Article
Ecology
Manuele Bazzichetto, Jonathan Lenoir, Daniele Da Re, Enrico Tordoni, Duccio Rocchini, Marco Malavasi, Vojtech Bartak, Marta Gaia Sperandii
Summary: The aim of this study was to assess how different sampling strategies affect the accuracy and precision of species response curves estimated by parametric species distribution models. The researchers simulated the occurrence of virtual plant species in Italy, using various sampling strategies, and compared the results to true coefficients. The study found that uniformly sampling the environmental space provided the best results for generalist species, while sampling occurrence data close to roads had the worst performance. For specialist species, all sampling designs showed comparable outcomes.
GLOBAL ECOLOGY AND BIOGEOGRAPHY
(2023)
Article
Operations Research & Management Science
Souvik Das, Ashwin Aravind, Ashish Cherukuri, Debasish Chatterjee
Summary: This article proposes an approach to find the optimal value of a convex semi-infinite program by solving a finite-dimensional global maximization problem. One of the major advantages of this approach is its flexibility to use various global optimization algorithms, and a simulated annealing based algorithm is proposed for high-dimensional constraint index sets. The convergence of the algorithm is proved, and the performance and accuracy are demonstrated on benchmark SIPs.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Chemistry, Analytical
Dongqi Luo, Binqiang Si, Saite Zhang, Fan Yu, Jihong Zhu
Summary: This paper focuses on the bandlimited graph signal sampling problem, proposing an efficient POGSS algorithm and an acceleration algorithm to improve evaluation speed. Theoretical analysis proves the effectiveness of POGSS, and empirical studies show its superiority over greedy algorithms.
Article
Environmental Sciences
Jian Li, Liqiao Tian, Yihong Wang, Shuanggen Jin, Tingting Li, Xuejiao Hou
Summary: This paper proposed an optimal sampling strategy using remote sensing big data and spatial sampling annealing integrated approach to optimize sampling design by minimizing spatial-temporal mean estimation error. Results showed that the RS + SSA sampling approach is superior to conventional sampling methods in improving spatial and temporal sampling accuracy.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Automation & Control Systems
Igor Melatti, Federico Mari, Toni Mancini, Milan Prodanovic, Enrico Tronci
Summary: This article presents a novel two-layer control strategy for home batteries, which enables efficient and user-oblivious substation constraint management.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Engineering, Aerospace
Jingrui Zhang, Kunpeng Zhang, Yao Zhang, Heng Shi, Liang Tang, Mou Li
Summary: This paper focuses on the minimax time problem in orbital pursuit-evasion and proposes a near-optimal guidance law using deep learning to intercept the evader.
Article
Energy & Fuels
Fulin Wang, Yunfei Zhao, Yanjun Fang
Summary: A system economic model was established to determine the development mode of layered sandstone reservoir. The model avoids the chemical agent effect and improves accuracy. The development mode can be determined by comparing cumulative oil production limits.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2023)
Article
Engineering, Chemical
Elena Leoni, Manuela Mancini, Giovanni Aminti, Gianni Picchi
Summary: Moisture content is a crucial quality parameter for wood fuels in bioenergy facilities. In Mediterranean conditions, the inherent variability of wood fuels requires a careful sampling strategy. The study suggests that for small batches like truckloads, three samples are needed for reliable moisture measurements, while for larger lots such as barge or ship loads, 20 samples can provide sufficient precision.
Article
Computer Science, Information Systems
Maria Antonia Maisto, Giovanni Leone, Adriana Brancaccio, Raffaele Solimene
Summary: This paper addresses the sampling of the near-field radiated by a planar source observed over a finite planar aperture using the warping method. The warping transformations allow for an approximation of the kernel function of the relevant operator as a band-limited function. The study shows that non-uniformly arranged sampling points across the measurement aperture are more efficient and the number of sampling points required is generally much lower than classical half-wavelength sampling.
Article
Engineering, Multidisciplinary
Jiaxuan Wang, Zhifu Zhang, Zhuang Li, Qibai Huang
Summary: This paper proposes an improved near-field acoustical holography method, JTCSA-NAH, which optimizes the hyperparameters of the CSA-NAH method through joint training and improves the implementation framework. The feasibility of JTCSA-NAH is verified through numerical examples, showing its accuracy and applicability, and it outperforms other methods in terms of performance.
Article
Computer Science, Theory & Methods
Marco Bressan
Summary: We address the problem of uniformly and randomly sampling a connected induced k-vertex subgraph from a given simple graph G. This problem is fundamental in graph mining and has applications in various domains. Surprisingly, there are no known efficient algorithms for uniform sampling, and the available algorithms either provide approximate uniform samples or have unclear or suboptimal running times. In this work, we propose a nearly optimal mixing time bound for a popular random walk technique, the first efficient algorithm for truly uniform graphlet sampling, and the first sublinear-time algorithm for e-uniform graphlet sampling.
ACM TRANSACTIONS ON ALGORITHMS
(2023)
Article
Physics, Applied
Shizheng Wen, Chunzhuo Dang, Xianglei Liu
Summary: This study presents a machine learning strategy combining an artificial neural network and a genetic algorithm for simulating the complex design process of near-field radiative heat transfer. The trained neural network accurately obtains the radiative heat flow and rectification ratio, while the genetic algorithm determines the optimal physical parameters. This work demonstrates the importance of data-driven machine learning methods in future NFRHT research.
