Miracle-dz/UniFAR-FTUs huggingface dataset:
Beyond Seen Primitive Concepts for Attributes-Objects Compositional Learning Anonymous

Learning from seen attribute-object pairs to generalize to un-seen compositions has been studied extensively in Compositional Zero-Shot Learning (CZSL). However, CZSL setup is still limited to seen attributes and objects, and cannot generalize to unseen concepts and their compositions. To overcome this limitation, we propose a new task, Open Vocabulary-Compositional Zero-shot Learning (OV-CZSL), where un-seen attributes, objects, and unseen compositions are evaluated. To show that OV-CZSL is a challenging yet solvable problem, we propose three new benchmarks based on existing datasets MIT-States (Isola, Lim, and Adelson 2015), C-GQA (Mancini et al. 2022) and VAW-CZSL (Saini, Pham, and Shrivastava 2022; Pham et al. 2021), along with new baselines and evaluation setup. We use language embeddings and external vocabulary with our novel neighborhood expansion loss to allow any method to learn semantic correlations between seen and unseen primitives.
Learning Team Coordination to Traverse Adversarial Environments

—This paper seeks to solve the coordination of a team of agents traversing a path in the presence of adversaries. Our goal is to minimize the overall cost of the team, which is determined by (i) accumulated risk when agents stay in adversary-impacted zones and (ii) mission completion time. During traversal, agents can reduce their speed and act as a ‘guard’ (the slower, the better), which can decrease the risks certain adversary incurs. This leads to a trade-off between agents’ guarding behaviors and their travel speeds. The formulated problem is highly non-convex and cannot be efficiently solved by existing algorithms. We provide theoretical analysis regarding the team’s coordination strategies when the number of agents and adversaries is small. As the scale of the problem expands, solving the optimal solution is challenging, therefore, we employ reinforcement learning techniques by developing new encoding and policy-generating methods. Simulations demonstrate that our learning methods can efficiently produce team coordination behaviors. We discuss the reasoning behind these behaviors and explain why they reduce the overall team cost.
Motion Memory: Leveraging Past Experiences to Accelerate Future Motion Planning

When facing a new motion-planning problem, most motion planners solve it from scratch, e.g., via sampling and exploration or starting optimization from a straight-line path. However, most motion planners have to experience a variety of planning problems throughout their lifetimes, which are yet to be leveraged for future planning. In this paper, we present a simple but efficient method called Motion Memory, which allows different motion planners to accelerate future planning using past experiences. Treating existing motion planners as either a closed or open box, we present a variety of ways that Motion Memory can contribute to reduce the planning time when facing a new planning problem. We provide extensive experiment results with three different motion planners on three classes of planning problems with over 30,000 problem instances and show that planning speed can be significantly reduced by up to 89% with the proposed Motion Memory technique and with increasing past planning experiences.
Building Method of a BERT-Based Model for Key Information Extraction from Chemical Engineering Literature

Forresearchers,itisessentialtoaccessvariousliteratureinordertostay up-to-date with the latest advancements and trends in scientiﬁc research. Chemical engineering literature, characterized by its diverse range, lengthy articles, complex experimental conditions, and numerous references to chemical compounds, poses a challenge in terms of manually extracting research content from a massive volume of literature. Relying solely on human effort to extract information from chemicalengineeringliteraturewouldbeextremelytime-consumingandresource-intensive.Toenhancethespeedatwhichchemicalengineeringresearchersacquire knowledgeandreducethetimespentonreadingliterature,thispaperproposesa textsummarizationmodelbasedonBERT(BidirectionalEncoderRepresentations fromTransformers). Themodelaimstogenerateconcisesummariescorrespond-ingtothekeyinformationfoundinchemicalengineeringliterature.Basedon thetextualcontentgeneratedbythemodel,ithasachievedsatisfactoryresultsin extractingkeyinformationfromchemicalengineeringliterature.
Wearing face mask detection using deep learning during COVID-19 pandemic

