The IBM Z microprocessor in the z14 system has been redesigned to improve performance, system capacity, and security 1 over the previous z13 system 2. The system contains up to 24 central processor ...(CP) and 4 system controller (SC) chips. Each CP, shown in die photo A (Fig. 2.2.7), operates at 5.2GHz and is comprised of 10 cores, 2 PCIe Gen3 interfaces, an IO bus controller (GX), 128MB of L3 embedded DRAM (eDRAM) cache, X-BUS interfaces connecting to 2 other CP chips and one SC chip, and a redundant array of independent memory (RAIM) interface. Each core on the CP chip has 4MB of eDRAM L2 Data cache and 2MB of eDRAM L2 Instruction cache, with 128KB SRAM Instruction and 128KB SRAM Data L1 caches. Each SC, shown in die photo B (Fig. 2.2.7), operates at 2.6GHz and has 672MB of L4 eDRAM cache, X-BUS interfaces connecting to CP chips in the drawer and A-BUS interfaces connecting SCs on the other drawers. Both chips are 696mm 2 and are designed in Global Foundries 14nm high performance (14HP) SOI FinFET technology with 17 layers of copper interconnect 3. The CP contains 6.1B transistors, while the SC contains 9.7B transistors. The total IO bandwidth of the CP and SC are 2.9Tb/s and 5.5Tb/s, respectively.
We face increasing demand for greater access to effective routine mental health services, including telehealth. However, treatment outcomes in routine clinical practice are only about half the size ...of those reported in controlled trials. Progress feedback, defined as the ongoing monitoring of patients' treatment response with standardized measures, is an evidence-based practice that continues to be under-utilized in routine care. The aim of the current review is to provide a summary of the current evidence base for the use of progress feedback, its mechanisms of action and considerations for successful implementation. We reviewed ten available meta-analyses, which report small to medium overall effect sizes. The results suggest that adding feedback to a wide range of psychological and psychiatric interventions (ranging from primary care to hospitalization and crisis care) tends to enhance the effectiveness of these interventions. The strongest evidence is for patients with common mental health problems compared to those with very severe disorders. Effect sizes for not-on-track cases, a subgroup of cases that are not progressing well, are found to be somewhat stronger, especially when clinical support tools are added to the feedback. Systematic reviews and recent studies suggest potential mechanisms of action for progress feedback include focusing the clinician's attention, altering clinician expectations, providing new information, and enhancing patient-centered communication. Promising approaches to strengthen progress feedback interventions include advanced systems with signaling technology, clinical problem-solving tools, and a broader spectrum of outcome and progress measures. An overview of methodological and implementation challenges is provided, as well as suggestions for addressing these issues in future studies. We conclude that while feedback has modest effects, it is a small and affordable intervention that can potentially improve outcomes in psychological interventions. Further research into mechanisms of action and effective implementation strategies is needed.
The radial velocity method is one of the most successful techniques for detecting exoplanets. It works by detecting the velocity of a host star induced by the gravitational effect of an orbiting ...planet, specifically the velocity along our line of sight, which is called the radial velocity of the star. Low-mass planets typically cause their host star to move with radial velocities of 1 m/s or less. By analyzing a time series of stellar spectra from a host star, modern astronomical instruments can in theory detect such planets. However, in practice, intrinsic stellar variability (e.g., star spots, convective motion, pulsations) affects the spectra and often mimics a radial velocity signal. This signal contamination makes it difficult to reliably detect low-mass planets. A principled approach to recovering planet radial velocity signals in the presence of stellar activity was proposed by Rajpaul et al. (2015). It uses a multivariate Gaussian process model to jointly capture time series of the apparent radial velocity and multiple indicators of stellar activity. We build on this work in two ways: (i) we propose using dimension reduction techniques to construct new high-information stellar activity indicators; and (ii) we extend the Rajpaul et al. (2015) model to a larger class of models and use a power-based model comparison procedure to select the best model. Despite significant interest in exoplanets, previous efforts have not performed large-scale stellar activity model selection or attempted to evaluate models based on planet detection power. In the case of main sequence G2V stars, we find that our method substantially improves planet detection power compared to previous state-of-the-art approaches.
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