Miracle-dz/UniFAR-FTUs huggingface dataset:
Persistent pulmonary subsolid nodules: How long should they be observed until clinically relevant growth occurs?

During the first two decades of 21 st century, there has been remarkable advance in the knowledge about lung cancer. One of the most important advances is persistent pulmonary subsolid nodules (SSNs) including pure ground-glass nodules (GGNs) and part-solid nodules (PSNs). Pulmonary SSNs, when persistent, have high probability of being pulmonary adenocarcinomas spectrum pathologically, and ironically show very indolent clinical courses over follow-ups (1-3). Many researchers investigated the natural history of persistent pulmonary SSNs, which included the frequency and pattern of interval growth, and the growth rate, to determine optimal management plan of patients with these nodules (4-8). However, uncertainty still remains on the natural course of persistent SSNs, especially with respect to the long-term consequences and ideal timing for surgical resection.
From obXML to the OP ontology: developing a semantic model for occupancy profile

Building energy performance simulation is vital for predicting energy performance under speciﬁc conditions. Even though there exist several calculation methodologies that can provide precise simulation approximations, the accuracy of these tools is aﬀected by the level of detail of its input data, being occupant behavior the main source of uncertainty in building energy performance results. Hence, initiatives such as the obXML schema have been developed recently to get a deeper understanding and to generate a more elaborated description of these data. Besides, the use of semantic web technologies can open opportunities to link behavioral patterns with other building information and related domains allowing interoperability and heterogeneous data integration. This paper presents the Occupancy Proﬁle ontology, a semantic model based on obXML that allows the representation of occupant behaviors and actions inside building spaces. This paper also provides a catalogue of modelling decisions taken during the development and an example.
Histogram based Image Spam Detection using Back propagation Neural Networks

PT Abstract-In general words, image spam is a type of e-mail in which the text message is presented as a picture in an image file. This prevents the text based spam filters from detecting and blocking such spam messages. In our study we have considered the valid message as “ham” and the invalid message as “spam”. Though there are several techniques available for detecting the image spam (DNSBL, Greylisting, Spamtraps, etc.,) each one has its own advantages and disadvantages. On behalf of their weakness, they become controversial to one another. This paper includes a general study on image spam detection using some of the well-liked methods. The methods comprise, image spam filtering based on File type, RGB Histogram, and HSV histogram, which are explained in the following sections. The finest method for detecting the image spam from the above-mentioned methods can be determined from the above study.
Boundary Spanners and Calculative Practices

This paper questions to what extent particular calculative practices used for inter organisational decision-making help or hinder boundary spanners meet performativity ideals. It uses programmatic rationalities of government as a framework to study reciprocity between them and the conditions of performativity. Empirical data was collected from health care commissioning spaces of English NHS. Data triangulation was achieved through documentary analysis, data collected through interviews, and observation notes taken in local commissioning meetings and national conferences. Findings revealed an apparent lack of reciprocity between programmatic rationality and calculative practices surrounding the commissioning activities of boundary spanners. As a consequence, in local commissioning situations boundary spanners with formal roles used calculative practices differently than semi-formal boundary spanners. Unlike their formal counterparts, who used only accounting information in their calculative practices, semi-formal boundary spanners incorporated non-accounting information and devised alternative calculative practices. In addition, while formal boundary spanners on NHS Committees used calculative practices in maintaining clear boundaries between commissioning and provider organisations, semi-formal boundary spanners observed made use of the data of both parties in order to reach inter organisational decisions. The study has three main contributions. First, it differentiates boundary spanners and explains differences in their interaction with calculative practices. Second, it introduces the concept of reciprocity to inter-organisational studies in accounting. Third, it shows how conditions of performativity reflected in micro settings influenced how semi-formal boundary spanners used calculative practices (and other supplementary information) to achieve performance ideals of government programmes.
NIST TAC SM-KBP 2019 System Description: JHU/UR Framework

We designed and constructed a pipeline sys-tem for the Streaming Multimedia Knowledge Base Population (SM-KBP) 2019 evaluation. Our pipeline consists of a series of Information Extraction and Machine Translation components, supporting the population of knowledge graphs from a multilingual corpus (see Figure 1). Some of our key contributions include: a new dataset supporting event argument linking across multiple sentences; a novel algorithm for predicting such linkages, even when arguments are not co-referent with mentions in the same sentence as the event trigger; and a novel algorithm for supporting hierarchical typing of events, relations and entities.
Mapping potential signs of gas emissions in ice of lake Neyto, Yamal, Russia using synthetic aperture radar and multispectral remote sensing data

