Miracle-dz/UniFAR-FTUs huggingface dataset:
Capacity and Delay of Unmanned Aerial Vehicle Networks With Mobility

Unmanned aerial vehicles (UAVs) are widely exploited in environment monitoring, search-and-rescue, etc. However, the mobility and short flight duration of UAVs bring challenges for UAV networking. In this paper, we study the UAV networks with ${n}$ UAVs acting as aerial sensors. UAVs generally have short flight duration and need to frequently get energy replenishment from the control station. Hence, the returning UAVs bring the data of the UAVs along the returning paths to the control station with a store-carry-and-forward (SCF) mode. A critical range for the distance between the UAV and the control station is discovered. Within the critical range, the per-node capacity of the SCF mode is ${\Theta ({n}/{\log n})}$ times higher than that of the multihop mode. However, the per-node capacity of the SCF mode outside the critical range decreases with the distance between the UAV and the control station. To eliminate the critical range, a mobility control scheme is proposed such that the capacity scaling laws of the SCF mode are the same for all UAVs, which improves the capacity performance of UAV networks. Moreover, the delay of the SCF mode is derived. The impact of the size of the entire region, the velocity of UAVs, the number of UAVs and the flight duration of UAVs on the delay of SCF mode is analyzed. This paper reveals that the mobility and short flight duration of UAVs have beneficial effects on the performance of UAV networks, which may motivate the study of SCF schemes for UAV networks.
Genetic requirements for infection-specific responses in conferring disease resistance in Arabidopsis

Immunity in plants arises from defense regulatory circuits that can be conceptualized as modules. Both the types (and isolates) of pathogen and the repertoire of plant receptors may cause different modules to be activated and affect the magnitude of activation. Two major defense enzymes of Arabidopsis are ALD1 and ICS1/SID2. ALD1 is an aminotransferase needed for producing the metabolites pipecolic acid, hydroxy-pipecolic acid, and possibly other defense signals. ICS1/SID2 produces isochorismate, an intermediate in the synthesis of salicylic acid (SA) and SA-derivatives. Metabolites resulting from the activation of these enzymes are found in petiole exudates and may serve as priming signals for systemic disease resistance in Arabidopsis. Mutants lacking ALD1 are known to have reduced SA accumulation. To further investigate the role of ALD1 in relation to the SA-related module, immunity phenotypes of double mutants that disrupt ALD1 and ICS1/SID2 or SA perception by NPR1 were compared with each single mutant after infection by different Pseudomonas strains. Exudates collected from these mutants after infection were also evaluated for their ability to confer disease resistance when applied to wild-type plants. During infection with virulent or attenuated strains, the loss of ALD1 does not increase the susceptibility of npr1 or sid2 mutants, suggesting the main role of ALD1 in this context is in amplifying the SA-related module. In contrast, after an infection that leads to strong pathogen recognition via the cytoplasmic immune receptor RPS2, ALD1 acts additively with both NPR1 and ICS1/SID2 to suppress pathogen growth. The additive effects are observed in early basal defense responses as well as SA-related events. Thus, there are specific conditions that dictate whether the modules independently contribute to immunity to provide additive protection during infection. In the exudate experiments, intact NPR1 and ICS1/SID2, but not ALD1 in the donor plants were needed for conferring immunity. Mixing exudates showed that loss of SID2 yields exudates that suppress active exudates from wild-type or ald1 plants. This indicates that ICS1/SID2 may not only lead to positive defense signals, but also prevent a suppressive signal(s).
Behavioural Effects and Market Dynamics in Field and Laboratory Experimental Asset Markets

