Mapping and validation of sex-linked SNP markers in the swimming crab Portunus trituberculatus

Portunus trituberculatus is one of the most commercially important marine crustacean species for both aquaculture and fisheries in Southeast and East Asia. Production of monosex female stocks is attractive in commercial production since females are more profitable than their male counterparts. Identification and mapping of the sex-linked locus is an efficient way to elucidate the mechanisms of sex determination in the species and support the development of protocols for monosex female production. In this study, a sex-averaged map and two sex-specific genetic maps were constructed based on 2b-restriction site-associated DNA sequencing. A total of 6349 genetic markers were assigned to 53 linkage groups. Little difference was observed in the pattern of sex-specific recombination between females and males. Association analysis and linkage mapping identified 7 markers strongly associated with sex, four of which were successfully mapped on the extremity of linkage group 22. Females were homozygous and males were heterozygous for those 7 markers strongly suggesting an XX/XY sex determination system in this species. Three Markers were successfully validated in a wild population of P. trituberculatus and exhibited a specificity ranging from 93.3% to 100%. A high-resolution melting based assay was developed for sex genotyping. This study provides new knowledge and tools for sex identification which will help the development of protocols for monosex female production of P. trituberculatus and support future genomic studies

Operation Scheduling Algorithms for Power, Energy and Resource Minimization in High-Level Synthesis

Power, energy and resource minimization subject to a latency constraint are important optimization objectives in operation scheduling in high-level synthesis. The research work presented herein aims to address each of the objective as follows. First, we proposed that the degree of optimization achievable in high-level synthesis (HLS) designs with functional unit (FU) or module selection is significantly dependent on how the FUs in the resource library are parameterized. For power minimization, our proposal is that appreciably more power optimization is possible when: • the FUs for each function type (FT) have a wide range of both power and delay metrics; • their pair-wise power-delay product ratios are close to 1, say, in the range [0.8, 1.25], than when these criteria are not satisfied. We showed that it is possible to achieve these parameter ranges for arithmetic FTs due to design variety and flexibility to hierarchically combine different design approaches. We also provided a probabilistic rationale for our hypotheses and further bolster it empirically by constructing different FU libraries that either meet or do not meet the above FU parameter criteria. Using a new power-driven simulated annealing (SA) based algorithm PSA, we consistently found that the power consumption of designs using libraries that meet our criteria are significantly lower than those that do not. Then, we proposed a leakage energy (LE) minimization scheduling algorithm LPR-GPS. It co-explores unit-time leakage power (LP) and latency spaces in order to minimize their product. LPR-GPS extends the classical force-directed scheduling (FDS) by: • an initial probabilistic distribution graph (DG) based on a non-uniform probability-driven randomized scheduling that yields the final starting scheduling probabilities that are conducive to LE minimization; • a root-mean-square (RMS) based estimation of the maximum FU usage distributed across cc’s that contributes to LE minimization; • a fast and greedy noncommittal scheduling algorithm for estimating the latency by scheduling output operations first. Experimental results show LPR-GPS reduces total LE by an average of 44% compared to the power-driven FDS and 12% compared to a version of LPR-GPS that only minimizes unit-LP. Finally, we proposed an iterative list scheduling (LS) type algorithm FALLS to minimize the total number of FUs allocated, and thus the total area, in HLS designs. FALLS incorporates a novel lookahead technique to selectively schedule available non-0-slack operations by allocating the needed FUs earlier or reserving available FUs for scheduling more timing-urgent operations later, such that no additional FU is needed and a higher FU utilization is obtained. Further, a fractional search framework is developed to iteratively estimate the number of FUs of each FT required in the final design based on the current scheduling and FU utilization, and reiterate the lookahead-based list scheduling with the new FU allocation estimate to further increase FU utilization. Experimental results comparing FALLS with several state-of-the-art algorithms using a non-trivial FU library show an average 18.9% to 71.4% FU reduction while only has 5.5% optimality gap compared to an optimal integer linear programming (ILP) formulation. FALLS also performs much better in architectural area (FU + mux/demux + register area), interconnect congestion and number of interconnects than state-of-the-art approximate algorithms, and is at most 4.0% worse in these metrics than the optimal ILP method

On the Correlation between Resource Minimization and Interconnect Complexities in High-Level Synthesis

As the technology node of VLSI designs advances to sub10 nm, two interconnect-centric metrics of a circuit, the interconnect complexity (either number of interconnects or wirelength/WL) and congestion, become critically important across all design stages alongside conventional resource or function-unit (FU)-centric metrics like area/number-of-FUs and leakage power. High Level synthesis (HLS), one of the earliest and most impactful design stages, rarely monitors interconnect metrics, which makes their recovery at later stages very difficult. HLS algorithms and tools typically perform FU-centric minimization via operation scheduling, module selection (SMS) and binding. As a consequence, it mostly overlooks interconnect-based metrics. In this paper, we explore whether this can adversely affect interconnect metrics, and in general explore the correlation between FU-centric optimization in SMS, and the resulting interconnect metrics co-optimized (along with FU metrics) in the later binding stage(s). For this purpose we develop a probabilistic analysis for post-scheduling binding to estimate interconnect metrics, and verify its accuracy by comparison to empirical results across different scheduling techniques that generate different degrees of FU optimization. Based on both empirical and analytical results we predict how interconnects metrics will pan out with different degrees of FU optimization. Finally, based on our analysis, we also provide suggestions to improve interconnect metrics for whatever FU optimization degree an available SMS technique can achieve

A Power-Driven Stochastic-Deterministic Hierarchical High-Level Synthesis Framework for Module Selection, Scheduling and Binding

