide better performance through automatic feature learning. The demo code is at https://github.com/info-ruc/FeatConvNet.
Population Size and Structure of the Ornate Diamondback Terrapin (Malaclemys terrapin macrospilota) on Small Gulf Coast Islands in Florida

Abstract. Management decisions for species are often based on estimates of abundance, which can be difficult to obtain for species that are a challenge to survey, as are some reptiles. Information on abundance and population status are lacking for the diamondback terrapin (Malaclemys terrapin), a coastal species that inhabits brackish waters and plays an important trophic role in the saltmarsh ecosystem. Population declines are suspected throughout the species' range, and its population status is unknown in Florida. Of the 5 subspecies that inhabit Florida's coastline, the most understudied subspecies may be the ornate diamondback terrapin (M. t. macrospilota). We conducted a capture–mark–recapture study of M. t. macrospilota during the summer of 2013 on 3 adjacent coastal islands in the eastern panhandle of Florida that provided information on population size and demography. We captured 334 individuals; modeling estimated a population size of 1282 (867–1905 95% CI) and a density of 150 terrapins/ha. Population size decreased throughout the study, suggesting that this population is an aggregation that seasonally emigrates from the islands. This emigration trend was more evident for females. Males outnumbered females 4:1, and females were larger than males. Our study is the first to report on M. t. macrospilota populations in the Florida panhandle. We recommend collaborative, long-term population monitoring at our sites to estimate population trends that will be crucial for managing this subspecies.
Approximate solutions for modal propagation in channel dielectric waveguides

A method allowing the approximate modal solutions of a truly two-dimensional-channel, dielectric waveguide to be evaluated easily is presented. In principle, the approximation can be applied iteratively until an arbitrary numerical accuracy is achieved. The application of the method to planar optical waveguides is illustrated; the results obtained for a step semicircular channel guide are presented as an example. It is shown that, within its limitations, the method provides an approximation that lies within 1% of the converged value. >
Transnational Dimensions of Civil War

Existing research has related civil war primarily to country-specific factors or processes that take place within individual states experiencing conflict. Many contemporary civil wars, however, display a transnational character, where actors, resources, and events span national boundaries. This article challenges the 'closed polity' approach to the study of civil war, where individual states are treated as independent entities, and posits that transnational factors and linkages between states can exert strong influences on the risk of violent civil conflict. Previous research has shown that conflicts in a state's regional context can increase the risk of conflict, but the research has not distinguished between different varieties of transnational linkages that may underlie geographic contagion, and it has failed to consider the potential influences of domestic attributes. The article develops and evaluates a series of hypotheses on how transnational factors can influence the risk of conflict and the prospects for maintaining peace in a conditional autologistic model, including country-specific factors often associated with civil wars. The results suggest that transnational linkages between states and regional factors strongly influence the risk of civil conflict. This, in turn, implies that the risk of civil war is not determined just by a country's internal or domestic characteristics, but differs fundamentally, depending on a country's linkages to other states.
Dialogue as a Response to the Psychiatrization of Society? Potentials of the Open Dialogue Approach

In recent decades, the use of psychosocial and psychiatric care systems has increased worldwide. A recent article proposed the concept of psychiatrization as an explanatory framework, describing multiple processes responsible for the spread of psychiatric concepts and forms of treatment. This article aims to explore the potentials of the Open Dialogue (OD) approach for engaging in less psychiatrizing forms of psychosocial support. While OD may not be an all-encompassing solution to de-psychiatrization, this paper refers to previous research showing that OD has the potential to 1) limit the use of neuroleptics, 2), reduce the incidences of mental health problems and 3) decrease the use of psychiatric services. It substantiates these potentials to de-psychiatrize psychosocial support by exploring the OD’s internal logic, its use of language, its processes of meaning-making, its notion of professionalism, its promotion of dialogue and how OD is set up structurally. The conclusion touches upon the dangers of co-optation, formalization and universalization of the OD approach and stresses the need for more societal, layperson competencies in dealing with psychosocial crises.
How Does Human Capital Spillover Inflow of Foreign Workers Affect Economic Growth?

