Selective Mapping Research Articles

Development of 454 New Kompetitive Allele-Specific PCR (KASP) Markers for Temperate japonica Rice Varieties.

Temperate japonica rice varieties exhibit wide variation in the phenotypes of several important agronomic traits, including disease resistance, pre-harvest sprouting resistance, plant architecture, and grain quality, indicating the presence of genes contributing to favorable agronomic traits. However, gene mapping and molecular breeding has been hampered as a result of the low genetic diversity among cultivars and scarcity of polymorphic DNA markers. Single nucleotide polymorphism (SNP)-based kompetitive allele-specific PCR (KASP) markers allow high-throughput genotyping for marker-assisted selection and quantitative trait loci (QTL) mapping within closely related populations. Previously, we identified 740,566 SNPs and developed 771 KASP markers for Korean temperate japonica rice varieties. However, additional markers were needed to provide sufficient genome coverage to support breeding programs. In this study, the 740,566 SNPs were categorized according to their predicted impacts on gene function. The high-impact, moderate-impact, modifier, and low-impact groups contained 703 (0.1%), 20,179 (2.7%), 699,866 (94.5%), and 19,818 (2.7%) SNPs, respectively. A subset of 357 SNPs from the high-impact group was selected for initial KASP marker development, resulting in 283 polymorphic KASP markers. After incorporation of the 283 markers with the 771 existing markers in a physical map, additional markers were developed to fill genomic regions with large gaps between markers, and 171 polymorphic KASP markers were successfully developed from 284 SNPs. Overall, a set of 1225 KASP markers was produced. The markers were evenly distributed across the rice genome, with average marker density of 3.3 KASP markers per Mbp. The 1225 KASP markers will facilitate QTL/gene mapping and marker-assisted selection in temperate japonica rice breeding programs.

An Improved GreenOFDM Scheme for PAPR Reduction

In this paper, we propose an improvement to a recent Peak-to-Average Power Ratio (PAPR) reduction technique for Orthogonal Frequency Division Multiplexing (OFDM), the GreenOFDM. This technique, which is inspired by SeLected Mapping (SLM), generates several waveform candidates using a given number of Inverse Fast Fourier Transforms (IFFT), and selects the one with the lowest PAPR for the transmission of the OFDM symbol. For U IFFTs, GreenOFDM provides better PAPR reduction capabilities than SLM-OFDM as it increases the number of waveform candidates from U (for SLM-OFDM) to U2/4. In this work, we propose an extension of the GreenOFDM that further increases the number of waveform candidates by a factor of 4 (from U2/4 to U2), or equivalently reduces by a factor of 2 the number of IFFTs for a same PAPR performance. Compared to SLM-OFDM, the improved GreenOFDM technique reduces the complexity by requiring only the square-root of the number of IFFTs for a same PAPR reduction performance. Furthermore, exciting methods for additional complexity reduction are also implemented and discussed.

DSHPoolF: deep supervised hashing based on selective pool feature map for image retrieval

Deep supervised hashing has turned up to unravel many large-scale image retrieval challenges. Although deep supervised hashing accomplishes good results for image retrieval process, requisite for further improving the retrieval accuracy always remains the primal focus of interest. In Deep hashing methods, feature representation happens at the outset of the fully connected (FC) layers, causing shortage of spatial information owing to its global nature, whereas deeper pooling layers preserve semantically similar information by retaining the images spatial information, which can result in uplifting the retrieval performance. Hereby, for enhancing the image retrieval accuracy through exploring spatial information, a novel way of deep supervised hashing based on Pooled Feature map (DSHPoolF) is proposed to generate compact hash codes that explore the spatial information by weighing the informative Feature maps from the last pooling layer. This is achieved, firstly, by weighing the last pooling layers Feature map in two ways, namely average–max-based pooling and probability-based pooling strategies. Secondly, informative Feature maps are selected with the help of the weights. In addition to this, the informative Feature maps play a key role in optimizing quantization error together with the loss function and classification errors in a single-step, point-wise ranking manner. This proposed DSHPoolF method is assessed using three datasets (CIFAR-10, MNIST and ImageNet) that unveils primitive outcome in comparison with other existing prominent hash-based methods.

