Edge and Central Cloud Computing: A Perfect Pairing for High Energy Efficiency and Low-latency

In this paper, we study the coexistence and synergy between edge and central cloud computing in a heterogeneous cellular network (HetNet), which contains a multi-antenna macro base station (MBS), multiple multi-antenna small base stations (SBSs) and multiple single-antenna user equipment (UEs). The SBSs are empowered by edge clouds offering limited computing services for UEs, whereas the MBS provides high-performance central cloud computing services to UEs via a restricted multiple-input multiple-output (MIMO) backhaul to their associated SBSs. With processing latency constraints at the central and edge networks, we aim to minimize the system energy consumption used for task offloading and computation. The problem is formulated by jointly optimizing the cloud selection, the UEs' transmit powers, the SBSs' receive beamformers, and the SBSs' transmit covariance matrices, which is {a mixed-integer and non-convex optimization problem}. Based on methods such as decomposition approach and successive pseudoconvex approach, a tractable solution is proposed via an iterative algorithm. The simulation results show that our proposed solution can achieve great performance gain over conventional schemes using edge or central cloud alone. Also, with large-scale antennas at the MBS, the massive MIMO backhaul can significantly reduce the complexity of the proposed algorithm and obtain even better performance.Comment: Accepted in IEEE Transactions on Wireless Communication

Localized JNK signaling regulates organ size during development.

A fundamental question of biology is what determines organ size. Despite demonstrations that factors within organs determine their sizes, intrinsic size control mechanisms remain elusive. Here we show that Drosophila wing size is regulated by JNK signaling during development. JNK is active in a stripe along the center of developing wings, and modulating JNK signaling within this stripe changes organ size. This JNK stripe influences proliferation in a non-canonical, Jun-independent manner by inhibiting the Hippo pathway. Localized JNK activity is established by Hedgehog signaling, where Ci elevates dTRAF1 expression. As the dTRAF1 homolog, TRAF4, is amplified in numerous cancers, these findings provide a new mechanism for how the Hedgehog pathway could contribute to tumorigenesis, and, more importantly, provides a new strategy for cancer therapies. Finally, modulation of JNK signaling centers in developing antennae and legs changes their sizes, suggesting a more generalizable role for JNK signaling in developmental organ size control

{1,3-Bis[(diphenyl­phosphanyl-κP)­oxy]prop-2-yl-κC 2}iodido(trimethyl­phosphane)cobalt(II)

The title compound, [Co(C27H25O2P2)I(C3H9P)], was synthesized by the addition of 1-iodo­butane to a solution of the parent cobalt complex {1,3-bis­[(diphenyl­phosphan­yl)­oxy]prop-2-yl}bis­(trimethyl­phosphane)cobalt(II). Two five-membered cobaltocycles with considerable ring bending (sum of inter­nal angles = 516.4 and 517.7°) are formed through two P atoms of the PPh2 groups and a metallated Csp 3 atom. The CoII atom is centered in a trigonal-bipyramidal configuration

Wafer Map Defect Patterns Semi-Supervised Classification Using Latent Vector Representation

As the globalization of semiconductor design and manufacturing processes continues, the demand for defect detection during integrated circuit fabrication stages is becoming increasingly critical, playing a significant role in enhancing the yield of semiconductor products. Traditional wafer map defect pattern detection methods involve manual inspection using electron microscopes to collect sample images, which are then assessed by experts for defects. This approach is labor-intensive and inefficient. Consequently, there is a pressing need to develop a model capable of automatically detecting defects as an alternative to manual operations. In this paper, we propose a method that initially employs a pre-trained VAE model to obtain the fault distribution information of the wafer map. This information serves as guidance, combined with the original image set for semi-supervised model training. During the semi-supervised training, we utilize a teacher-student network for iterative learning. The model presented in this paper is validated on the benchmark dataset WM-811K wafer dataset. The experimental results demonstrate superior classification accuracy and detection performance compared to state-of-the-art models, fulfilling the requirements for industrial applications. Compared to the original architecture, we have achieved significant performance improvement.Comment: 6 pages, 2 figures, CIS confernec

A literature review of the COVID-19 pandemic’s effect on sustainable HRM

The ramifications of the COVID-19 pandemic continue to emerge across all facets of the world of work, including the field of human resource management (HRM). Sustainable HRM, drawing on the triple bottom line elements of the economic, environmental and social pillars of sustainability, provides an ideal basis from which to understand the intersection of the COVID-19 pandemic and HRM. In this systematic literature review, we analyze peer reviewed articles published in the nexus of the pandemic and sustainable HRM, identifying the dimensions and extent of research in this topical area of study. Our CEDEL model—complicator–exposer–disruptor–enabler– legitimizer—conceptualizes our understanding of the role of COVID-19 in sustainable HRM. This paper provides a framework from which future studies can benefit when investigating the impacts of COVID-19, and a comprehensive identification of future research avenues. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Huntington's like conditions in China, A review of published Chinese cases

Background: Knowledge about HD in China is lacking in the international literature. We have therefore analyzed the Chinese literature to thoroughly explore the clinical characteristics of Huntington disease in China. Methods: A computer-based online search of China National Knowledge Infrastructure was performed to review case reports concerning HD published between January 1980 and April of 2011, and the clinical characteristics were extracted. Results: A total of 92 studies involving 279 patients (157 males and 122 females) were collected, 82.0% of which were from provinces of North China. Most of the cases (97.8%) had a family history of HD, and paternal inheritance (65.5%) was higher than maternal inheritance (34.5%). Onset age was 35.8 (± 11.8) years, death occurred with 45.6 (± 13.5) years after a course of 11.6 (± 5.6) years. Involuntary movements were the most frequent reported presentation (found in 52.3%, including 64.4% in the entire body, 19.8% in the upper limbs, and 13.7% in the head and face). Psychiatric symptoms at onset were reported in 16.1%, and cognitive impairment in 1.8%. With disease progression, 99.6% of patients had abnormal movements, 67.9% cognitive impairment, and 35.0% suffered psychiatric symptoms. Of the reported patients, only 22 underwent IT15 gene testing with positive results. Conclusion: HD is a well-reported entity in Chinese medical literature, however, only a small number of instances have been proven by molecular diagnosis. Most of the features resemble what is known in other countries. The highly predominant motor presentation, and the higher male prevalence as well as the apparent concentration in Northern China may be due to observational bias. There is therefore a need to prospectively examine cohorts of patients with appropriate comprehensive assessment tools including genetic testing