APPLIED PHYSICS LETTERS
(2022)
Article
Nanoscience & Nanotechnology
Ming Liu, Qunping Fan, Jian Wang, Francis Lin, Zijin Zhao, Kaixuan Yang, Xingchao Zhao, Zhengji Zhou, Alex K. -Y. Jen, Fujun Zhang
Summary: Broadband photomultiplication-type organic photodetectors (PM-OPDs) were prepared with PMBBDT:PY3Se-2V and PC71BM:P3HT, and their performance can be effectively improved by optimizing the AL thickness, exhibiting broad spectral response, high EQE, and D*.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Business
Srinivas Tunuguntla, Paul R. Hoban
Summary: This article introduces a near-optimal bidding algorithm for use in real-time display advertising auctions. The algorithm has shown great performance in simulations and real-world campaigns, meeting advertiser requirements and achieving zero regret.
JOURNAL OF MARKETING RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Haoang Li, Ji Zhao, Jean-Charles Bazin, Yun-Hui Liu
Summary: This paper proposes a hybrid approach for estimating three VPs in images, combining sampling and search strategies to achieve high accuracy and efficiency simultaneously. The approach outperforms state-of-the-art methods in terms of accuracy and/or efficiency on both synthetic and real-world datasets.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Neurosciences
Priyanka Gupta, Dinu F. Albeanu, Upinder S. Bhalla
NATURE NEUROSCIENCE
(2015)
Article
Computer Science, Interdisciplinary Applications
Subhasis Ray, Chaitanya Chintaluri, Upinder S. Bhalla, Daniel K. Wojcik
Editorial Material
Biology
Priyanka Gupta, Upinder S. Bhalla
Article
Neurosciences
Upinder S. Bhalla
Article
Biology
Upinder Singh Bhalla
Article
Neurosciences
Adil G. Khan, Sonja B. Hofer
CURRENT OPINION IN NEUROBIOLOGY
(2018)
Article
Neurosciences
Adil G. Khan, Jasper Poort, Angus Chadwick, Antonin Blot, Maneesh Sahani, Thomas D. Mrsic-Flogel, Sonja B. Hofer
NATURE NEUROSCIENCE
(2018)
Article
Biology
Dilawar Singh, Upinder Singh Bhalla
Article
Biology
Aanchal Bhatia, Sahil Moza, Upinder Singh Bhalla
Article
Biochemical Research Methods
G. HarshaRani, S. Moza, N. Ramakrishnan, U. S. Bhalla
Summary: This study presents a resource of over 35,000 reaction topologies for systematic surveys of bistable biochemical reaction networks, and provides a searchable database for analyzing stability in chemical systems.
Article
Neurosciences
Suranjana Pal, Deepanjali Dwivedi, Tuli Pramanik, Geeta Godbole, Takuji Iwasato, Denis Jabaudon, Upinder S. Bhalla, Shubha Tole
Summary: Loss of the LHX2 gene in cortical progenitors results in premature ingrowth of thalamocortical afferents into the cortex, leading to atrophy of the sensory thalamus and nearly eliminating sensory innervation to the cortex. This indicates a profound mechanism operating in subplate progenitors affecting the growth of thalamocortical axons into the cortex.
JOURNAL OF NEUROSCIENCE
(2021)
Article
Neurosciences
Jasper Poort, Katharina A. Wilmes, Antonin Blot, Angus Chadwick, Maneesh Sahani, Claudia Clopath, Thomas D. Mrsic-Flogel, Sonja B. Hofer, Adil G. Khan
Summary: The selectivity of cortical neurons for sensory stimuli can increase across days as animals learn their behavioral relevance and across seconds when animals switch attention. The study found that the selectivity changes due to learning and attention were uncorrelated in individual neurons, with learning leading to suppression of responses to one stimulus and attention leading to selective enhancement and suppression. The mechanisms underlying increased discriminability of relevant sensory stimuli across longer and shorter timescales were found to be different, with cell class-specific top-down inputs explaining attentional modulation and reorganization of local functional connectivity accounting for learning-related changes.
Article
Biochemical Research Methods
Upinder Bhalla
Summary: Chemical signals play a crucial role in cell computations, and modeling these complex networks can be challenging. HillTau provides a simplified way to model these networks, condensing multiple reaction steps into single steps defined by a small number of parameters. It is fast, simple, and fits well with full chemical formulations, making it a valuable tool for modeling signaling network functions and fitting complicated networks. HillTau is especially useful for system abstraction, model reduction, data-driven optimization, and fast approximations to complex cellular signaling.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Psychiatry
Dipannita Sarkar, Mohammad Shariq, Deepanjali Dwivedi, Nirmal Krishnan, Ronald Naumann, Upinder Singh Bhalla, Hiyaa Singhee Ghosh
Summary: Research on the schizophrenia-risk gene Tcf4 has revealed its significant role in adult neurons, affecting their structure and excitability. The targets of Tcf4 in adult neurons differ from those in embryonic brains, indicating previously unappreciated gene networks regulating mature neuronal function. Acute loss of Tcf4 in adult neurons leads to changes in membrane-related processes that underlie the functional and structural integrity of adult neurons.
TRANSLATIONAL PSYCHIATRY
(2021)
Article
Neurosciences
Deepanjali Dwivedi, Sumantra Chattarji, Upinder S. Bhalla