An efficient SLM technique based on migrating birds optimization algorithm with cyclic bit flipping mechanism for PAPR reduction in UFMC waveform

The peak-to-average power ratio (PAPR) is one of the most serious issues to be dwelled on, carefully, in wireless communication. It is not possible to take the advantage of multicarrier transmission strategy without handling the problem of high PAPR arising from the usage of multiple subcarriers for generating the time domain transmission signals. As being a kind of multicarrier waveform, universal filtered multicarrier (UFMC) which is developed a short time ago as a contender waveform for the fifth generation (5G) telecommunication systems, suffers from the high PAPR values of its transmission signals as well. By considering the related issue, we developed a new selective mapping (SLM) technique based on migrating birds optimization (MBO) algorithm to offer an efficient solution to the problem of high PAPR in the UFMC waveform. In the proposed MBO-based SLM (MBO–SLM) scheme, in order to perform an effective phase optimization in discrete space, cyclic bit flipping mechanism is integrated to the MBO algorithm. According to the simulation results, with our proposed MBO–SLM technique, significant improvement is achieved in the PAPR reduction performance of the conventional SLM method thanks to the MBO-based phase optimization process supported by the cyclic bit flipping mechanism.

A novel discrete cuckoo search algorithm‐based selective mapping technique to minimize the peak‐to‐average power ratio of universal filtered multicarrier signal

SummaryThe universal filtered multicarrier (UFMC), which has emerged as a product of the intensive studies carried out for developing alternative waveforms compatible with the oncoming fifth generation (5G) technology, has rapidly become one of the few waveforms considered seriously to be utilized in the next generation telecommunication systems due to its exclusive features. However, high peak‐to‐average power ratio (PAPR) problem specific to the multicarrier waveforms is waiting for researchers as the primary issue to be tackled in the UFMC waveform. To address this issue, an efficient PAPR reduction scheme called discrete cuckoo search algorithm‐based selective mapping (DCS‐SLM) is suggested in this paper. While creating the proposed DCS‐SLM scheme, in order to make the original CS algorithm suitable to be integrated into the conventional SLM method, a novel DCS algorithm was developed. Thanks to the related DCS algorithm, it becomes possible in the SLM technique to perform phase sequence optimization, which is a combinatorial optimization process that can be carried out in discrete space. It is clearly observed from the simulation results that the integration of our novel DCS algorithm to create a new PAPR reduction technique called DCS‐SLM leads to a remarkable performance improvement in the conventional SLM method due to the DCS‐based phase optimization through which the PAPR of UFMC signals are reduced to minimum levels.

Demonstrating the Effect of Using Goppa Coding with Hybrid Selective Mapping and Partial Transmit Sequence Technique for PAPR Reduction in OFDM Systems

Orthogonal Frequency Division Multiplexing is a multi-carrier modulation technique which provides numerous advantages like high spectral efficiency, minimal interference, low multipath fading, etc. But Peak-to-average Power Ratio is a severe challenge in using such multiplexing technique as it introduces distortions in nonlinear devices. Various Peak-to-average Power Ratio reduction techniques have been investigated in the literature to improve the performance of Orthogonal Frequency Division Multiplexing systems. But, each of them suffers either from high complexity or degraded bit error rate or less spectral efficiency. For reducing Peak-to-average Power Ratio more effectively, a hybrid combination of Partial Transmit Sequence with Selective Mapping is detected to show better performance. In this paper, we have combined Goppa coding technique with this hybrid Selective Mapping and Partial Transmit Sequence for further improving the performance. Along with Peak-to-average Power Ratio reduction capability, the proposed technique also has inherent error control mechanism due to the use of coding. Based on the simulation results, we have concluded that the proposed technique provides good amount of Peak-to-average Power Ratio reduction than conventional techniques. The proposed technique is analyzed for different number of Orthogonal Frequency Division Multiplexing symbol candidates for Selective Mapping and different number of block divisions for Partial Transmit Sequence. Further, this technique is simulated for different number of subcarriers and modulation order and the simulation results are compared with each other. The proposed technique also shows better Bit error rate values for high Signal-to-Noise ratio.