During the COVID-19 pandemic, wearing a face mask has been an e(cid:11)ective way to prevent the spread of COVID-19. In a number of monitoring jobs, human workforce has been replaced with computers thanks to the outstanding performance of deep learning models. Monitoring the wearing of a face mask is another task that can be done by deep learning models with acceptable accuracy. The main challenge of this task, however, is the limited amount of data because of the quarantine constraints. This study investigated the capability of three state-of-the-art object detection neural networks to detect face mask for real-world applications. To this end, three models were employed: Single Shot Detector (SSD) and two versions of You Only Look Once (YOLO) including YOLOv4-tiny and YOLOv4-tiny-3l, among which the best was selected. In the proposed method, according to the performance of these models, the most viable model for real-world and mobile device applications, compared to other recent studies, was the YOLOv4-tiny model with the mean Average Precision (mAP) and Frames Per Second (FPS) of 85.31% and 50.66, respectively. These acceptable values were obtained using two datasets with only 1531 images in three separate classes.
Northern and southern hemisphere ground-based infrared spectroscopic measurements of tropospheric

Time series of CO and C{sub 2}H{sub 6} measurements have been derived from high-resolution infrared solar spectra recorded in Lauder, New Zealand (45.0h{degree}S, 169.7h{degree}E, altitude 0.37 km), and at the U.S. National Solar Observatory (31.9h{degree}N, 111.6h{degree}W, altitude 2.09 km) on Kitt Peak. Lauder observations were obtained between July 1993 and November 1997, while the Kitt Peak measurements were recorded between May 1977 and December 1997. Both databases were analyzed with spectroscopic parameters that included significant improvements for C{sub 2}H{sub 6} relative to previous studies. Target CO and C{sub 2}H{sub 6} lines were selected to achieve similar vertical samplings based on averaging kernels. These calculations show that partial columns from layers extending from the surface to the mean tropopause and from the mean tropopause to 100 km are nearly independent. Retrievals based on a semiempirical application of the Rodgers optimal estimation technique are reported for the lower layer, which has a broad maximum in sensitivity in the upper troposphere. The Lauder CO and C{sub 2}H{sub 6} partial columns exhibit highly asymmetrical seasonal cycles with minima in austral autumn and sharp peaks in austral spring. The spring maxima are the result of tropical biomass burning emissions followed by deep convective vertical transportmore » to the upper troposphere and long-range horizontal transport. Significant year-to-year variations are observed for both CO and C{sub 2}H{sub 6}, but the measured trends, (+0.37{plus_minus}0.57){percent}hyr{sup {minus}1} and ({minus}0.64{plus_minus}0.79){percent}hyr{sup {minus}1}, 1 sigma, respectively, indicate no significant long-term changes. The Kitt Peak data also exhibit CO and C{sub 2}H{sub 6} seasonal variations in the lower layer with trends equal to ({minus}0.27{plus_minus}0.17){percent}hyr{sup {minus}1} and ({minus}1.20{plus_minus}0.35){percent}hyr{sup {minus}1}, 1 sigma, respectively. Hence a decrease in the Kitt Peak tropospheric C{sub 2}H{sub 6} column has been detected, though the CO trend is not significant. Both measurement sets are compared with previous observations, reported trends, and three-dimensional model calculations. {copyright} 1998 American Geophysical Union« less
Flow in Open-Channel Embayments

This study investigates flows in a square and a rectangular embayment located on the side bank of an open channel. It is found that the main flow of the open channel induces a circulatory flow in the square and rectangular embayment and the center of the circulatory flow is shifted downstream in comparison with the center of the embayment. A solution of the shallow water equations solved using the method of variation yields results of the 95% confidence intervals within 10% of mean errors between the observed and computed nondimensional velocities.
Assessment of Human Exposure to Electromagnetic Fields: Review and Future Directions

This article reviews recent standardization activities and scientific studies related to the assessment of human exposure to electromagnetic fields (EMF). The differences of human exposure standards and assessment of consumer products and medical applications are summarized. First, we reviewed human body modeling and tissue dielectric properties. Then, we explain the rationale of current exposure standards from the viewpoint of EMF and the standardization process for product compliance based on these exposure standards. The assessment of wireless power transfer, as an example of emerging wireless devices, and environmental EMFs in our daily lives are reviewed. Safety in magnetic resonance systems, where the EMF exposure is much larger than from typical consumer devices, is also reviewed. Finally, we summarize future research directions and research needs for EMF safety.
A probability method for local earthquake focal mechanisms

