Occurrence Of Minimum Research Articles

Towards a process model of supervision in social work– a bibliometric analysis

Supervision plays a pivotal role in social work, ensuring ethical practices, professional growth, and the delivery of quality services. This study conducts a bibliometric analysis to explore the evolving conceptualizations and applications of supervision in social work. Using the Web of Science Core Collection, a search for studies with "supervision AND social work" in their titles yielded 246 works. Full bibliographic records were downloaded and analyzed using VOSviewer software. A co-occurrence analysis of all keywords, with a minimum occurrence threshold of one, identified 89 keywords relevant to the topic. Excluded terms included regional and cultural-specific terms such as "England," "Ontario," and "Maori concepts," to maintain a focused and universal scope. The analysis revealed several thematic clusters encompassing clinical supervision, external supervision, crisis management, and child welfare supervision, among others. Notable themes include the intersection of supervision with burnout, cultural competence, and outcomes, highlighting its complex nature. The study emphasizes the significance of supervision frameworks tailored to diverse contexts and professional roles within social work. The findings contribute to the development of a process model for supervision, offering insights for researchers, educators, and practitioners to enhance supervisory practices. By identifying critical trends and gaps, this bibliometric analysis provides a foundation for future investigations aimed at refining supervision processes in social work.

Effective Noise Reduction in NDR Systems: A Simple Yet Powerful Apriori-Based Approach.

Noise (un-important) alerts are generally considered a major challenge in intrusion detection systems/sensors because they require more analysts to review and may cause disruption to systems that are shut down to avoid the consequences of a compromise. However, in real-world situations, many alerts could be raised for automatic tasks being completed by some software or regular tasks by users doing their daily job. This paper proposes an approach to reduce the number of noise alerts, assuming that frequent long-term security alerts can be considered noise if their frequency is meeting some criteria, such as the minimum occurrence ratio. We prove that to effectively reduce the level of noise alerts in Network Detection and Response (NDR) systems, we are able to use simpler algorithms; sometimes, the answer is in simpler solutions, and not always in complex solutions. We study data from a real customer of a Danish NDR solution and propose an Apriori-based approach to find frequent noisy alerts. Our comparison of the detected noise before and after applying our solution shows high performance in reducing noise alerts for most of the alert types for a real customer. Our experiments show that our method can filter more than 40% of the alerts by setting the minimum occurrences to 70%. Moreover, our results show that we were able to filter out more than 90% for some alert categories.

Comparison of the Occurrence Morphology of Phase Scintillation of GPS and Beidou Signals at Zhongshan Station, Antarctica

AbstractThe characteristics of phase scintillation (represented by the phase scintillation indices, σφ) from GPS and Beidou are statistically analyzed using a ground‐based receiver at Zhongshan Station, Antarctica, from 2020 to 2022 for the first time. The phase scintillation of the GPS and Beidou signals present a similar pattern of occurrence. The statistical results on the occurrence morphology of phase scintillation show that the phase scintillation predominately occurs in the magnetic pre‐noon and pre‐midnight sectors. Moreover, phase scintillation performs a dependence on solar and geomagnetic activities. Furthermore, the phase scintillation also gives a seasonal variation with the maximum occurrence happened at the autumn and the minimum occurrence during the summer. Consequently, these results improve understanding of the morphological characteristics of the phase fluctuations in the less studied Antarctic region. The study also demonstrates the use of the combined data set to improve the coverage in the Antarctic region.

