Libra: Achieving Efficient Instruction- and Data- Parallel Execution for Mobile Applications.

Mobile computing as exemplified by the smart phone has become an integral part of our daily lives. The next generation of these devices will be driven by providing richer user experiences and compelling capabilities: higher definition multimedia, 3D graphics, augmented reality, and voice interfaces. To meet these goals, the core computing capabilities of the smart phone must be scaled. But, the energy budgets are increasing at a much lower rate, thus fundamental improvements in computing efficiency must be garnered. To meet this challenge, computer architects employ hardware accelerators in the form of SIMD and VLIW. Single-instruction multiple-data (SIMD) accelerators provide high degrees of scalability for applications rich in data-level parallelism (DLP). Very long instruction word (VLIW) accelerators provide moderate scalability for applications with high degrees of instruction-level parallelism (ILP). Unfortunately, applications are not so nicely partitioned into two groups: many applications have some DLP, but also contain significant fractions of code with low trip count loops, complex control/data dependences, or non-uniform execution behavior for which no DLP exists. Therefore, a more adaptive accelerator is required to be able to deploy resources as needed: exploit DLP on SIMD when it’s available, but fall back to ILP on the same hardware when necessary. In this thesis, we first focus on various compiler solutions that solve inefficiency problem in both VLIW and SIMD accelerators. For SIMD accelerators, a new vectorization pass, called SIMD Defragmenter, is introduced to uncover hidden DLP using subgraph identification in SIMD accelerators. CGRA express effectively accelerates sequential code regions using a bypass network in VLIW accelerators, and Resource Recycling leverages stream-graph modulo scheduling technique for scheduling of multiple code regions in multi-core accelerators. Second, we propose the new scalable multicore accelerator referred to as Libra for mobile systems, which can support execution of code regions having both DLP and ILP, as well as hybrid combinations of the two. We believe that as industry requires higher performance, the proposed flexible accelerator and compiler support will put more resources to work in order to meet the performance and power efficiency requirements.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99840/1/yjunpark_1.pd

Negative Affect and Counterproductive Work Behavior: Roles of Arousal Level

Negative affect is examined for its influences on counterproductive work behavior (CWB) aimed at individuals (CWBI) or organizations (CWBO). The circumplex model of affect is applied to a sample of 264 employees in South Korea. Results support the predictions that high arousal negative affect is positively associated with CWBI and low arousal negative affect is positively associated with CWBO. Limitations and implications are discussed.This Study was supported by the Institute of Management Research at Seoul National Universit

Time to Progress: the Impact of Temporal Ownership on Time Perception

Time is often linguistically portrayed either in a narrative or possessive framing. Building on this tendency, the authors demonstrate that communicating time in possession framing increases perceived ownership and feelings of responsibility towards making use of time. The heightened responsibility leads consumers to minimize time loss, but maximize time investment

A microfluidic chip for screening individual cancer cells via eavesdropping on autophagyinducing crosstalk in the stroma niche

Autophagy is a cellular homeostatic mechanism where proteins and organelles are digested and recycled to provide an alternative source of building blocks and energy to cells. The role of autophagy in cancer microenvironment is still poorly understood. Here, we present a microfluidic system allowing monitoring of the crosstalk between single cells. We used this system to study how tumor cells induced autophagy in the stromal niche. Firstly, we could confirm that transforming growth factor beta 1 (TGF beta 1) secreted from breast tumor cells is a paracrine mediator of tumor-stroma interaction leading to the activation of autophagy in the stroma component fibroblasts. Through proof of concept experiments using TGF beta 1 as a model factor, we could demonstrate real time monitoring of autophagy induction in fibroblasts by single tumor cells. Retrieval of individual tumor cells from the microfluidic system and their subsequent genomic analysis was possible, allowing us to determine the nature of the factor mediating tumor-stroma interactions. Therefore, our microfluidic platform might be used as a promising tool for quantitative investigation of tumor-stroma interactions, especially for and high-throughput screening of paracrine factors that are secreted from heterogeneous tumor cell populations

Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms?

Scaling laws have allowed Pre-trained Language Models (PLMs) into the field of causal reasoning. Causal reasoning of PLM relies solely on text-based descriptions, in contrast to causal discovery which aims to determine the causal relationships between variables utilizing data. Recently, there has been current research regarding a method that mimics causal discovery by aggregating the outcomes of repetitive causal reasoning, achieved through specifically designed prompts. It highlights the usefulness of PLMs in discovering cause and effect, which is often limited by a lack of data, especially when dealing with multiple variables. Conversely, the characteristics of PLMs which are that PLMs do not analyze data and they are highly dependent on prompt design leads to a crucial limitation for directly using PLMs in causal discovery. Accordingly, PLM-based causal reasoning deeply depends on the prompt design and carries out the risk of overconfidence and false predictions in determining causal relationships. In this paper, we empirically demonstrate the aforementioned limitations of PLM-based causal reasoning through experiments on physics-inspired synthetic data. Then, we propose a new framework that integrates prior knowledge obtained from PLM with a causal discovery algorithm. This is accomplished by initializing an adjacency matrix for causal discovery and incorporating regularization using prior knowledge. Our proposed framework not only demonstrates improved performance through the integration of PLM and causal discovery but also suggests how to leverage PLM-extracted prior knowledge with existing causal discovery algorithms