We propose a method for obtaining focal mechanisms of earthquakes recorded on a local network. It is based on the non-linear estimation of the probability function for strike, dip and slip of the focal mechanism from P polarities, S polarizations and S/P amplitude ratios. The method is shown to be effective for the analysis of small earthquakes recorded by local networks. In particular, the S/P amplitude ratios bring strong constraints on fault parameters, even if large errors are present. An application to a small earthquake recorded at the volcanic zone of Campi Flegrei (Naples, Italy) during a seismic outburst is presented.
Classification of Mediterranean vegetation by TM and ancillary data for the evaluation of fire risk

Mediterranean vegetation is strongly subjected to the risk of wildfires, which can become a major cause of land degradation. The knowledge of the spatial variations of this risk is essential, therefore, for forest resource management. Relying on the fact that different vegetation types can be associated with different risk levels, a classification approach based on the use of Landsat Thematic Mapper (TM) scenes is currently proposed for the generation of maps related to fire risk. Hard and fuzzy classifications were tested for this purpose on Elba island (central Italy), taking into account the effects of the use of scenes from different periods (spring and summer) and of ancillary data. The fire risk images obtained were evaluated by comparison with the fire events that occurred on the island during the last decade. The results show that, while the acquisition period has only minor effects, classification accuracy is strongly dependent on the inclusion of ancillary data. Moreover, the fuzzy approach better exploits the information of the integrated datasets, producing maps which are temporally stable and highly indicative of the fire risk in the study area.
Rainfall–runoff response and event-based runoff coefficients in a humid area (northwest Spain)

Abstract The hydrological response of a small agroforestry catchment in northwest Spain (Corbeira catchment, 16 km2) is analysed, with particular focus on rainfall events. Fifty-four rainfall–runoff events, from December 2004 to September 2007, were used to analyse the principal hydrological patterns and show which factors best explain the hydrological response. The nonlinearity between rainfall and runoff showed that the variability in the hydrological response of the catchment was linked to the seasonal dynamics of the rainfall and, to a lesser extent, to evapotranspiration. The runoff coefficient, estimated as the ratio between direct runoff and rainfall volume, on an event basis, was analysed as a function of rainfall characteristics (amount and intensity) and the initial catchment state conditions prior to an event, such as pre-event baseflow and antecedent rainfall index. The results revealed that the hydrological response depends both on the soil humidity conditions at the start of the event and on rainfall amount, whereas rainfall intensity presented only a significant correlation with discharge increment. The antecedent conditions seem to be a key point in runoff production, and they explain much of the response. The hydrographs are characterized by a steep rising limb, a relatively narrow peak discharge and slow recession limb. These data and the observations suggest that the subsurface flow is the dominant runoff process. Editor Z.W. Kundzewicz; Associate editor T. Wagener Citation Rodríguez-Blanco, M.L. , Taboada-Castro, M.M. and Taboada-Castro, M.T. , 2012. Rainfall–runoff response and event-based runoff coefficients in a humid area (northwest Spain). Hydrological Sciences Journal, 57 (3), 445–459.
PERTUMBUHAN BIBIT SENGON (Paraserianthes falcataria) PADA BERBAGAI MEDIA TUMBUH GROWTH OF SENGON SEEDLING (Paraserianthes falcataria) AT VARIOUS GROWTH MEDIA

This research was carried out in Silviculture Laboratory, Agriculture Faculty, Sam Ratulangi University, from April to June 2012. The aim of this was to examine the influence of growth media combination on height, diameter and number of leaf sengon seedling, using a Randomized Complete Design with one factor. The factor is top soil, top soil and sekam bakar, and top soil and coco peat. Based on the research, the results of Anaslysis of Variance showed that top soil and combination of top soil and sekam bakar give most number of seedling leaf. However, growth of height and diameter at all of combination was no significant, but there was trend that top soil give best growth of height and best growth of diameter given by the top soil and combination of top soil and sekam bakar.
Transient climate simulation forced by natural and anthropogenic climate forcings