On the characterization of Cloud occurrence and its impact on solar radiation in Mbour, Senegal

The objective of this study is to evaluate the clouds seasonal occurrence characteristics, and to estimate their impact on solar radiation in Mbour, Senegal, West Africa. Here, we use datasets from various sources including: i) observations from the Clouds and Earth's Radiant Energy System satellite sensors, ii) in situ shortwave radiation measurement obtained from the Mbour station, and iii) the outgoing longwave radiation (OLR) obtained from the National Centers for Environmental Prediction reanalysis data. Results show a marked seasonality, associated with high spatial variation in terms of cloud occurrence over Senegal. The maximum cloud occurrences are observed during the wet summer season (June–October), whilst the minimum cloud occurrences are recorded during the long-dry season from November to May. During the monsoon season the cloud activity becomes more intense with a total cloud cover of about 80%, a cloud optical depth of around 7, and a high convective activity illustrated by a low OLR (below 240 W/m2). Likewise, across Senegal a strong north-south gradient of the cloud characteristics is observed. Based on quantitative comparison between cloud occurrence and radiation measurement, results show an important seasonal impact on available solar potential in Mbour. Conversely to the cloud occurrence, the maximum of both direct normal and global solar potentials is recorded during the dry season, coinciding with the period with clean sky. An investigation of the cloud influence on solar radiation on selected study cases indicates a decrease of 60% (80%) for the total (direct normal) radiation during the peak of the summer monsoon season.

Когнитивное моделирование процессов адаптивного обучения

An approach to modeling adaptive learning processes using signed and weighted directed graphs (digraphs) is exam-ined. The vertices of the digraphs represent the characteristics of educational activities. The orientation, signs, and weights of the digraph arcs define the mutual influence of these characteristics. The dynamics of adaptive learning are modeled within digraphs using a specific impulse process algorithm. An external disturbance is introduced into a partic-ular vertex of the digraph, and the propagation of this impulse is analyzed, enabling the prediction of values at other vertices of the digraph. The problem of optimizing the weights of digraph arcs is formulated, and an algorithm for solv-ing it is proposed to achieve stability in the impulse process. Computational experiments on a digraph revealed that the objective function for optimizing the arcs of a weighted digraph is multiextremal. The occurrence of a local minimum is determined by the initial values of the vector of design variables (weights of digraph arcs) and constraints on these var-iables. Consequently, the qualifications of the developer of the adaptive learning model who assigns these values are crucial. Cognitive models of adaptive learning can be classified as prescriptive and descriptive. Prescriptive models out-line what the adaptive learning process should be, while descriptive models depict existing adaptive learning processes and can be utilized to study their effectiveness. The developed methodology for cognitive modeling of adaptive learn-ing processes allows for the prediction of learning outcomes and can be employed in the research, design, and imple-mentation of adaptation mechanisms and intelligent control in e-learning systems, as well as in the didactic training of teachers in the field of e-learning.

Acoustic occurrence of beaked whales off eastern Canada, 2015-2017

Several beaked whale species occur off eastern Canada. However, except for the northern bottlenose whale (NBW; Hyperoodon ampullatus), their distribution and annual occurrence remain largely unknown, which complicates management efforts to assess the status of poorly known species and effectively protect those species considered at risk. The main objective of this paper is to provide a year-round and pluriannual description of the minimum acoustic occurrence of the NBW, Sowerby’s (SBW; Mesoplodon bidens), Cuvier’s (CBW; Ziphius cavirostris), True’s (TBW; M. mirus) and Gervais’ (GBW; M. europaeus) beaked whales. Twenty-five acoustic recorders were deployed off eastern Canada between May 2015 and November 2017. Beaked whale echolocation clicks were detected using a combination of automated detectors and manual validation at 12 of these stations. Detections were generally restricted to deep continental slope waters. All detected species occurred in the southern part of the study area (off the Scotian Shelf and southern Grand Banks), while only NBWs were detected at the northern edge, off southern Labrador. Clicks identified as TBW or GBW were restricted to, but occurred annually in, the southern areas. All other species were present, at least seasonally, east and north of the Grand Banks. NBWs occurred every day in the Gully Canyon, where SBWs also occurred regularly. While these results should be interpreted as minimum species presence and considered with regards to detector performance, they provide important information regarding beaked whales’ use of areas off eastern Canada where these species have generally received no or very limited monitoring effort.