A vast literature investigating behavioural underpinnings of financial bubbles and crashes relies on laboratory experiments. However, it is not yet clear how findings generated in a highly artificial environment relate to the human behaviour in the wild. It is of concern that the laboratory setting may create a confound variable that impacts the experimental results. To explore the similarities and differences between human behaviour in the laboratory environment and in a realistic natural setting, with the same type of participants, we translate a field study conducted by reference (Sornette, D.; et al. Econ. E-J. 2020, 14, 1–53) with trading rounds each lasting six full days to a laboratory experiment lasting two hours. The laboratory experiment replicates the key findings from the field study but we observe substantial differences in the market dynamics between the two settings. The replication of the results in the two distinct settings indicates that relaxing some of the laboratory control does not corrupt the main findings, while at the same time it offers several advantages such as the possibility to increase the number of participants interacting with each other at the same time and the number of traded securities. These findings pose important insights for future experiments investigating human behaviour in complex systems.
Understanding Dynamics of Mangrove Forest on Protected Areas of Hainan Island, China: 30 Years of Evidence from Remote Sensing

Implementation of the UN Sustainable Development Goals requires countries to determine targets for the protection, conservation, or restoration of coastal ecosystems such as mangrove forests by 2030. Satellite remote sensing provides historical and current data on the distribution and dynamics of mangrove forests, essential baseline data that are needed to design suitable policy interventions. In this study, Landsat time series were used to map trends and dynamics of mangrove change over a time span of 30 years (1987–2017) in protected areas of Hainan Island (China). A support vector machine algorithm was combined with visual interpretation of imagery and result showed alternating periods of expansion and loss of mangrove forest at seven selected sites on Hainan Island. Over this period, there was a net decrease in mangrove area of 9.3%, with anthropic activities such as land conversion for aquaculture, wastewater disposal and discharge, and tourism development appearing to be the likely drivers of this decline in cover. Long-term studies examining trends in land use cover change coupled with assessments of drivers of loss or gain enable the development of evidence based on policy and legislation. This forms the basis of financing of natural reserves of management and institutional capacity building, and facilitates public awareness and participation, including co-management.
Digital Diplomacy via Social Networks: A Cross-National Analysis of Governmental Usage of Facebook and Twitter for Digital Engagement

Over the last couple of years, digital diplomacy has become a fascinating area of research among Mass Communication, Peace and Conflict Studies, and International Affairs scholars. Social media and new technology open up new avenues for governments, individuals, and organizations to engage with foreign audiences. However, developing countries’ governments are still lacking in the realization of the potential of social media. This study aims to analyze the usage of social media (Facebook & Twitter) by the two biggest countries in South Asia (Pakistan and India). I selected 10 government officials’ social media accounts including prime ministers', national press offices’, military public relations offices’, public diplomacy divisions’, and ministries of foreign offices’ profiles. The study relies on quantitative content analysis and a comparative research approach. The total number of analyzed Twitter tweets (n=1,015) and Facebook posts (n=1,005) include 10 accounts, five from each country. In light of Kent and Taylor’s (1998) dialogic communication framework, the results indicate that no digital engagement and dialogue occurs between government departments and the public through social networking sites. Government departments do not engage with local or foreign audiences through digital media. When comparing both countries, results reveal that India has more institutionalized and organized digital diplomacy. In terms of departmental use of social media, the digital diplomacy division and foreign office of India is more active than other government departments in that nation. Meanwhile, Pakistan’s military public relations office and press office is more active than its other government departments. In conclusion, both countries realize the potential of social media in digital diplomacy, but still lack engagement with foreign audiences.
Combined proteomics and single cell RNA-sequencing analysis to identify biomarkers of disease diagnosis and disease exacerbation for systemic lupus erythematosus