PAPR reduction of MIMO-OFDM system with reduced computational complexity SLM scheme

Multiple input and multiple output orthogonal frequency division multiplexing (MIMO-OFDM) is a prominent technology for fourth generation mobile radio communication. OFDM is a special case of multi-carrier-modulation (MCM) technique that divides the high data rate input bit streams into large number of lower rate sub streams and each sub stream is transmitted over orthogonal subcarriers. The main advantage of MIMO-OFDM system is the efficient utilization of band width, multipath delay spread tolerance and mitigation of inter symbol interference (ISI) in frequency selective fading channels. However, the main drawback of MIMO-OFDM system is high peak to average power ratio (PAPR) for large number of sub carriers which causes serious degradation in performance. One of the well-known peak to average power ratio (PAPR) reduction schemes for MIMO-OFDM systems is selected mapping (SLM) scheme. In this work computational complexity of MIMO-OFDM system is reduced by adding mapping signal sequences to the OFDM signal sequences. It also increases the PAPR reduction performance of the MIMO-OFDM system.

The Role of Frontoparietal Cortex across the Functional Stages of Visual Search

Areas in frontoparietal cortex have been shown to be active in a range of cognitive tasks and have been proposed to play a key role in goal-driven activities (Dosenbach, N. U. F., Fair, D. A., Miezin, F. M., Cohen, A. L., Wenger, K. K., Dosenbach, R. A. T., et al. Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences, U.S.A., 104, 11073-11078, 2007; Duncan, J. The multiple-demand (MD) system of the primate brain: Mental programs for intelligent behavior. Trends in Cognitive Sciences, 14, 172-179, 2010). Here, we examine the role this frontoparietal system plays in visual search. Visual search, like many complex tasks, consists of a sequence of operations: target selection, stimulus-response (SR) mapping, and response execution. We independently manipulated the difficulty of target selection and SR mapping in a novel visual search task that involved identical stimulus displays. Enhanced activity was observed in areas of frontal and parietal cortex during both difficult target selection and SR mapping. In addition, anterior insula and ACC showed preferential representation of SR-stage information, whereas the medial frontal gyrus, precuneus, and inferior parietal sulcus showed preferential representation of target selection-stage information. A connectivity analysis revealed dissociable neural circuits underlying visual search. We hypothesize that these circuits regulate distinct mental operations associated with the allocation of spatial attention, stimulus decisions, shifts of task set from selection to SR mapping, and SR mapping. Taken together, the results show frontoparietal involvement in all stages of visual search and a specialization with respect to cognitive operations.

Human electrophysiology reveals delayed but enhanced selection in inhibition of return

Visual environment tends to be stable over the short run. An immediately visited location often doesn't provide new information and can be safely inhibited, as exemplified by inhibition of return (IOR)—attention takes longer to return to a previously cued location. Attention selection at this inhibited location has been widely characterized as inferior, in which the target at the cued location has diminished salience, with lower rate of accumulation in the priority map for attention selection. We demonstrate here that an electrophysiology index of visual selection—the N2pc component—is delayed but enhanced at the cued than uncued location, and this enhancement in the N2pc amplitude predicts reduction in the behavioral IOR effect. By isolating a pure target N2pc, these results reveal an active attention enhancement mechanism that facilitates adaptive allocation of attention when a target appears at a previously cued location, potentially acting as a compensation mechanism for inhibition.

Effective PAPR reduction in SCFDM‐based massive MIMO system using binary crow search algorithm for visible light communication towards 5G networks

Presently, the single-carrier frequency division multiplexing (SCFDM)-based visible light communication (VLC) system is extensively implemented for secure and high-speed data transmission. However, the effect of additive white Gaussian noise in VLC with white light-emitting diode is high, due to a high peak to average power ratio (PAPR). To address this difficulty in 5G networks, two objectives were carried out in this research article. Initially, selective mapping (SLM) scheme was applied for PAPR reduction, because it considerably selects the effective phase rotation factors that help in the reduction of system complexity. Besides, binary crow search algorithm was used for sub-block partition optimisation in SLM for enhancing the convergence speed of the proposed SCFDM-based VLC system. In the experimental investigation, the proposed SCFDM-based VLC system was analysed in terms of complementary cumulative distribution function, bit error rate and signal-to-noise ratio by varying the equalisation techniques for 5G networks.