Conducting Polymers for Wearable Sensors: A Bibliometric Analysis Using VOSviewer

The objective of this study is to conduct a bibliometric analysis using VOSviewer on the research progress of the conducting polymer for wearable sensors topic. Data was extracted from the Dimensions database from 2014 to August 2023. 268 Dimensions articles were relevant to the keywords. The title and abstract from the metadata were employed to be analyzed for co-occurrence using VOSviewer. As a result, 9544 terms were obtained through the search method, but only 184 met the threshold of 10 minimum occurrences in all retrieved articles and were selected for further analysis. There was a consistent upward trend in publication numbers between 2014 to August 2023. Based on the network visualization of keyword co-occurrence, it evidenced six clusters that group all specific keywords based on the common themes. The most recent keywords (occurred between 2021 and 2022) included conductive hydrogel, polymer hydrogel, flexible sensor, MXene, strain sensor, and stretchable strain sensor. Based on this study, it is suggested to discover more about conducting and flexible hydrogel materials and the possibilities to enhance the electrical and mechanical properties of conducting polymers by introducing MXene. The materials are viewed for applications such as flexible strain sensors and other wearable sensors.

BIBLIOMETRIC ANALYSIS OF INVESTMENT CLASSIFICATION CRITERIA

"In this paper, the scientific articles from the Web of Science base were analyzed, which address the investment classification criteria by means of the bibliometric analysis. Querying the Web of Science database and applying filters revealed a sample of 273 articles. The distribution by years, by countries, by authors, by categories, by fields of research, by sustainable development goals of this sample was followed. Also, within the work, a qualitative analysis was carried out, following the words and phrases with the highest density in the studied articles. The investigation method was based on the PRISMA Statements methodology. To determine the correlations regarding the countries of origin of the authors, the Co-authorship filter was used with a minimum number of 10 documents/country and a minimum number of 11 citations/country, so out of 73 countries only 14 met the conditions for analysis. For the word density analysis, the co-occurrence filter was applied, with a minimum occurrence of 5, resulting in 37 words grouped into 5 clusters. To support the conclusions, the following classifications were analyzed: WOS Categories, Research Areas, Sustainable Development Goals, Citation Topics Micro. The results of the research constitute the starting point for future analyzes in the field of investments."

A new tree-based approach to mine sequential patterns

Generic sequential pattern mining problem aims to mine the set of sequential patterns from a sequential database that satisfies a minimum support or occurrence threshold constraint. The main challenges that affect the efficiency of a solution lie in reducing the pattern search space, early detecting the infrequent patterns, representing the database in an efficient format, etc. Also, additional challenges get included when the problem environment transitions from static to incremental database leading to not to re-mine but efficiently tracking the effect of the incremental portion over the complete updated database. In this article, we introduce a new tree-based solution to the sequential pattern mining problem, including two sets of novel solutions for static and incremental sequential databases. We propose two new structures, SP-Tree and IncSP-Tree, and design two efficient algorithms, Tree-Miner and IncTree-Miner to mine the complete set of sequential patterns from static and incremental databases respectively. The proposed novel structures provide an efficient manner to store the complete sequential database maintaining “build-once-mine-many” property and giving scope to perform interactive mining. Additionally, we also design a new breath-first based support counting technique to efficiently identify the infrequent patterns at early stages and a new heuristic pruning strategy to reduce pattern search space. We also design a new pattern storage structure BPFSP-Tree to store the frequent patterns during successive iterations in incremental mining to reduce the number of database scans and to remove the infrequent patterns efficiently. A novel structure named Sequence Summarizer is also introduced to efficiently calculate and update the co-occurrence information of the items, especially in an incremental environment. Experimental results from various real-life and synthetic datasets demonstrate the efficiency of our work in comparison with the related state-of-the-art approaches.