Atomic-layer-confined multiple quantum wells enabled by monolithic bandgap engineering of transition metal dichalcogenides

Quantum wells (QWs), enabling effective exciton confinement and strong light-matter interaction, form an essential building block for quantum optoelectronics. For two-dimensional (2D) semiconductors, however, constructing the QWs is still challenging because suitable materials and fabrication techniques are lacking for bandgap engineering and indirect bandgap transitions occur at the multilayer. Here, we demonstrate an unexplored approach to fabricate atomic-layer-confined multiple QWs (MQWs) via monolithic bandgap engineering of transition metal dichalcogenides and van der Waals stacking. The WOX/WSe2 hetero-bilayer formed by monolithic oxidation of the WSe2 bilayer exhibited the type I band alignment, facilitating as a building block for MQWs. A superlinear enhancement of photoluminescence with increasing the number of QWs was achieved. Furthermore, quantum-confined radiative recombination in MQWs was verified by a large exciton binding energy of 193 meV and a short exciton lifetime of 170 ps. This work paves the way toward monolithic integration of band-engineered hetero-structures for 2D quantum optoelectronics

Prognostic influence of body mass index and body weight gain during adjuvant FOLFOX chemotherapy in Korean colorectal cancer patients

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Background: Asian population has different body mass index (BMI) profile compared to Caucasian population. However, the effect of obesity and body weight gain in Asian colorectal cancer patients treated with adjuvant chemotherapy has not been studied thus far. Methods: We have analyzed the association between disease-free survival (DFS) and obesity/body weight change during treatment in Korean stage III or high-risk stage II colorectal cancer patients treated with adjuvant 5-fluorouracil/leucovorin/oxaliplatin. BMI was classified according to WHO Asia-Pacific classification. Weight change was calculated by comparing body weights measured at the last chemotherapy cycle and before surgery. Results: Among a total of 522 patients, 35.7 % of patients were obese (BMI >= 25 kg/m(2)) and 29.1 % were overweight (BMI, 23-24.9 kg/m(2)) before surgery. 18.0 % of patients gained = 5 kg and 26.1 % gained 2-4.9 kg during the adjuvant chemotherapy period. Baseline BMI or body weight change was not associated with DFS in the overall study population. However, body weight gain (>= 5 kg) was associated with inferior DFS (adjusted hazard ratio 2.04, 95 % confidence interval 1.02-4.08, p = 0.043) in overweight and obese patients (BMI >= 23.0 kg/m(2)). Conclusion: In Korean colorectal cancer patients treated with adjuvant FOLFOX chemotherapy, body weight gain during the treatment period has a negative prognostic influence in overweight and obese patients

Association of pathway mutation with survival after recurrence in colorectal cancer patients treated with adjuvant fluoropyrimidine and oxaliplatin chemotherapy

Background Although the prognostic biomarkers associated with colorectal cancer (CRC) survival are well known, there are limited data on the association between the molecular characteristics and survival after recurrence (SAR). The purpose of this study was to assess the association between pathway mutations and SAR. Methods Of the 516 patients with stage III or high risk stage II CRC patients treated with surgery and adjuvant chemotherapy, 87 who had distant recurrence were included in the present study. We analyzed the association between SAR and mutations of 40 genes included in the five critical pathways of CRC (WNT, P53, RTK-RAS, TGF-β, and PI3K). Results Mutation of genes within the WNT, P53, RTK-RAS, TGF-β, and PI3K pathways were shown in 69(79.3%), 60(69.0%), 57(65.5%), 21(24.1%), and 19(21.8%) patients, respectively. Patients with TGF-β pathway mutation were younger and had higher incidence of mucinous adenocarcinoma (MAC) histology and microsatellite instability-high. TGF-β pathway mutation (median SAR of 21.6 vs. 44.4 months, p = 0.021) and MAC (20.0 vs. 44.4 months, p = 0.003) were associated with poor SAR, and receiving curative resection after recurrence was associated with favorable SAR (Not reached vs. 23.6 months, p <  0.001). Mutations in genes within other critical pathways were not associated with SAR. When MAC was excluded as a covariate, multivariate analysis revealed TGF-β pathway mutation and curative resection after distant recurrence as an independent prognostic factor for SAR. The impact of TGF-β pathway mutations were predicted using the PROVEAN, SIFT, and PolyPhen-2. Among 25 mutations, 23(92.0%)-24(96.0%) mutations were predicted to be damaging mutation. Conclusions Mutation in genes within TGF-β pathway may have negative prognostic role for SAR in CRC. Other pathway mutations were not associated with SAR.This research was supported by the Seoul National University Hospital (SNUH) Research Fund (03–2014-0440) and a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C1277 and HI13C2163). The funding bodies had no influence on the design of the study and collection, analysis, and interpretation of data and in writing the manuscript