Introduction Systemic lupus erythematosus (SLE) is a chronic autoimmune disease for which there is no cure. Effective diagnosis and precise assessment of disease exacerbation remains a major challenge. Methods We performed peripheral blood mononuclear cell (PBMC) proteomics of a discovery cohort, including patients with active SLE and inactive SLE, patients with rheumatoid arthritis (RA), and healthy controls (HC). Then, we performed a machine learning pipeline to identify biomarker combinations. The biomarker combinations were further validated using enzyme-linked immunosorbent assays (ELISAs) in another cohort. Single-cell RNA sequencing (scRNA-seq) data from active SLE, inactive SLE, and HC PBMC samples further elucidated the potential immune cellular sources of each of these PBMC biomarkers. Results Screening of the PBMC proteome identified 1023, 168, and 124 proteins that were significantly different between SLE vs. HC, SLE vs. RA, and active SLE vs. inactive SLE, respectively. The machine learning pipeline identified two biomarker combinations that accurately distinguished patients with SLE from controls and discriminated between active and inactive SLE. The validated results of ELISAs for two biomarker combinations were in line with the discovery cohort results. Among them, the six-protein combination (IFIT3, MX1, TOMM40, STAT1, STAT2, and OAS3) exhibited good performance for SLE disease diagnosis, with AUC of 0.723 and 0.815 for distinguishing SLE from HC and RA, respectively. Nine-protein combination (PHACTR2, GOT2, L-selectin, CMC4, MAP2K1, CMPK2, ECPAS, SRA1, and STAT2) showed a robust performance in assessing disease exacerbation (AUC=0.990). Further, the potential immune cellular sources of nine PBMC biomarkers, which had the consistent changes with the proteomics data, were elucidated by PBMC scRNAseq. Discussion Unbiased proteomic quantification and experimental validation of PBMC samples from two cohorts of patients with SLE were identified as biomarker combinations for diagnosis and activity monitoring. Furthermore, the immune cell subtype origin of the biomarkers in the transcript expression level was determined using PBMC scRNAseq. These findings present valuable PBMC biomarkers associated with SLE and may reveal potential therapeutic targets.
Methods of determination of territorial resources in conditions of compacted urban development (using Kyiv as an example)

The article highlights the results of the analysis of domestic and foreign experience of application of the applied coatings and a modified typology of roofs based on their geometric and structural features is proposed. The following factors that influence taking the decision on the need and directions of the use of the used roofs are provided. On the basis of the analysis of the dynamics of the normative and actual indicators of urban development, the constant growth of the development density and growth of the lack of territory for greenery and other elements of the population service are proved. The described methods for the determination of the resource potential of urban areas are normative method, comparative and calculation method. A new calculation method for identifying potential territorial resources of micro districts, blocks or individual plots due to the use of exploited roofs in conditions of compacted urban development has been proposed. The mathematical model is based on taking into account the geometric type of the roof, type of historically originated development, its technical condition and the availability of the status of the cultural heritage monument. Coefficients for the calculation of the potential territorial resource have been experimentally determined. Based on the example of Kyiv, using GIS-technologies, a specialized database for identifying a potential territorial resource has been formed. The recommendations for placement on different types of objects on the exploited roofs depending on the frequency of their visit and the cityplanning situation have been provided. The methodical scheme for the determination of a potential territorial resource due to the use of exploited roofs in the development of urban planning, design and land management documentation has been proposed.
Public perceptions of how to reduce carbon footprints of consumer food choices

Carbon footprints—the greenhouse gas (GHG) emissions associated with consumer food choices—substantially contribute to climate change. Life cycle analyses from climate and environmental sciences have identified effective rules for reducing these food-related GHG emissions, including eating seasonal produce and replacing dairy and red meat with plant-based products. In a national UK survey, we studied how many and which rules our participants generated for reducing GHG emissions of produce, dairy, and protein-rich products. We also asked participants to estimate GHG emission reductions associated with pre-selected rules, expressed in either grams or percentages. We found that participants generated few and relatively less effective rules, including ambiguous ones like ‘Buy local’. Furthermore, participants’ numerical estimates of pre-selected rules were less accurate when they assessed GHG emission reductions in grams rather than in percentages. Findings suggest a need for communicating fewer rules in percentages, for informing consumers about reducing food-related GHG emissions.
A 30-frames/s,  $252\times144$  SPAD Flash LiDAR With 1728 Dual-Clock 48.8-ps TDCs, and Pixel-Wise Integrated Histogramming