A Benford’s law-based framework to determine the threshold of occurrence sites for species distribution modelling from ecological monitoring databases

The use of data-based species distribution models (SDMs) has increased significantly in recent years. However, studies of determining the minimum requirements of occurrence sites from ecological monitoring datasets used in species distribution modelling remain insufficient. Therefore, this study proposed a framework to determine the threshold of minimum occurrence sites for SDMs by assessing compliance with Benford’s law. The compliance test verified that the national-scale freshwater fish monitoring dataset was natural and reliable. Results derived from true skill statistics (TSS) determined the minimum number of occurrence sites for reliable species distribution modelling was 20 with a TSS value of 0.793 and an overall accuracy of 0.804. The Benford compliance test has shown to be a useful tool for swift and efficient evaluation of the reliability of species occurrence datasets, or the determination of the threshold of occurrence sites before species distribution modelling. Further studies regarding the evaluation of this method’s transferability to other species and validation using SDM performance are required. Overall, the framework proposed in this study demonstrates that Benford compliance test applied to species monitoring datasets can be used to derive a universal and model-independent minimum occurrence threshold for SDMs.

Optimizing mat quality and transplanter performance using soil mix with vermicompost and farmyard manure in paddy tray nursery: A sustainable smart farming approach in India

In order to improve transplanter performance and mat characteristics in mat-type paddy tray nurseries in paddy cultivation and to increase the paddy seedling quality and yield, a soil mix fertilizer with vermicompost and farmyard manure was optimized in different proportions. The investigation provides valuable insights for optimizing paddy cultivation practices, with emphasis on the potential of a specific treatment TC7, composed of 50% vermicompost, 30% farmyard manure, and 20% soil, to contribute to more robust and productive paddy cultivation systems. The TC7 treatment showed notable results, including highest average paddy seed germination (93.00 ​± ​2.24%), significant paddy seedling height (16.85 ​± ​1.72 ​cm), balanced root-to-shoot ratio (0.72 ​± ​0.013), robust seedling vigour index (1567.05 ​± ​121.45), substantial biomass production (0.481 ​± ​0.0010 ​g), and significant dry matter production (0.0422 ​± ​0.0029 ​g). The highest mat thickness of 28.10 ​± ​0.05 ​mm and the lowest mat weight per m2 area of 22.30 ​± ​1.56 ​kg/m2 was recorded in TC4 treatment containing 44% vermicompost, 44% farmyard manure, and 12% soil. The highest rolling quality of the mat with a rolling score of 10.00 ​± ​0.027 in TC8 treatment containing 30% vermicompost, 50% farmyard manure, and 20% soil, and the maximum mat strength of 54.90 ​± ​3.82 ​kg/m2 in TC10 treatment (soil alone). Mechanical transplanter performance exhibited superiority maximum planted hills per meter run (7 ​± ​1), optimum seedlings per hill (3), minimum occurrences of missing hills (1), and a maximum plant population per m2 (116 ​± ​5) utilizing seedling mats prepared with TC7 treatment. The highest grain yield of 4180 ​± ​449 ​kg/ha and grain straw ratio of 0.88 ​± ​0.0317 was recorded in the TC7 treatment. Thus, this study recommends fine-tuning and adopting the TC7 treatment combination to facilitate sustainable smart farming practices in India. Farmers are encouraged to consider implementing TC7 treatment combinations to elevate the quality and productivity of paddy cultivation.