Indicator element selection and geochemical anomaly mapping using recursive feature elimination and random forest methods in the Jingdezhen region of Jiangxi Province, South China

Determining indicator element association for mineralization can not only improve mineral exploration efficiency but also reduce the cost of unnecessary element analysis during geochemical exploration. This study provides a case study of Zhuxi tungsten-copper deposits and presents a workflow using recursive feature elimination and random forest methods to select the indicator element association for copper and tungsten mineralization in regional geochemical mapping. First, a training dataset containing positive and negative samples was built based on the known mineral deposits and mineral deposit model. Second, a 100-time simulation of recursive feature elimination with cross-validation based on random forest (RFECV-RF) was run to get a robust result of indicator elements by the ranking of variable importance. Third, the random forest (RF) method was used to integrate six indicator elements for mapping geochemical anomaly. The Youden index and prediction-area (P-A) plot were used to determine the threshold value for geochemical anomaly identification. The results demonstrated the hybrid workflow was useful to determine key indicator element for geochemical anomaly identification associated with copper and tungsten mineralization. Bi, Mo, Cu, Cd, W, and As were selected as the key indicator elements for geochemical exploration of Cu–W mineralization. Bi, Mo, W and Cu elements correspond to skarn and altered granite mineralization at depth while Cd and As elements correspond to the hydrothermal-vein mineralization at shallow levels. The result of receiver operating characteristic (ROC) curve showed that geochemical anomaly identified using the hybrid method proposed in this study had the best performance in producing comprehensive geochemical signatures. The six indicator elements also exhibited an excellent performance of identifying geochemical anomaly associated to Cu–W mineralization. This study provides a cost-benefit solution to reduce the cost of unnecessary elements concentration detection by determining a small number of key indicator elements using machine learning methods in the regional geochemical mapping for discovering mineral deposits.

A Novel Distributive Population-Based Differential Evolution Algorithm for SLM Scheme to Reduce PAPR in Massive MIMO-OFDM Systems

To achieve the ever rising demand for high data rates with high spectral efficiency, the energy efficient massive Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) will be essential and useful for future wireless communication systems as well as Industrial network applications to reduce the operational costs significantly. But the high Peak to Average Power Ratio (PAPR) in a massive MIMO-OFDM system is identified as a critical issue that causes the non-linear signal distortion and restricts the efficiency of the power amplifier. Among different PAPR reduction schemes, Selected Mapping (SLM) is a distortionless technique and highly attractive due to its simple implementation capability. However, the conventional SLM scheme is inefficient for the massive MIMO-OFDM antenna system for its enormous Side Information (SI) burden and large computational complexity to search the best set of phase factors. In this paper, a Distributive Population based Switching Differential Evolution strategy is incorporated in the SLM scheme which eventually enhances the searching ability. The algorithm is employed in different antenna grouping (homogeneous and heterogeneous) based massive MIMO systems. The antenna grouping concept in the massive MIMO system minimizes the SI burden. The proposed algorithm for SLM techniques outperforms the existing techniques in terms of PAPR, Bit Error Rate, SI burden, energy efficiency and computational complexity.

A Multi-Carrier Waveform Design for 5G and beyond Communication Systems

The next generation communication network (NGCN) is expected to provide higher spectral efficiency, low latency, large throughput and massive machine-to-machine type communications. In this regard, the design of the multi-carrier waveform (MCW) is posing a major research problem for the NGCN. To overcome the stated problem, a lot of state-of-the-art work exists that proposes various MCW alternative to the standard orthogonal frequency division multiplexing (OFDM) waveform. It is true that OFDM was used in a number of real-time communication systems of fourth generation (4G) networks. However, their use in the upcoming fifth generation (5G) network is not very feasible. This is because of the strict requirements of 5G communication systems, which also extend beyond 5G systems; hence rendering the use of OFDM infeasible for newer communication standards. To satisfy the requirements of upcoming communication networks, there is a dire need for MCWs with better flexibility. In this regard, a precoding-based MCW has been proposed. The proposed MCW fulfills the requirements of the NGCN in terms of low peak-to-average power ratio (PAPR), high spectral efficiency and throughput. The MCW proposed in this work uses power-domain multiplexing such as non-orthogonal multiple access (NOMA) and phase rotation by using the selective mapping (SLM) and generalized chirp-like (GCL) precoding of the input signal to the universal filtered multi-carriers (UFMC) modulations. Statistical analysis of the PAPR is presented by using the complementary cumulative distribution function (CCDF). The MATLAB® simulations have been carried out to implement the CCDF of PAPR and results show that a PAPR gain of 5.4 dB is obtained when the proposed waveform is compared with the standard NOMA-UFMC waveform at clip rate of 10−3, using 4-QAM.

