Abstract Spence [9] constructed $$\left( \frac{3^{d+1}(3^{d+1}-1)}{2}, \frac{3^d(3^{d+1}+1)}{2}, \frac{3^d(3^d+1)}{2}\right) $$ 3 d + 1 ( 3 d + 1 - 1 ) 2 , 3 d ( 3 d + 1 + 1 ) 2 , 3 d ( 3 d + 1 ) 2 -difference sets in groups $$K \times C_3^{d+1}$$ K × C 3 d + 1 for d any positive integer and K any group of order $$\frac{3^{d+1}-1}{2}$$ 3 d + 1 - 1 2 . Smith and Webster [8] have exhaustively studied the $$d=1$$ d = 1 case without requiring that the group have the form listed above and found many constructions. Among these, one intriguing example constructs Spence difference sets in $$A_4 \times C_3$$ A 4 × C 3 by using (3, 3, 3, 1)-relative difference sets in a non-normal subgroup isomorphic to $$C_3^2$$ C 3 2 . Drisko [3] has a note implying that his techniques allow constructions of Spence difference sets in groups with a noncentral normal subgroup isomorphic to $$C_3^{d+1}$$ C 3 d + 1 as long as $$\frac{3^{d+1}-1}{2}$$ 3 d + 1 - 1 2 is a prime power. We generalize this result by constructing Spence difference sets in similar families of groups, but we drop the requirement that $$\frac{3^{d+1}-1}{2}$$ 3 d + 1 - 1 2 is a prime power. We conjecture that any group of order $$\frac{3^{d+1}(3^{d+1}-1)}{2}$$

SUMMARY: Genome assembly projects have grown exponentially due to breakthroughs in sequencing technologies and assembly algorithms. Evaluating the quality of genome assemblies is critical to ensure the reliability of downstream analysis and interpretation. To fulfil this task, we have developed the AssemblyQC pipeline that performs file-format validation, contaminant checking, contiguity measurement, gene- and repeat-space completeness quantification, telomere inspection, taxonomic assignment, synteny alignment, scaffold examination through Hi-C contact-map visualization, and assessments of completeness, consensus quality and phasing through k-mer analysis. It produces a comprehensive HTML report with method descriptions, tables, and visualizations. AVAILABILITY AND IMPLEMENTATION: The pipeline uses Nextflow for workflow orchestration and adheres to the best-practice established by the nf-core community. This pipeline offers a reproducible, scalable, and portable method to assess the quality of genome assemblies-the code is available online at GitHub: https://github.com/Plant-Food-Research-Open/assemblyqc.

Abstract The work described in this paper builds upon our previous research on adoption modelling and aims to identify the best subset of features that could offer a better understanding of technology adoption. The current work is based on the analysis and fusion of two datasets that provide detailed information on background, psychosocial, and medical history of the subjects. In the process of modelling adoption, feature selection is carried out followed by empirical analysis to identify the best classification models. With a more detailed set of features including psychosocial and medical history information, the developed adoption model, using kNN algorithm, achieved a prediction accuracy of 99.41% when tested on 173 participants. The second-best algorithm built, using NN, achieved 94.08% accuracy. Both these results have improved accuracy in comparison to the best accuracy achieved (92.48%) in our previous work, based on psychosocial and self-reported health data for the same cohort. It has been found that psychosocial data is better than medical data for predicting technology adoption. However, for the best results, we should use a combination of psychosocial and medical data where it is preferable that the latter is provided from reliable medical sources, rather than self-reported.

A fully automatic test system for characterizing advanced probe cards able to probe on large-array fine-pitch micro-bumps (such as JEDEC's Wide-I/O Mobile DRAM interfaces [1, 2]) has been specified, developed, installed, and brought to a full-operational state. The system is based on a Cascade CM300 probe station from FormFactor and National Instruments PXI test instrumentation and complemented by in-house developed software for automatic test generation and data analysis and visualization. The system is successfully used in conjunction with FormFactor's Pyramid Probe®RBI probe-card technology on WIO1 and WIO2 micro-bump arrays on 0300mm wafers designed and manufactured by IMEC. This paper describes the various system components in hardware and software, and experimental results obtained with several test wafers.

In order to obtain acceptable compound stack yields for 2.5D- and 3D-SICs, there is a need to test the constituting dies before stacking. The non-bottom dies of these stacks have their functional access exclusively through large arrays of fine-pitch micro-bumps, which are too dense for conventional probe technology. A common approach to obtain pre-bond test access is to equip these dies with dedicated pre-bond probe pads, which comes with drawbacks such as increased silicon area, test application time, and reduced interconnect performance. In order to avoid the many drawbacks of dedicated pre-bond probe pads, we advocate the usage of advanced probe technology that allows to directly probe on these micro-bumps. This paper reports on the technical and economical feasibility of this approach.

Practical silicon stacking requires pre-tested dies, but contact probing of TSV interconnects requires much higher density, lower probing forces, and lower cost per pin than conventional probe cards have achieved. This paper examines a cost-effective, lithographic-based MEMS probe card technology that is suitable for probing 40μm pitch arrays, and scalable to finer pitches. Initial mechanical and electrical results are presented, demonstrating the feasibility of probing large arrays at 1 gram-force per tip with very low pad damage, so as not to impair downstream bonding or other processing steps.

Magnetoresistive random access memory (MRAM) technology combines a spintronic device with standard silicon-based microelectronics to obtain a combination of attributes not found in any other memory technology. Key attributes of MRAM technology are nonvolatility and unlimited read and write endurance. Magnetic tunnel junction (MTJ) devices have several advantages over other magnetoresistive devices for use in MRAM cells, such as a large signal for the read operation and a resistance that can be tailored to the circuit. Due to these attributes, MTJ MRAM can operate at high speed and is expected to have competitive densities when commercialized. In this paper, we review our recent progress in the development of MTJ-MRAM technology. We describe how the memory operates, including significant aspects of reading, writing, and integration of the magnetic material with CMOS, which enabled our recent demonstration of a 1-Mbit memory chip. Important memory attributes are compared between MRAM and other memory technologies.