Predictive control of linear discrete-time Markovian jump systems by learning recurrent patterns

Incorporating pattern-learning for prediction (PLP) in many discrete-time or discrete-event systems allows for computation-efficient controller design by memorizing patterns to schedule control policies based on their future occurrences. In this paper, we demonstrate the effect of PLP by designing a controller architecture for a class of linear Markovian jump systems (MJSs) where the aforementioned “patterns” correspond to finite-length sequences of modes. In our analysis of recurrent patterns, we use martingale theory to derive closed-form solutions to quantities pertaining to the occurrence of patterns: (1) the expected minimum occurrence time of any pattern from some predefined collection, (2) the probability of a pattern being the first to occur among the collection. To make our method applicable to real-world dynamics, we make two extensions to common assumptions in prior pattern-occurrence literature. First, the distribution of the mode process is unknown, and second, the true realization of the mode process is not observable. As demonstration, we consider fault-tolerant control of a dynamic topology-switching network, and empirically compare PLP to two controllers without PLP: a baseline based on the novel System Level Synthesis (SLS) approach and a topology-robust extension of the SLS baseline. We show that PLP is able to reject disturbances just as effectively as the topology-robust controller at reduced computation time and control effort. We discuss several important tradeoffs, such as the size of the pattern collection and the system scale versus the accuracy of the mode predictions, which show how different PLP implementations affect stabilization and runtime performance.

The Influence of Wind-Induced Response in Urban Trees on the Surrounding Flow Field

In recent years, cities have experienced frequent climate changes and deteriorating wind environments. Urban vegetation has become an important measure to improve local microclimates with its flexible configuration. Leaves and branches also reorient with the direction of wind, affecting the airflow through the tree. However, trees are usually considered as stationary porous media areas and are not influenced by wind speed in existing numerical simulation studies. Therefore, by considering the response of a tree under natural wind, this study established a fitted relationship between porosity and wind speed by measuring the porosity of trees at different wind speeds in the field. A numerical model of the wind response of the tree was developed, and the tree drag coefficient was changed using the additional source term method to verify the feasibility of the model by measuring the wind environment behind the tree. To understand the effect of the wind-induced response on the surrounding flow field and its variation pattern, the surrounding flow fields of stationary tree (T-S) and wind-induced tree (T-D) at different wind speeds were compared and analyzed. The effect of porosity and height-to-width ratio under the wind-induced response of trees on the wind environment were quantified. It was found that at different wind speeds, as the wind speed increases, the tree porosity gradually increases and the drag coefficient decreases accordingly. The effective shading distance after wind response was 2.4H, which was 0.3H less compared to vertically fixed trees. The minimum wind speed increased linearly with plant porosity, and the minimum wind speed occurrence location and wind speed recovery distance were linearly and negatively correlated with tree height-to-width ratio. Therefore, the flow field around the tree was simulated to provide references for guiding tree planting and mitigating urban wind environments.

Seasonal Diet Variation of (Tetracerus quadricornis) Four-horned Antelope in Rangayyanadurga Wildlife Sanctuary, Karnataka, Southern India

In the ecosystem, the four-horned antelope were selective feeders by browsing and grazing plant species in different compositions. These species have adaptable characteristics to feed on nutritious parts of available shrubs and trees in their habitat. The study was conducted through fecal analysis studies on the diet of four-horned antelopes in Rangayyanadurga four-horned Antelope Wildlife Sanctuary, Karnataka, Southern India. The study identified 95.7% of the plant species that occurred in the pellet sample, with 4.30% remaining unidentified. The percentage occurrence of dicots in the pellet sample was 80.85%, while monocots had a minimum occurrence of 19.15%. In point of growth forms, trees accounted for 34.52%, shrubs for 19.15%, herbs for 19.10%, grasses for 19.14%, and climbers for 3.5%. The Poaceae family had the highest composition percentage of occurrence in the diet with 19.13%, followed by Fabaceae at 17.53% in the diet of four-horned antelope. The study concluded that antelopes were adaptable in nature when it comes to the matter of food and survival, picking out the nutritious food that they need as available in nature. The composition of plant species in the diet helps in understanding the food habits and habitats of the four-horned antelope, which is essential for conservation and management in their natural habitat. This study provides valuable knowledge of the food habits and habitats of four-horned antelopes for further studies in this area.