The ASEAN Economic Community provides opportunities for foreign workers to enter Indonesia, including Central Java Province. The existence of these foreign workers tends to negatively and positively impact the regional economic growth of the country. Therefore, this study aims to analyze the effects of foreign workers’ human capital spillover inflow on the economic growth of Central Java. The Euclidean distance spatial weight matrix was used to calculate the spatial autoregressive model from 2015 to 2020. These results indicate that the presence of skilled foreign workers positively impacts increasing economic growth in Central Java Province. The influx of foreign workers, along with the influx of investment, encourages local workers to follow the performance of foreign workers. This study suggests a policy to encourage technology transfer from foreign workers to local workers. The government is also expected to strengthen local workers’ productivity to compete with foreign workers.
Minimizing demolition wastes in Hong Kong public housing projects

Being one of the major housing developers in Hong Kong, the Hong Kong Housing Authority (HA) carries out a large number of construction and demolition projects. As a result, a large amount of construction and demolition waste is produced. As for demolition projects, demolition wastes usually contain a large amount of reusable materials. If sorted out properly, these materials could be better reused or recycled. Two case studies have been carried out on public housing projects to quantify the recovery rates of various types of demolition wastes in demolition projects and to assess the implementation of on‐site sorting requirements. The current practices of demolition contractors in Hong Kong mainly focus on the working procedures and waste generation during the main demolition stage and sorting of waste is difficult due to cross contamination although on‐site sorting has been stated as a requirement in the contract. The demolition method statement should include working details of both the salvaging and the demolition stages to affect waste sorting and recycling. Selective demolition should be considered to further improve the waste recycling rate but there is a need to develop recycling markets to provide outlets for the collected recyclables.
Organizing a Venture Factory: Company Builder Incubators and the Case of Rocket Internet

We study the phenomenon of “company builders” – a recent type of business incubators that create new ventures in a factory-like manner, i.e., with a focus on efficiency and scale, and by using standardized processes and shared resources. To characterize this novel organizational form and delineate it from existing incubator models, we conceptualize incubator organizations as hybrid governance structures along key dimensions of the market-hierarchy spectrum. We contextualize and extend our conceptual arguments through an in-depth study of Rocket Internet, the incubator that pioneered an extreme company builder strategy by replicating successful Internet business models. We argue that while traditional incubators lean toward the market end of the market-hierarchy spectrum, company builders are truly hybrid organizational forms in that new ventures are assembled and scaled up in a centrally-coordinated manner. Referring to cooperation and coordination as basic organizational challenges, we discuss the stability, advantages, and pitfalls of the company builder model, as well as its applicability to other domains. Our findings make contributions to work on organizing venturing processes, novel organizational forms, and business model replication.
Relation Also Need Attention: Integrating Relation Information Into Image Captioning

Image captioning methods with attention mechanism are leading this ﬁeld, especially models with global and local attention. But there are few conventional models to integrate the relationship information between various regions of the image. In this paper, this kind of relationship features are embedded into the fused attention mechanism to explore the internal visual and semantic relations between diﬀerent object regions. Besides, to alleviate the exposure bias problem and make the training process more eﬃcient, we combine Generative Adversarial Network with Reinforcement Learning and employ the greedy decoding method to generate a dynamic baseline reward for self-critical training. Finally, experiments on MSCOCO datasets show that the model can generate more accurate and vivid image captioning sentences and perform better in multiple prevailing metrics than the previous advanced models.
Soundscape Preference of Urban Residents in China in the Post-pandemic Era

