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openbsd-3-clause-clearMay 2023View details →

Data for: Machine Intelligence-Accelerated Discovery of All-Natural Plastic Substitutes

Data for: Machine Intelligence-Accelerated Discovery of All-Natural Plastic Substitutes

Fig. 8 in MS/MS-based molecular networking accelerated discovery of germacrane-type sesquiterpene lactones from Elephantopus scaber L

Fig. 8. The ability to inhibit LPS-induced NO production in BV-2 microglial cell of compounds 1–7.

Fig. 6 in MS/MS-based molecular networking accelerated discovery of germacrane-type sesquiterpene lactones from Elephantopus scaber L

Fig. 6. The ORTEP drawing of compounds 1, 2, 4 and 5.

Fig. 4 in MS/MS-based molecular networking accelerated discovery of germacrane-type sesquiterpene lactones from Elephantopus scaber L

Fig. 4. Key NOESY correlations of compounds 1–6.

Fig. 5. Experimental and calculated ECD spectra for compounds 1–6 in MS/MS-based molecular networking accelerated discovery of germacrane-type sesquiterpene lactones from Elephantopus scaber L

Fig. 5. Experimental and calculated ECD spectra for compounds 1–6 in MeOH.

Fig. 3. Key HMBC correlations and 1 H- 1 H in MS/MS-based molecular networking accelerated discovery of germacrane-type sesquiterpene lactones from Elephantopus scaber L

Fig. 3. Key HMBC correlations and 1 H- 1 H COSY correlations of compounds 1 6.

opencc-by-4.0Aug 2024View details →

Using the IBM analog in-memory hardware acceleration kit for neural network training and inference - Supplementary Material

Analog In-Memory Computing (AIMC) is a promising approach to reduce the latency and energy consumption of Deep Neural Network (DNN) inference and training. However, the noisy and non-linear device characteristics and the non-ideal peripheral circuitry in AIMC chips require adapting DNNs to be deployed on such hardware to achieve equivalent accuracy to digital computing. In this Tutorial, we provide a deep dive into how such adaptations can be achieved and evaluated using the recently released IBM Analog Hardware Acceleration Kit (AIHWKit), freely available at https://github.com/IBM/aihwkit. AIHWKit is a Python library that simulates inference and training of DNNs using AIMC. We present an in-depth description of the AIHWKit design, functionality, and best practices to properly perform inference and training. We also present an overview of the Analog AI Cloud Composer, a platform that provides the benefits of using the AIHWKit simulation in a fully managed cloud setting along with physical AIMC hardware access, freely available at https://aihw-composer.draco.res.ibm.com. Finally, we show examples of how users can expand and customize AIHWKit for their own needs. This Tutorial is accompanied by comprehensive Jupyter Notebook code examples that can be run using AIHWKit, which can be downloaded from <a href="https://github.com/IBM/aihwkit/tree/master/notebooks/tutorial" target="_blank" rel="noopener">https://github.com/IBM/aihwkit/tree/master/notebooks/tutorial</a>.

opencc-by-4.0Jan 2016View details →

Figure 2 in Is adult translocation a credible way to accelerate the recolonization process of Chondrostoma nasus in a rehabilitated river?

Figure 2. - Movement behaviours of eight translocated nases in the River Amblève between February 2011 and July 2012 in relation with the variations in water temperature and flow. In the upper graph, point 0 corresponds to the release site and dark rectangles represent the identified spawning period.

opencc-by-4.0Jan 2016View details →

Figure 1 in Is adult translocation a credible way to accelerate the recolonization process of Chondrostoma nasus in a rehabilitated river?

Figure 1. - Map of the study area and representation of the translocations of nase (Chondrostoma nasus) performed inside the River Amblève. Letters A and B indicate the two capture sites. The pictures represent the physical barriers in the upstream and downstream limits of the new river stretch.

Partial Breast Irradiation Using Accelerated Intensity Modulated Radiotherapy

ClinicalTrials.gov study NCT00581529. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Use of Teriparatide to Accelerate Fracture Healing

ClinicalTrials.gov study NCT00594906. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Concurrent Adjuvant Carboplatin and Accelerated Radiotherapy for Triple Negative Breast Cancer

ClinicalTrials.gov study NCT01289353. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Short-Term Effects & Safety of an Accelerated Intravenous Iron Regimen in Patients With Heart Failure

ClinicalTrials.gov study NCT01925703. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Prospective Randomized Study of Accelerated Radiation Therapy (PRART)

ClinicalTrials.gov study NCT04175210. IPD Sharing: NO. Countries: 1. Publications: 0.

Accelerated Theta Burst Stimulation for Inpatients With Bipolar Disorder

ClinicalTrials.gov study NCT04058249. IPD Sharing: NO. Countries: 1. Publications: 0.

Accelerated Radiation Therapy After Surgery in Treating Patients With Breast Cancer

ClinicalTrials.gov study NCT01417286. IPD Sharing: NO. Countries: 1. Publications: 0.

Cold Plasma Therapy for Acceleration of Wound Healing in Diabetic Foot

ClinicalTrials.gov study NCT04205942. IPD Sharing: NO. Countries: 0. Publications: 2.

DIAbetes Maximal ACCeleration

ClinicalTrials.gov study NCT05646147. IPD Sharing: NO. Countries: 0. Publications: 1.

Investigating Accelerated Learning and Memory in Healthy Subjects Using a Face Name Memory Task

ClinicalTrials.gov study NCT03309072. IPD Sharing: NO. Countries: 1. Publications: 0.