Numerical experiments have been carried out with a two‐dimensional sector‐averaged global climate model coupled to a diffusive ocean in order to assess the potential impact of four hypothesized mechanisms of decadal to century‐scale climate variability, both natural and anthropogenically induced: (1) solar variability; (2) variability in volcanic aerosol loading of the atmosphere; (3) anthropogenic increase of sulphate aerosols' concentration; (4) anthropogenic increase of greenhouse gas concentrations.
Evidence of a partial melt zone beneath Stromboli volcano (Italy) from inversion of teleseismic receiver functions

Teleseismic body waves from broadband seismic stations are used to investigate the crustal and uppermost mantle structure of Stromboli volcano through inversion of the receiver functions (RFs). First, we computed RFs in the frequency domain using a multiple‐taper spectral correlation technique. Then, the non‐linear neighbourhood algorithm was applied to estimate the seismic shear wave velocity of the crust and uppermost mantle and to define the main seismic velocity discontinuities. The stability of the inversion solution was tested using a range of initial random seeds and model parameterizations. A shallow Moho, present at depth of 14.8 km, is evidence of a thinned crust beneath Stromboli volcano. However, the most intriguing and innovative result is a low S velocity layer in the uppermost mantle, below 32 km. The low S velocity layer suggests a possible partial melt region associated with the volcanism, as also recently supported by tomographic studies and petrological estimations.
A situation-centric, knowledge-driven requirements elicitation approach by Jingwei Yang A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY

Human factors have been increasingly recognized as one of the major driving forces of requirement changes. We believe that the requirements elicitation (RE) process should largely embrace human-centered perspectives, and this work focuses on changing human intentions and desires over time. To support software evolution due to requirement changes, Situ framework has been proposed to model and detect human intentions by inferring their desires through monitoring environmental contexts and human behavioral contexts prior to or after system deployment. Earlier work on Situ reported that the technique is able to infer users’ desires with a certain degree of accuracy using the Conditional Random Fields method. However, new intention identification and new requirements elicitation still primarily depends on manual analysis. This work attempts to find a computable way to identify users’ new intentions with limited help from human oracle. We discuss the feasibility of implementing the concept of Data-Information-Knowledge-Wisdom (DIKW) to bridge the gap between requirements and data pertaining to user behaviors and environmental contexts, and propose a situation-centric, knowledge-driven requirements elicitation approach using the Multi-strategy, Task-adaptive Learning (MTL) method and the Strategic Rationale (SR) model. A case study shows that the proposed approach is able to identify users’ new intentions, and is especially effective to capture alternatives of low-level tasks. We also demonstrate how these newly identified intentions can be fused to the existing domain knowledge network using the SR model, and harvest high-level wisdom, in terms of new requirements and design insights.
A situation-centric, knowledge-driven requirements elicitation approach

Human factors have been increasingly recognized as one of the major driving forces of requirement changes. We believe that the requirements elicitation (RE) process should largely embrace human-centered perspectives, and this work focuses on changing human intentions and desires over time. To support software evolution due to requirement changes, Situ framework has been proposed to model and detect human intentions by inferring their desires through monitoring environmental contexts and human behavioral contexts prior to or after system deployment. Earlier work on Situ reported that the technique is able to infer users’ desires with a certain degree of accuracy using the Conditional Random Fields method. However, new intention identification and new requirements elicitation still primarily depends on manual analysis. This work attempts to find a computable way to identify users’ new intentions with limited help from human oracle. We discuss the feasibility of implementing the concept of Data-Information-Knowledge-Wisdom (DIKW) to bridge the gap between requirements and data pertaining to user behaviors and environmental contexts, and propose a situation-centric, knowledge-driven requirements elicitation approach using the Multi-strategy, Task-adaptive Learning (MTL) method and the Strategic Rationale (SR) model. A case study shows that the proposed approach is able to identify users’ new intentions, and is especially effective to capture alternatives of low-level tasks. We also demonstrate how these newly identified intentions can be fused to the existing domain knowledge network using the SR model, and harvest high-level wisdom, in terms of new requirements and design insights.
Entertainment-education and social change : history, research, and practice