This research aims to explore the reality of the soundscape preferences of Chinese urban residents in general public landscape in the post-pandemic era, and then to propose design recommendations to meet the practical needs of people’s preferences for landscape—especially soundscapes—in the post-pandemic era. In this study, we utilized the subjective evaluation method to conduct an online questionnaire in 29 Chinese provinces which experienced severe pandemic caseloads and collected 860 valid responses. This study revealed people’s preference for landscape and soundscape in the post-pandemic era. We further studied the correlation between landscape preference and soundscape preference, analyzed the influence of living conditions on soundscape preference, founded the effects of personal characteristics and living conditions on soundscape preference, and explored the strongest influence factors on soundscape preference through the establishment of automatic linear model. The results revealed a positive correlation between life happiness and soundscape preference, whereas wearing masks significantly reduced soundscape perception ratings and people who have been vaccinated are more tolerant of various noises. Moreover, based on these analysis results, the design recommendations on landscape (overall landscape, plant, and tour space), soundscape construction of caring for vulnerable groups (teenagers and children, elderly people, and disabled and unhealthy) has been discussed.
Uplift Modeling with High Class Imbalance

Uplift modeling refers to estimating the causal eﬀect of a treatment on an individual observation, used for instance to identify customers worth targeting with a discount in e-commerce. We introduce a simple yet eﬀective undersampling strategy for dealing with the prevalent problem of high class imbalance (low conversion rate) in such applications. Our strategy is agnostic to the base learners and produces a 6.5% improvement over the best published benchmark for the largest public uplift data which incidentally exhibits high class imbalance. We also introduce a new metric on calibration for uplift modeling and present a strategy to improve the calibration of the proposed method.
Application of optimized PLS-SEM measurement model and empirical research on Chinese cultural and creative industries competitive formation mechanism

Based on reviewing the PLS-SEM measure model, and summarizing the theory and reference of other scholars, the PLS-SEM measure model is optimized, in order to contain many latent variables and relatively scientific operations. At the same time, we make comments on the framework of industrial competitiveness referring to diamond model theory. Summarize the factors affecting the competitiveness of cultural and creative industry and measurement standard, and construct the framework of mechanism model for the formation of the cultural and creative industries’ competitiveness. Using PLS-SEM measurement optimization model’s 62 sets of data on Chinese provinces’ cultural and creative industry in 2011 and 2012 to do the empirical analysis. The final optimization model is verified rationally. The study finds that the ability of sustainable development, capacity requirement, the government support and the overall innovation capability influence on cultural and creative industries’ competitive strength are the most important keys.
Designing Location-Specific 3D-Printed Vessels Using Mobile-Based Multisensor Data Fusion

Abstract This statement presents an innovative creative process for designing ceramic vessels. The authors detail how three disparate concepts—mobile device-driven creativity, digitally designed and fabricated ceramics, and multisensor data fusion—are unified and applied to an emerging practice in which sensor data are used to generate vessel designs via a prototype smartphone app. In a pilot study users in a variety of locations tested the app, and their designs were 3D printed, with location becoming a tangible parameter. Results show the feasibility of using data fusion, mobile devices and digital fabrication to create physical, location-specific artifacts. Broad implications and potential ways forward are then discussed.
Learning Optimal Decisions for Stochastic Hybrid Systems

We apply reinforcement learning to approximate the optimal probability that a stochastic hybrid system satisfies a temporal logic formula. We consider systems with (non)linear continuous dynamics, random events following general continuous probability distributions, and discrete nondeterministic choices. We present a discretized view of states to the learner, but simulate the continuous system. Once we have learned a near-optimal scheduler resolving the choices, we use statistical model checking to estimate its probability of satisfying the formula. We implemented the approach using Q-learning in the tools HYPEG and modes, which support Petri net- and hybrid automata-based models, respectively. Via two case studies, we show the feasibility of the approach, and compare its performance and effectiveness to existing analytical techniques for a linear model. We find that our new approach quickly finds near-optimal prophetic as well as non-prophetic schedulers, which maximize or minimize the probability that a specific signal temporal logic property is satisfied.
Translation of Continuous Function Charts to Imperative Synchronous Quartz Programs