Regions of anomalously low backscatter in Cband synthetic aperture radar (SAR) imagery of lake ice of Lake Neyto in northwestern Siberia have been suggested to be caused by emissions of gas (methane from hydrocarbon reservoirs) through the lake’s sediments. However, to assess this connection, only analyses of data from boreholes in the vicinity of Lake Neyto and visual comparisons to mediumresolution optical imagery have been provided due to a lack of in situ observations of the lake ice itself. These observations are impeded due to accessibility and safety issues. Geospatial analyses and innovative combinations of satellite data sources are therefore proposed to advance our understanding of this phenomenon. In this study, we assess the nature of the backscatter anomalies in Sentinel-1 C-band SAR images in combination with very high resolution (VHR) WorldView-2 optical imagery. We present methods to automatically map backscatter anomaly regions from the Cband SAR data (40 m pixel spacing) and holes in lake ice from the VHR data (0.5 m pixel spacing) and examine their spatial relationships. The reliability of the SAR method is evaluated through comparison between different acquisition modes. The results show that the majority of mapped holes (71 %) in the VHR data are clearly related to anomalies in SAR imagery acquired a few days earlier, and similarities to SAR imagery acquired more than a month before are evident, supporting the hypothesis that anomalies may be related to gas emissions. Further, a significant expansion of backscatter anomaly regions in spring is documented and quantified in all analysed years 2015 to 2019. Our study suggests that the backscatter anomalies might be caused by lake ice subsidence and consequent flooding through the holes over the ice top leading to wetting and/or slushing of the snow around the holes, which might also explain outcomes of polarimetric analyses of auxiliary L-band Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) data. C-band SAR data are considered to be valuable for the identification of lakes showing similar phenomena across larger areas in the Arctic in future studies.
Birth-Factors and Success: A Theoretical Perspective

What causes success in people? Answering this question, Waterman and Peter (1982) demonstrates that excellence, which the authors equated with success, is dependent on myriads of factors. These factors were conceptually declassified into 7-S model. However, to many, hard work, educational qualifications, luck, prayer and preparedness cause success. These arguments are in contrast to the new theoretical perspective of success. This new paper examined previous theories on human behaviour and introduced ‘the birth factor theory of success’ as a formidable replacement to the previous theories of success. Major theories examined included: Bronfenbrenner’s ecological systems theory, diffusion of innovations theory, cognitive developmental theory, relative cohort size theory and human capital theory. However, the researcher categorised these theories as ‘previous theories’ and introduced a ‘new perspective’ entitled ‘birth factors theory of success. The paper argued that success cannot be caused by a single birth factor, rather by conglomeration of birth factors. Also, the new theory negates arguments of previous theories that success is caused by traits, innovation, gender and cohort or time of birth. The paper concluded that success is caused by where, when, how, and to whom one was born. Word Count: 189 Keyword: Success, Birth-Factor, Human Capital, Birth-Effect, month of birth, Birth Order. -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 11-08-2020 Date of Acceptance: 27-08-2020 -------------------------------------------------------------------------------------------------------------------------------------
Design and Implementation of University Sports Network Management System

: The management of university sports performance at present, involving many students in semi manual mode are repetitive and error prone, and the network is conducive to improve the efficiency of management, is conducive to the movement performance of the sharing of resources, development of network management system of university sports performance imperative. This paper introduces the design idea, main functions and key technologies of the university public sports network management system. This paper first introduces the research background, research status at home and abroad, the theory gives the project development and the use of Web technology and data mining, and then the user needs a detailed analysis, combined with the demand, the system's data flow analysis; secondly, the system architecture and database design are discussed in detail, according to the implementation method of motion the performance management of each functional module, and discusses the application of data mining in the system; finally, the test program is given and verified the correctness of the system function. The combination of decision tree ID3 algorithm based on motion, student test scores, the data mining and analysis, for the formation of information teaching materials of students' physique characteristic value, provides important reference data, so as to improve the teaching quality of physical education requirements.
Potential Short-Term Memory Induction as a Promising Method for Increasing Drought Tolerance in Sweetpotato Crop Wild Relatives [Ipomoea series Batatas (Choisy) D. F. Austin]