A <inline-formula> <tex-math notation="LaTeX">$252 \times 144$ </tex-math></inline-formula> single-photon avalanche diode (SPAD) pixel sensor, called Ocelot, is reported for light detection and ranging (LiDAR). The sensor, fabricated in the 180-nm CMOS technology, features 1728 12-bit time-to-digital converters (TDCs) with 48.8-ps resolution (LSB). Each 126 pixels in a half-column are connected to six TDCs through a collision detection bus, which enables effective sharing of resources, and consequently a fill factor of 28% with a pixel pitch of 28.5 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>. The column-parallel TDCs, based on dual-clock architecture, exhibit a DNL of +0.48/−0.48 LSB and an INL of +0.89/−1.67 LSB; they are dynamically reallocated in a scalable daisy chain approach that enables a maximum of five photon detections per illumination cycle per half-column. The sensor can operate in time-correlated single-photon counting (TCSPC) and single-photon counting (SPC) modes, while peak detection (PD) and partial histogramming (PH) are included in the operation of the sensor. The PD and PH modes are enabled by the first implementation of integrated histogramming for a full array via 3.32-Mb SRAM-based PH readout (PHR) scheme providing a 14.9-to-1 compression. Telemetry measurements up to 50 m achieve an accuracy of 8.8 cm and worst-case precision of 1.4 mm (<inline-formula> <tex-math notation="LaTeX">$\sigma $ </tex-math></inline-formula>). A flash LiDAR using direct time of flight (dTOF) and based on Ocelot is demonstrated, achieving depth imaging at short distances with a frame rate of 30 frames/s, employing an ultra-low power laser with an average power of 2 mW and peak power of 0.5 W.
Driving simulator test of variable message sign and audio warning information at highway-rail grade crossings

Highway-rail grade crossing concerns the safety of railway and roadway transportation, and the high rate of accidents involved in highway-rail grade crossing has drawn much attention from society. This paper chose Variable Message Signs (VMS) and audio message as key factors, aiming to evaluate driver stop-go behaviors at highway-rail grade crossing under four warning levels. The data from the driving-simulator-based experiment were analyzed using descriptive statistical analysis. Results indicated that VMS and audio information can enhance drivers’ alertness so that they decelerate gently ahead of time to improve the stop rate. As VMS cannot present the warning of danger individually and optimally, the collaboration of audio warning and visual information on the road can increase the stopping ratio up to 100%, resulting in a satisfying precaution effect.
Assessing the efficacy of immunotherapy in lung squamous carcinoma using artificial intelligence neural network

Background At present, immunotherapy is a very promising treatment method for lung cancer patients, while the factors affecting response are still controversial. It is crucial to predict the efficacy of lung squamous carcinoma patients who received immunotherapy. Methods In our retrospective study, we enrolled lung squamous carcinoma patients who received immunotherapy at Beijing Chest Hospital from January 2017 to November 2021. All patients were grouped into two cohorts randomly, the training cohort (80% of the total) and the test cohort (20% of the total). The training cohort was used to build neural network models to assess the efficacy and outcome of immunotherapy in lung squamous carcinoma based on clinical information. The main outcome was the disease control rate (DCR), and then the secondary outcomes were objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Results A total of 289 patients were included in this study. The DCR model had area under the receiver operating characteristic curve (AUC) value of 0.9526 (95%CI, 0.9088–0.9879) in internal validation and 0.9491 (95%CI, 0.8704–1.0000) in external validation. The ORR model had AUC of 0.8030 (95%CI, 0.7437–0.8545) in internal validation and 0.7040 (95%CI, 0.5457–0.8379) in external validation. The PFS model had AUC of 0.8531 (95%CI, 0.8024–0.8975) in internal validation and 0.7602 (95%CI, 0.6236–0.8733) in external validation. The OS model had AUC of 0.8006 (95%CI, 0.7995–0.8017) in internal validation and 0.7382 (95%CI, 0.7366–0.7398) in external validation. Conclusions The neural network models show benefits in the efficacy evaluation of immunotherapy to lung squamous carcinoma patients, especially the DCR and ORR models. In our retrospective study, we found that neoadjuvant and adjuvant immunotherapy may bring greater efficacy benefits to patients.
Student satisfaction, learning outcomes, and cognitive loads with a mobile learning platform