A fully integrated machine learning scan of selection in the chimpanzee genome.

After diverging, each chimpanzee subspecies has been the target of unique selective pressures. Here, we employ a machine learning approach to classify regions as under positive selection or neutrality genome-wide. The regions determined to be under selection reflect the unique demographic and adaptive history of each subspecies. The results indicate that effective population size is important for determining the proportion of the genome under positive selection. The chimpanzee subspecies share signals of selection in genes associated with immunity and gene regulation. With these results, we have created a selection map for each population that can be displayed in a genome browser (www.hsb.upf.edu/chimp_browser). This study is the first to use a detailed demographic history and machine learning to map selection genome-wide in chimpanzee. The chimpanzee selection map will improve our understanding of the impact of selection on closely related subspecies and will empower future studies of chimpanzee.

PAPR Reduction in UFMC for 5G Cellular Systems

Universal filtered multi-carrier (UFMC) is a potential multi-carrier system for future cellular networks. UFMC provides low latency, frequency offset robustness, and reduced out-of-band (OOB) emission that results in better spectral efficiency. However, UFMC suffers from the problem of high peak-to-average power ratio (PAPR), which might impact the function of high power amplifiers causing a nonlinear distortion. We propose a comparative probabilistic PAPR reduction technique, called the decomposed selective mapping approach, to alleviate PAPR in UFMC systems. The concept of this proposal depends on decomposing the complex symbol into real and imaginary parts, and then converting each part to a number of different phase vectors prior to the inverse fast Fourier transform (IFFT) operation. The IFFT copy, which introduces the lowest PAPR, is considered for transmission. Results obtained using theoretical analysis and simulations show that the proposed approach can significantly enhance the performance of the UFMC system in terms of PAPR reduction. Besides, it maintains the OOB emission with candidate bit error rate and error vector magnitude performances.

Accessing Excited State Molecular Vibrations by Femtosecond Stimulated Raman Spectroscopy.

Excited state vibrations are crucial for determining the photophysical and photochemical properties of molecular compounds. Stimulated Raman scattering can coherently stimulate and probe molecular vibrations with optical pulses, but it is generally restricted to ground state properties. Working under resonance conditions enables cross-section enhancement and selective excitation to a targeted electronic level but is hampered by an increased signal complexity due to the presence of overlapping spectral contributions. Here, we show how detailed information about ground and excited state vibrations can be disentangled by exploiting the relative time delay between Raman and probe pulses to control the excited state population, combined with a diagrammatic formalism to dissect the pathways concurring with the signal generation. The proposed method is then exploited to elucidate the vibrational properties of the ground and excited electronic states in the paradigmatic case of cresyl violet. We anticipate that the presented approach holds the potential for selective mapping of the reaction coordinates pertaining to transient electronic stages implied in photoactive compounds.

Development and Reorganization of Orientation Representation in the Cat Visual Cortex: Experience-Dependent Synaptic Rewiring in Early Life.

To date, numerous mathematical models have been proposed on the basis of some types of Hebbian synaptic learning to account for the activity-dependent development of orientation maps as well as neuronal orientation selectivity. These models successfully reproduced orientation map-like spatial patterns. Nevertheless, we still have questions: (1) How does synaptic rewiring occur in the visual cortex during the formation of orderly orientation maps in early life? (2) How does visual experience contribute to the maturation of orientation selectivity of visual cortical neurons and reorganize orientation maps? (3) How does the sensitive period for orientation plasticity end? In this study, we performed animal experiments and mathematical modeling to understand the mechanisms underlying synaptic rewiring for experience-dependent formation and reorganization of orientation maps. At first, we visualized orientation maps from the intrinsic signal optical imaging in area 17 of kittens reared under single-orientation exposure through cylindrical-lens-fitted goggles. The experiments revealed that the degree of expansion of cortical domains representing the experienced orientation depends on the age at which the single-orientation exposure starts. As a result, we obtained the sensitive period profile for orientation plasticity. Next, we refined our previously proposed mathematical model for the activity-dependent self-organization of thalamo-cortical inputs on the assumption that rewiring is caused by the competitive interactions among transient synaptic contacts on the same dendritic spine. Although various kinds of molecules have been reported to be involved in such interactions, we attempt to build a mathematical model to describe synaptic rewiring focusing on brain-derived neurotrophic factor (BDNF) and its related molecules. Performing computer simulations based on the refined model, we successfully reproduced orientation maps reorganized in kittens reared under single-orientation exposure as well as normal visual experience. We also reproduced the experimentally obtained sensitive period profile for orientation plasticity. The excellent agreement between experimental observations and theoretical reproductions suggests that the BDNF-induced competitive interaction among synaptic contacts from different axons on the same spine is an important factor for the experience-dependent formation and reorganization of orientation selectivity and orientation maps.