Programmable logic controllers operating in a sequential execution scheme are widely used for various applications in industrial environments with real-time requirements. The graphical programming languages described in the third part of IEC 61131 are often intended to perform open and closed loop control tasks. Continuous Function Charts (CFCs) represent an additional language accepted in practice which can be interpreted as an extension of IEC 61131-3 Function Block Diagrams. Those charts allow more flexible positioning and interconnection of function blocks, but can quickly become difficult to manage. Furthermore, the sequential execution order forces a sequential processing of possible independent and thus possibly parallel program paths. The question arises whether a translation of existing CFCs to synchronous programs considering independent actions can lead to a more manageable software model. While current formalization approaches for CFCs primarily focus on verification, the focus of this approach is on restructuring and possible reuse in engineering. This paper introduces a possible automated translation of CFCs to imperative synchronous Quartz programs and outlines the potential for reducing the states of equivalent extended finite state machines through restructuring.
Cadaveric Stem Cells: Their Research Potential and Limitations

In the era of growing interest in stem cells, the availability of donors for transplantation has become a problem. The isolation of embryonic and fetal cells raises ethical controversies, and the number of adult donors is deficient. Stem cells isolated from deceased donors, known as cadaveric stem cells (CaSCs), may alleviate this problem. So far, it was possible to isolate from deceased donors mesenchymal stem cells (MSCs), adipose delivered stem cells (ADSCs), neural stem cells (NSCs), retinal progenitor cells (RPCs), induced pluripotent stem cells (iPSCs), and hematopoietic stem cells (HSCs). Recent studies have shown that it is possible to collect and use CaSCs from cadavers, even these with an extended postmortem interval (PMI) provided proper storage conditions (like cadaver heparinization or liquid nitrogen storage) are maintained. The presented review summarizes the latest research on CaSCs and their current therapeutic applications. It describes the developments in thanatotranscriptome and scaffolding for cadaver cells, summarizes their potential applications in regenerative medicine, and lists their limitations, such as donor’s unknown medical condition in criminal cases, limited differentiation potential, higher risk of carcinogenesis, or changing DNA quality. Finally, the review underlines the need to develop procedures determining the safe CaSCs harvesting and use.
A Study of the Lipidomic Profiles of the CAL-27 and HOK Cell Lines Using EMS Spectra

Objective The aim of this study was to explore the lipidomic profiles of the CAL-27 human tongue cancer cell line and the human oral keratinocyte (HOK) cell line. Methods The lipidomic differences between the CAL-27 and the HOK cell lines were investigated using non-targeted high-performance liquid chromatography–mass spectrometry lipidomic analysis. The resulting data were then further mined via bioinformatics analysis technology and metabolic pathway analysis was conducted in order to map the most affected metabolites and pathways in the two cell lines. Results A total of 711 lipids were identified, including 403 glycerophospholipids (GPs), 147 glycerolipids, and 161 sphingolipids. Comparison of the enhanced MS (EMS) spectra of the two cell lines in positive and negative ionization modes showed the lipid compositions of HOK and CAL-27 cells to be similar. The expressions of most GP species in CAL-27 cells showed an increasing trend as compared with HOK, whereas a significant increase in phosphatidylcholine was observed (p < 0.05). Significant differences in the lipid composition between CAL-27 and HOK cells were shown as a heatmap. Through principal component analysis and orthogonal partial least squares discriminant analysis, noticeably clear separation trends and satisfactory clustering trends between groups of HOK and CAL-27 cells were identified. The numbers of specific lipid metabolites that could distinguish CAL-27 from HOK in positive and negative modes were 100 and 248, respectively. GP metabolism was the most significantly altered lipid metabolic pathway, with 4 metabolites differentially expressed in 39 hit products. Conclusion This study demonstrated the potential of using untargeted mass spectra and bioinformatics analysis to describe the lipid profiles of HOK and CAL-27 cells.