We present a power-driven hierarchical framework for module/functional-unit selection, scheduling, and binding in high level synthesis. A significant aspect of algorithm design for large and complex problems is arriving at tradeoffs between quality of solution and timing complexity. Towards this end, we integrate an improved version of the very runtime-efficient list scheduling algorithm called modified list scheduling (MLS) with a power-driven simulated annealing (SA) algorithm for module selection. Our hierarchical framework efficiently explores the problem solution space by an extensive exploration of the power-driven module-selection solution space via SA, and for each module selection solution, uses MLS to obtain a scheduling and (integrated) binding (S&B) solution in which the binding is either a regular one (minimizing number of FUs and thus FU leakage power) or power-driven with mux/demux power considerations. This framework avoids the very runtime intensive exploration of both module selection and S&B within a conventional SA algorithm, but retains the basic prowess of SA by exploring only the important aspect of power-driven module-selection in a stochastic manner. The proposed hierarchical framework provides an average of 9.5% FU leakage power improvement over state of the art (approximate) algorithms that optimize only FU leakage power, and has a smaller runtime by factors of 2.5–3x. Further, compared to a sophisticated flat simulated annealing framework and an optimal 0/1-ILP formulation for total (dynamic and leakage) FU and architecture power optimization under latency constraints, PSA-MLS provides an improvement of 5.3–5.8% with a runtime advantage of 2x, and has an average optimality gap of only 4.7–4.8% with a significant runtime advantage of a factor of more than 1900, respectively

Hierarchical heterostructured nickle foam-supported Co3S4 nanorod arrays embellished with edge-exposed MoS2 nanoflakes for enhanced alkaline hydrogen evolution reaction

Transition metal chalcogenides with abundant active edge sites and suitable structures for large-scale water splitting in alkaline hydrogen evolution reaction (HER) are challenging but promising. Herein, hierarchical heterostructured nickel foam–supported Co3S4 nanorod arrays embellished with edge-exposed MoS2 nanoflakes (Edge-MoS2/Co3S4@NFs) as an effective HER catalyst are designed. There into, porous nickel foam and moderately distributed nanorod arrays of Edge-MoS2/Co3S4@NFs provide multiscale pathways for efficient charge and mass transport and significantly enlarge the surfaces for the deposition of MoS2 flakes. The superhydrophilic/aerophobic surface improves the electrolyte transport and facilitates the detachment of hydrogen bubbles from the surface of the catalyst. The MoS2 flakes anchored on nanorods are well dispersed with plentiful active sites exposed which enhance the intrinsic activity of active sites owing to the adequate intersection of charge and mass. In addition, there is a synergetic effect of bimetal sulfides, evidenced by increasing the turnover frequency. Therefore, the Edge-MoS2/Co3S4@NF affords a low overpotential (η10 = 90.3 mV and η1000 = 502.0 mV) and small Tafel slope (61.69 mV dec−1). This study provides a facile strategy to develop electrocatalysts through the synergy of enhanced thermodynamic and kinetic processes, shedding lights on the advanced design of functional materials for energy chemistry

Construction of highly efficient Z-scheme ZnxCd1-xS/Au@g-C3N4 ternary heterojunction composite for visible-light-driven photocatalytic reduction of CO2 to solar fuel

Converting CO2 into renewable solar fuel using photocatalysts is one of the most ideal solutions for environmental challenges and energy crises. Here, the solid-solid Z-scheme Zn0.5Cd0.5S/Au@g-C3N4 (ZCS/Au@CN) heterojunction showed improved photocatalytic reduction of CO2 due to the enhanced visible light consumption, fast dissolution of photogenerated electron-hole pairs, quick interfacial transfer process of electrons, and enlarged surface area. Under visible-light irradiation, methanol (CH3OH) was produced at a rate of 1.31 μmol h−1 g−1 over ZCS/Au@CN, roughly 43.6 and 32.7 folds higher than those observed over pure ZCS and CN samples. The analytical characterization results verified the role of AuNPs as an electron mediator, which improved the rapid extraction of photoinduced electrons and enhanced the reduction ability of CO2. This work not only demonstrates a facile photodeposition assisted hydrothermal method for fabrication of ZnxCd1-xS/Au@C3N4 heterojunction composite photocatalysts but also demonstrates the possibility of utilizing ternary composites for enhanced photocatalytic reduction of CO2

Multiple regulation over growth direction, band structure, and dimension of monolayer WS2 by a quartz substrate

A substrate plays a crucial role in controlled growth and property modulation of two-dimensional (2D) transition-metal dichalcogenides (TMDCs). In this work, we report multiple regulation over growth direction, band structure, and dimension of an epitaxial monolayer (1L) WS2 by an m-plane quartz substrate. The as-grown WS2 is oriented on a 2-fold symmetric m-quartz based on an anisotropic lattice match, which is distinct from that on c-sapphire. Owing to the large thermal expansion coefficient, the m-quartz generates a large compressive thermal strain in the as-grown WS2. By manipulating this thermal strain, the band structure of 1L-WS2 can be in situ regulated and a direct–indirect band gap transition occurs when the thermal strain exceeds 0.5%. Moreover, the unique atom distribution of the m-plane quartz established an anisotropic diffusion barrier for adlayer monomers which restricted the growth of WS2 uniaxially. By exploiting this, the dimension of WS2 can be tailored from a 2D triangle to a one-dimensional ribbon with controlled growth time. This work not only deepens the understanding of the relationship between a substrate and a material but also provides an effective way to directly regulate the as-grown TMDCs with desirable structures and properties