Evaluating a Suitable Aquaculture Site Selection Model for Cobia (Rachycentron canadum) during Extreme Events in the Inner Bay of the Penghu Islands, Taiwan

Despite numerous studies on the effect of a cold weather disaster on fisheries in 2008, no operational systems have been developed to monitor the threat of such an event to mariculturists in the Penghu Islands (PHI) region of Taiwan. The present study employed a suitable aquaculture site selection map of the inner bay of the PHI to reduce aquaculture losses and mortality rates of cobia (Rachycentron canadum) during extreme events. Daily marine environmental data, including sea surface temperature (SST), chlorophyll-a concentration (chl-a), and wind speed in the winter, were collected. An extreme event was defined as a period of over 11 days in a month of strong winds (>6 m/s). Four parameters in the PHI inner bay, including SST, cold-water intrusion days, chl-a, and offshore distance to the PHI coastline, were used to evaluate suitable aquaculture sites for cobia culture. The results indicated that La Niña events could not be used as a factor to detect cold-water intrusion events and select suitable aquaculture sites in the PHI. The evaluated suitable aquaculture site selection map, obtained using an arithmetic mean model and a geometric mean model, revealed that the avoidance sites during extreme events were concentrated in the northern and northwestern PHI. Suitable areas were concentrated in the southeastern areas. We further suggested that commercial cobia aquaculture operations in the PHI inner bay could be moved to the suitable sites in southeastern PHI during extreme events.

Combining partial transmit sequences and selective mapping to reduce computational complexity of selective mapping techniques

AbstractBoth selective mapping (SLM) and partial transmit sequences (PTSs) are multiple signal representation (MSR) techniques used to reduce the peak to average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. Given the same number of candidate signals, SLM is superior to PTS in improving PAPR performance. However, SLM is associated with greater computational complexity, as more inverse discrete Fourier transforms (IDFTs) are required for SLM in comparison with PTS. To address this issue, this study proposes an improved SLM scheme, which divides available subcarriers into two parts, with one part used in PTS and the other in SLM. The proposed method determines whether PTS or SLM is to be used by input signals by setting an adaptive threshold, which can reduce the number of IDFTs accumulated over the implementation of SLM following a large number of OFDM signal transmissions. Statistical analysis of the simulation results show that after a large number of OFDM signals are transmitted, the proposed method not only reduces the number of IDFTs accumulated, but also allows each transmit signal to have PAPR‐reduction performance equivalent to that of conventional SLM schemes.

A two-dimensional phase-field study on dendritic growth competition under convective conditions

In the present work, the growth competition of columnar dendrites is investigated in the presence of melt convection. By using a multiphase-field model, the microstructural evolution of unidirectionally solidified dendrites with different crystal orientations is addressed in detail. Generally, for converging bicrystal grains, the dendritic growth competition follows a conventional overgrowth model, where a favorably oriented dendrite eliminates an unfavorably oriented dendrite at the grain boundary. However, in the presence of lateral melt flow in the liquid phase, we discover that the conventional overgrowth mechanism transforms into an unusual overgrowth mechanism as the melt velocity gradually increases. Recently observed in bi-crystal studies, the unfavorably oriented dendrites overgrow at the expense of the favorably oriented dendrites during an unusual overgrowth behavior. From our simulations we elucidate that the presence of an additional convective transport in the liquid phase modifies the solute distribution at the grain boundary, which in turn affects the overgrowth mechanism of converging dendrites. We show that there exists a critical melt velocity to determine the growth competition at the grain boundary. In addition, the role of interfacial anisotropy on growth competition is analyzed in detail, where we discern that the conventional overgrowth behavior is dominant at large anisotropic strengths. Lastly, a morphological selection map is depicted to predict the crossover region between the two overgrowth behaviors.