Crop wild relatives of sweetpotato [Ipomoea series Batatas (Choisy) D. F. Austin] are a group of species with potential for use in crop improvement programs seeking to breed for drought tolerance. Stress memory in this group could enhance these species’ physiological response to drought, though no studies have yet been conducted in this area. In this pot experiment, drought tolerance, determined using secondary traits, was tested in 59 sweetpotato crop wild relative accessions using potential short-term memory induction. For this purpose, accessions were subjected to two treatments, i) non-priming: full irrigation (up to field capacity, 0.32 w/w) from transplanting to harvest and ii) priming: full irrigation from transplanting to flowering onset (FO) followed by a priming process from FO to harvest. The priming process consisted of three water restriction periods of increasing length (8, 11, and 14 days) followed each by a recovery period of 14 days with full irrigation. Potential stress memory induction was calculated for each accession based on ecophysiological indicators such as senescence, foliar area, leaf-minus-air temperature, and leaf 13C discrimination. Based on total biomass production, resilience and production capacity were calculated per accession to evaluate drought tolerance. Increase in foliar area, efficient leaf thermoregulation, improvement of leaf photosynthetic performance, and delayed senescence were identified in 23.7, 28.8, 50.8, and 81.4% of the total number of accessions, respectively. It was observed that under a severe drought scenario, a resilient response included more long-lived green leaf area while a productive response was related to optimized leaf thermoregulation and gas exchange. Our preliminary results suggest that I. triloba and I. trifida have the potential to improve sweetpotato resilience in dry environments and should be included in introgression breeding programs of this crop. Furthermore, I. splendor-sylvae, I. ramosissima, I. tiliacea, and wild I. batatas were the most productive species studied but given the genetic barriers to interspecific hybridization between these species and sweetpotato, we suggest that further genetic and metabolic studies be conducted on them. Finally, this study proposes a promising method for improving drought tolerance based on potential stress-memory induction, which is applicable both for wild species and crops.
Bi-Directional Relationships Between Psychological Symptoms and Environmental Factors in Early Adolescence

Aim Bi-directional relationships between various environmental factors and psychological symptoms can be seen from childhood to adolescence; however, there has been little prospective cohort study, which investigated the relationships simultaneously. In this study, we first distinguished specific psychological symptoms from general psychopathology using bifactor modeling and then tested the relationships between psychological symptoms and environmental factors from childhood to early adolescence using a structural equation model (SEM). Methods The analyses were based on Tokyo TEEN Cohort (TTC) data collected between October 2012 and March 2016. We obtained self-reported psychological symptoms and environmental factors from both parents and children (at their ages of 10 and 12). Participants were 3,171 children aged 10 [girls = 1,487 (46.9%), mean age, SD = 10.2, 0.28] and subsequently 12 (N = 3,007, follow-up rate 94.8%, mean age, SD = 12.2, 0.31) from three municipalities in Tokyo area. Results The best-fit symptom models included four unique factors and general psychopathology as the common factor. Combining the good fit bifactor model and the SEM, positive relationships between symptoms and environmental factors at the same waves and some bi-directional relationships were found. Especially, general psychopathology at age 10 was associated with bullying at age 12 and parental depressive symptoms at age 10 with general psychopathology at age 12. However, some negative relationships such as bullying/bullied involvement and later psychological symptoms were also seen. Conclusion By using the newly introduced methodology, our results were partly consistent with previous literature. Further studies are needed to validate this methodology and accelerate the findings regarding the emergence of psychological symptoms and the impact of environmental factors from childhood to early adolescence.
Diversity of Cultivable Microbes From Soil of the Fildes Peninsula, Antarctica, and Their Potential Application

To explore the diversity and application potential of Antarctic microorganisms, 1208 strains bacteria and fungi were isolated from 5 samples collected from the Fildes Peninsula during China’s 27th and 31st Antarctic expeditions. By using 16S and ITS sequence similarity alignment, 83 strains bacteria belonging to 20 genera and 30 strains fungi belonging to 7 genera were identified. Among them, 1 strains bacteria and 6 strains fungi showed low sequence similarity to the database, suggesting that they might be novel species. Physiological-biochemical characteristics showed that the identified bacteria could utilize many kinds of carbohydrates and that the identified fungi could produce several kinds of extracellular enzymes. The fungal strain MS-19, identified as Aspergillus sydowii, possesses the potential to produce antifungal activity agents based on an activity-guided approach. Further isolation yielded four polyketones: versicone A (1), versicone B (2), 4-methyl-5,6-dihydro-2H-pyran-2-one (3), and (R)-(+)-sydowic acid (4). It should be noted that 1 displayed strong activity against Candida albicans, with an MIC value of 3.91 μg/mL.
Interactive Visualization of Trivariate Georeferenced Data