Abstract After working with a number of scholars for two years, a university designed a mobile learning platform referred to as ‘College English IV,’ where learners could have easy access to various kinds of learning resources through installing the program in their smart phones. This study aims to identify whether this platform could significantly improve the proficiency of English as a foreign language (EFL), yield learner satisfaction, and reduce learners’ cognitive loads in EFL classes. Randomly selected 340 tertiary students participated in the study. After quantitative multivariate analysis and qualitative interview data analysis, it was concluded that: (1) In EFL classes, participants with the mobile learning platform were more satisfied than those without it; (2) In EFL classes, learning outcomes of participants with the mobile learning platform improved significantly more than those without it; and (3) In EFL classes, cognitive loads of participants with the mobile learning platform were significantly lower than those without it. Interdisciplinary research may be needed in future research.
Dispersion Over the Business Cycle: Productivity versus Demand

In this paper we use rich Swedish micro-data to show that increased dispersion during recessions is primarily a demand-side phenomenon. The key novelty of our analysis is that we use goods-level data on prices to estimate firm-level demand shocks, and production-line-level data on reported capacity utilization to accurately measure firm-level supply (TFPQ) shocks. We document that the dispersion of both TFPQ and demand growth across firms rose during the Great Recession, but that the increased dispersion in TFPQ growth is reduced by up to 1/4 after controlling for capacity utilization. We then perform a semi-structural variance decomposition exercise for firm-level sales growth. We show that 2/3 of the increased dispersion in sales growth in 2009 is explained by the increased dispersion of demand, while TFPQ dispersion plays essentially no role. Key to this finding is that we estimate a low level of passthrough from TFPQ shocks to prices, limiting the ability of increased TFPQ shock dispersion to affect sales dispersion. Consistent with this, we find evidence that demand curves are kinked.
Efficient renaming in CRDTs

Sequence Conflict-free Replicated Data Types (CRDTs) allow to repli-cate and edit, without any kind of coordination, sequences in distributed systems. To ensure convergence, existing works from the literature add metadata to each element but they do not bound its footprint, which impedes their adoption. Several approaches were proposed to address this issue but they do not fit a fully distributed setting. In this paper, we present our ongoing work on the design and validation of a fully distributed renaming mechanism, setting a bound to the metadata's footprint. Addressing this issue opens new perspectives of adoption of these CRDTs in distributed applications.
New B.ED. Programme in India: A Convergent Parallel Study on ICT-Integration

O presente trabalho visa a explorar e compartilhar a integração das TICs e a sua condição no novo programa de dois anos de bacharelado em educação (B.Ed.), o qual foi implementado em 2015, na Índia, por meio de um órgão regulatório chamado Conselho Nacional para a Formação de Professores (NCTE). O projeto de pesquisa convergente de método misto paralelo foi utilizado nesse estudo, no qual os pesquisadores coletaram dados qualitativos e quantitativos simultaneamente e compararam ou convergem ambos os tipos de dados para obter um entendimento aprofundado relacionado ao problema de pesquisa. Amostragem aleatória estratificada, amostragem intencional, amostragem aleatória sistemática e técnicas de amostragem convencional foram usadas de acordo com a necessidade de vários grupos de amostras. O resultado principal do estudo foi descrever os processos e as práticas atuais bem como as recomendações futuras para a integração de TICs no novo programa de bacharelado implementado em 2015 na Índia. Os esclarecimentos resultados desse estudo podem ser implementados em outros países ao redor do mundo.