Contents: Preface. Part I: History and Theory. A. Singhal, E.M. Rogers, The Status of Entertainment-Education Worldwide. D. Poindexter, A History of Entertainment-Education, 1958-2000. P.T. Poitrow, E. de Fossard, Entertainment-Education as a Public Health Intervention. M. Sabido, The Origins of Entertainment-Education. A. Bandura, Social Cognitive Theory for Personal and Social Change by Enabling Media. W.J. Brown, B.P. Fraser, Celebrity Identification in Entertainment-Education. S. Sood, T. Menard, K. Witte, The Theory Behind Entertainment-Education. Part II: Research and Implementation. S. Usdin, A. Singhal, T. Shongwe, S. Goldstein, A. Shabalala, No Short Cuts in Entertainment-Education: Designing Soul City Step-by-Step. W.N. Ryerson, N. Teffera, Organizing a Comprehensive National Plan for Entertainment-Education in Ethiopia. B.S. Greenberg, C.T. Salmon, D. Patel, V. Beck, G. Cole, Evolution of an E-E Research Agenda. V. Beck, Working With Daytime and Prime-Time Television Shows in the United States to Promote Health. M. Bouman, Entertainment-Education Television Drama in the Netherlands. M.J. Cody, S. Fernandes, H. Wilkin, Entertainment-Education Programs of the BBC and BBC World Service Trust. A.C. La Pastina, D.S. Patel, M. Schiavo, Social Merchandizing in Brazilian Telenovelas. E.M. Rogers, Delivering Entertainment-Education Health Messages Through the Internet to Hard-to-Reach U.S. Audiences in the Southwest. Part III: Entertainment-Education Interventions and Their Outcomes. R.A. Abdulla, Entertainment-Education in the Middle East: Lessons From the Egyptian Oral Rehydration Campaign. Y. Yaser, The Turkish Family Health and Planning Foundation's Entertainment-Education Campaign. N. McKee, M. Aghi, R. Carnegie, N. Shahzadi, Cartoons and Comic Books for Changing Social Norms: Meena, the South Asian Girl. A. Singhal, D. Sharma, M.J. Papa, K. Witte, Air Cover and Ground Mobilization: Integrating Entertainment-Education Broadcasts With Community Listening and Service Delivery in India. A. Singhal, Entertainment-Education Through Participatory Theater: Freirean Strategies for Empowering the Oppressed. T. Tufte, Soap Operas and Sense-Making: Mediations and Audience Ethnography. J.D. Storey, T.L. Jacobson, Entertainment-Education and Participation: Applying Habermas to a Population Program in Nepal. Epilogue.
An investigation on visitors’ expenditure pattern at Oklahoma State Parks

Abstract Based on an online survey, the answers of 355 respondents were analyzed in order to explore the influence of visitors’ personal characteristics, the visit characteristics, and purpose of visit on expenditure patterns at Oklahoma State Parks. Three models were developed based on multiple regression analyses. Findings indicated that the visitors’ expenditure pattern was most significantly influenced by age, annual household income, number of trips per year and by the particular purposes of visit. Additional information, regarding the most frequently visited Oklahoma State Parks and visitors’ preferred recreational activities at the parks provided visitors, is also presented and discussed. The paper concludes by suggesting improvement in the facilities and recreational choices offered to visitors. Implications of the study for decision makers and park managers are provided.
Genes controlling the development and function of plant vacuoles

It is known that plant cells can contain multiple distinct vacuoles, however, the abundance of multivacuolar cells and the mechanisms underlying vacuolar differentiation and communication among different type of vacuoles remained unknown. PH1 and PH5 are tonoplast P-ATPases that form a heteromeric pump which hyper-acidifies the central vacuole of epidermal cells in petunia petals. Here we show that the sorting of this pump and other vacuolar proteins to the CV involves transit through small vacuoles: vacuolinos. Vacuolino formation is controlled by transcription factors regulating pigment synthesis and transcription of PH1 and PH5. The traffic of proteins from vacuolinos to the central vacuole is impaired by miss-expression of vacuolar SNAREs as well as mutants for the PH1 component of the PH1-PH5 pump. The finding that PH1-PH5 and these SNAREs interact strongly suggests that structural tonoplast proteins can act as tethering factors in the recognition of different vacuolar types.