This paper describes an online interactive thematic map for simultaneously visualizing up to three scalar variables and which supports data filtering, panning and zooming in levels of detail. The visual encoding of the map mixes the use of colors and textures as well as simple operations like border detection and intersection identification. The user experience is enhanced by means of queries posed through manipulation tools that produce instant visual feedback. This is possible through the high rendering rates achieved by the system through the use of GPU programming to assemble and manipulate previously rasterized tiles with location information recorded in the color space of pixels. This procedure allows the implementation of interactive animated actions and spatial data decomposition.
Concept Drift Detection for Multivariate Data Streams and Temporal Segmentation of Daylong Egocentric Videos

The long and unconstrained nature of egocentric videos makes it imperative to use temporal segmentation as an important pre-processing step for many higher-level inference tasks. Activities of the wearer in an egocentric video typically span over hours and are often separated by slow, gradual changes. Furthermore, the change of camera viewpoint due to the wearer's head motion causes frequent and extreme, but, spurious scene changes. The continuous nature of boundaries makes it difficult to apply traditional Markov Random Field (MRF) pipelines relying on temporal discontinuity, whereas deep Long Short Term Memory (LSTM) networks gather context only upto a few hundred frames, rendering them ineffective for egocentric videos. In this paper, we present a novel unsupervised temporal segmentation technique especially suited for day-long egocentric videos. We formulate the problem as detecting concept drift in a time-varying, non i.i. d. sequence of frames. Statistically bounded thresholds are calculated to detect concept drift between two temporally adjacent multivariate data segments with different underlying distributions while establishing guarantees on false positives. Since the derived threshold indicates confidence in the prediction, it can also be used to control the granularity of the output segmentation. Using our technique, we report significantly improved state of the art f-measure for daylong egocentric video datasets, as well as photostream datasets derived from them: HUJI~(73.01%, 59.44%), UTEgo~(58.41%, 60.61%) and Disney~(67.63%, 68.83%).
Progress Update and Challenges on V.O2max Testing and Interpretation

The maximal oxygen uptake (V.O2max) is the primary determinant of endurance performance in heterogeneous populations and has predictive value for clinical outcomes and all-cause mortality. Accurate and precise measurement of V.O2max requires the adherence to quality control procedures, including combustion testing and the use of standardized incremental exercise protocols with a verification phase preceded by an adequate familiarization. The data averaging strategy employed to calculate the V.O2max from the breath-by-breath data can change the V.O2max value by 4–10%. The lower the number of breaths or smaller the number of seconds included in the averaging block, the higher the calculated V.O2max value with this effect being more prominent in untrained subjects. Smaller averaging strategies in number of breaths or seconds (less than 30 breaths or seconds) facilitate the identification of the plateau phenomenon without reducing the reliability of the measurements. When employing metabolic carts, averaging intervals including 15–20 breaths or seconds are preferable as a compromise between capturing the true V.O2max and identifying the plateau. In training studies, clinical interventions and meta-analysis, reporting of V.O2max in absolute values and inclusion of protocols and the averaging strategies arise as imperative to permit adequate comparisons. Newly developed correction equations can be used to normalize V.O2max to similar averaging strategies. A lack of improvement of V.O2max with training does not mean that the training program has elicited no adaptations, since peak cardiac output and mitochondrial oxidative capacity may be increased without changes in V.O2max.
Novel Branch Prediction Strategy based on Adaptive History Length for High-Performance Microprocessor

: - The demands for high-performance microprocessors have recently increased. Accurate branch prediction is one of the most important factors for high-performance processors. In order to predict branch outcomes, instruction program counter bits and the history of recently executed branch outcomes are used. Among the executed branch outcomes, some histories are useful while others are useless. In addition, these useful/useless histories vary among branch instructions. Numerous studies have shown a method that identifies optimal history. However, little research has been done regarding the treatment of useless history. In this paper, a new method called Instruction Address alloyed History Length Modification branch predictor is proposed to handle the useless history bits. When PHT entries are 4,096, IAaHLM has a prediction accuracy of 93.22% and Gshare has a prediction accuracy of 91.84%.