Bohemian sandstone for restoration of cultural heritage sites: 3D microstructure and mass transport properties

We characterised the microstructure of sandstone from the Msene locality (Czech Republic) by combining X-ray computed micro-tomography, back-scattered electron imaging, chemical composition analysis and textural analysis and gas permeation. Both, 2D and 3D images were commonly processed by linking an anisotropic non-linear diffusion filter and a segmentation method based on power watershed. This approach guaranteed binarised outputs that were almost the same in wide ranges of spatial-filter and power-watershed parameters, i.e., subjective choices of the parameters played the negligible role. The rock pore structure was found to be statistically homogeneous and almost isotropic with perfectly connected pore space. We also partitioned the void and solid phases into either grains or pores and throats, which enabled us to study characteristic sizes and connectivity of partitioned regions. By comparing pore and throat sizes, we demonstrated the significant convergent-divergent nature of the pore space because the throat size covered at most one half of the total surface area per pore (cavity). In addition, we calculated coordination numbers for all pores (cavities) to verify almost perfect connectivity of internal pores with those at the external surface. Effective (macroscopic) transport properties of the reconstructed pore space were simulated and the results were validated by experimentally observing steady state flow of inert gas. These findings appear to be a favorable starting point for future investigation of consolidation procedures. The well-connected pore structure with minimum occurrence of dead-end pores suggests that the consolidation agent is very likely to flood the whole pore space.

Increasing Risk of Spring Frost Occurrence during the Cherry Tree Flowering in Times of Climate Change

Climate change affects the agroecological conditions and persistence of cherry tree flowering. Detailed evaluation of minimum air temperature and occurrence of synoptic events occurrence during spring frosts within the cherry tree flowering in the Czech Republic (Central Europe) is missing. The main objective of this study was to evaluate the above-mentioned variables during the cherry tree flowering in different parts of the country from 1924 to 2012. Our question was how the frequency of frost days occurrence changed during the cherry tree flowering. A trend analysis was conducted with the Mann-Kendall test. The onset of the beginning of flowering and end of flowering shifted to an earlier date per the whole examined period (up to −13.9 and −8.1 days) and the period of flowering extended (up to 4.1 days). The shifts were more pronounced at higher elevations. During the period of the cherry tree flowering, the trend in change of the number of frost days was negative at the lowland station (−0.3 day) and positive at the highland station (+1.2 day). At all stations, “Ap3” synoptic event (anticyclone) occurrence during cherry tree flowering on days with the highest spring frost risk (Tmin at 2 m < −1.1 °C) prevailed. The positive trend of frost-day occurrence and the negative trend of minimum air temperature in cherry tree flowering indicate that blossoms are more endangered at higher elevations.

Probabilistic delineation of subsurface connected pathways in alluvial aquifers under geological uncertainty

The present work aims to address the issue of the delineation of subsurface pathways carved in sedimentary aquifers from a stochastic perspective. A probabilistic approach to recognize preferential alluvial pathways is proposed relying only upon borehole data. These data can be employed to identify locations where the surficial aquifer is characterized by highly permeable (alluvial) hydrofacies. A Monte Carlo (MC) approach is set up to simulate stochastic realizations of local alluvial soil ratios in a bi-dimensional regularly gridded domain. Alluvial pathways are defined as the collection of cells whose simulated alluvial ratios are greater or equal to a first threshold, imposed on the simulated sediments ratio, and sharing a minimum occurrence probability, equal to a second probabilistic threshold. Then, probable highly permeable subsurface pathways throughout the domain for a real case-study application, within the province of Lecco (Lombardy, Northern Italy), are appraised. Subsurface alluvial pathways delineated upon geological data show channel-like patterns, like their surface counterparts. Subsurface discharge peaks in the central portion of these pathways, where permeable sediment probability is higher than elsewhere. Moreover, subsurface alluvial pathways features are consistent with available hydrogeological and piezometric information. The present approach has been also compared with a Multiple-Points Statistics approach, proving better at capturing the spatial patterns of connected subsurface pathways. Therefore, the present approach seems promising to be employed in the preliminarily understanding of large-scale groundwater circulation patterns, in particular for poorly monitored areas or serving as further analysis background.

Patterns of geomagnetic Pc1 pulsations in different solar cycles in the near-equatorial region from the Indian subcontinent

Pc1 geomagnetic pulsations have been investigated at very low latitudes using 13 years of archived records covering solar cycle 20–21 from the equatorial site Choutuppal (CPL, L = 1.03), and 5 years of digital induction coil magnetometer data covering descending phase of solar cycle 24 from the low latitude site Desalpar (DSP, L = 1.07). At CPL, the maximum number of Pc1 events is seen in the declining phase of the solar cycle 20 and minimum occurrence is observed in the ascending phase of the solar cycle 21. In contrast, at DSP, the Pc1 occurrence shows a maximum during solar maximum and a minimum in the declining phase of solar cycle 24. The annual and seasonal patterns of Pc1 occurrence show an inverse relation with sunspot numbers at both stations. The seasonal variation of Pc1 occurrence has a maximum in December solstice at CPL and in June solstice at DSP, respectively. The diurnal variations of Pc1 activity show similar trends at both locations with maximum Pc1 occurrence during pre- and post-midnight sectors. The superposed epoch analysis shows minimum number of Pc1s in the initial phase, followed by Pc1 occurrence in the main phase, increasing significantly in the recovery phase of geomagnetic storms. The role of ionospheric plasma density and attenuation of Pc1 waves upon propagation via the ionospheric waveguide is presented.

Triple Factorization-Like Symmetric NLF Models With Latent Item–Item Relationship

Undirected, high-dimension and sparse (SHiDS) networks which are often encountered in industrial applications usually contain numerous useful information; thus, it is practically important to develop effective collaborative filtering methods to rigidly extract the latent information. In order to improve the performance of nonnegative latent factor (NLF) models based on the double factorization while reducing the computation burden of NLF models in terms of the triple factorization (TF) technique, a novel symmetric NLF (SNLF) model, i.e., TF-like SNLF model, is proposed in this article. A latent factor (LF) matrix that reflects the relationship of items is introduced into the objective function so as to offer more freedom for solutions. Then, a fixed weighting matrix designed by sensitivity experiments is used to replace the aforementioned LF matrix dependent on the update, which greatly helps save the time cost without sacrificing any accuracy. Furthermore, the alteration direction (ADI) method is adopted to design the algorithm, which effectively helps reduce the occurrence of the local minimum while guaranteeing convergence. Finally, experimental results on four real industrial data sets demonstrate that the proposed TF-like SNLF model makes a good compromise between the model performance and the time efficiency.

3D Selection of 167 Substellar Companions to Nearby Stars

We analyze 5108 AFGKM stars with at least five high-precision radial velocity points, as well as Gaia and Hipparcos astrometric data, utilizing a novel pipeline developed in previous work. We find 914 radial velocity signals with periods longer than 1000 days. Around these signals, 167 cold giants and 68 other types of companions are identified, through combined analyses of radial velocity, astrometry, and imaging data. Without correcting for detection bias, we estimate the minimum occurrence rate of the wide-orbit brown dwarfs to be 1.3%, and find a significant brown-dwarf valley around 40 M Jup. We also find a power-law distribution in the host binary fraction beyond 3 au, similar to that found for single stars, indicating no preference of multiplicity for brown dwarfs. Our work also reveals nine substellar systems (GJ 234 B, GJ 494 B, HD 13724 b, HD 182488 b, HD 39060 b and c, HD 4113 C, HD 42581 d, HD 7449 B, and HD 984 b) that have previously been directly imaged, and many others that are observable at existing facilities. Depending on their ages, we estimate that an additional 10–57 substellar objects within our sample can be detected with current imaging facilities, extending the imaged cold (or old) giants by an order of magnitude.