Out-Of-Band Management on UEFI System Firmware

The modern Redfish is a specification that utilize RESTful interface semantics to access data defined in model format to perform out-of-band (OOB) management through specific OOB software or hardware (such as Baseboard Management Controller, BMC). The OOB management allow users to configure system remotely when the system is in either power-off or power-on state. Industry can expect there are more and more pre-boot firmware drivers (like UEFI drivers) and system peripherals (such as PCI devices, PCI add-on-card and so on) support Redfish Schema/Configuration data model in the near future. This article describes the method to abstract the data communication/synchronization between UEFI drivers and OOB management on UEFI firmware environment. Furthermore, this article is not only restricted to single OOB management on system, the abstracts method described in this article is flexible and extensible to support multiple OOB management instances on one system simultaneously. Not only Redfish OOB management data model is supported, this article fulfills the requirements of any other data model of OOB managements such as OData XML/JSON data model, CIM-XML data model, 3rd party data model and etc

Constrained K-means and Genetic Algorithm-based Approaches for Optimal Placement of Wireless Structural Health Monitoring Sensors

Optimal placement of wireless structural health monitoring (SHM) sensors has to consider modal identification accuracy and power efficiency. In this study, two-tier wireless sensor network (WSN)-based SHM systems with clusters of sensors are investigated to overcome this difficulty. Each cluster contains a number of sensor nodes and a cluster head (CH). The lower tier is composed of sensors communicating with their associated CHs, and the upper tier is composed of the network of CHs. The first step is the optimal placement of sensors in the lower tier via the effective independence method by considering the modal identification accuracy. The second step is the optimal placement of CHs in the upper tier by considering power efficiency. The sensors in the lower tier are partitioned into clusters before determining the optimal locations of CHs in the upper tier. Two approaches, a constrained K-means clustering approach and a genetic algorithm (GA)-based clustering approach, are proposed in this study to cluster sensors in the lower tier by considering two constraints: (1) the maximum data transmission distance of each sensor; (2) the maximum number of sensors in each cluster. Given that each CH can only manage a limited number of sensors, these constraints should be considered in practice to avoid overload of CHs. The CHs in the upper tier are located at the centers of the clusters determined after clustering sensors in the lower tier. The two proposed approaches aim to construct a balanced size of clusters by minimizing the number of clusters (or CHs) and the total sum of the squared distance between each sensor and its associated CH under the two constraints. Accordingly, the energy consumption in each cluster is decreased and balanced, and the network lifetime is extended. A numerical example is studied to demonstrate the feasibility of using the two proposed clustering approaches for sensor clustering in WSN-based SHM systems. In this example, the performances of the two proposed clustering approaches and the K-means clustering method are also compared. The two proposed clustering approaches outperform the K-means clustering method in terms of constructing balanced size of clusters for a small number of clusters. Doi: 10.28991/CEJ-2022-08-12-01 Full Text: PD

AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks

Transformer-based pre-trained models with millions of parameters require large storage. Recent approaches tackle this shortcoming by training adapters, but these approaches still require a relatively large number of parameters. In this study, AdapterBias, a surprisingly simple yet effective adapter architecture, is proposed. AdapterBias adds a token-dependent shift to the hidden output of transformer layers to adapt to downstream tasks with only a vector and a linear layer. Extensive experiments are conducted to demonstrate the effectiveness of AdapterBias. The experiments show that our proposed method can dramatically reduce the trainable parameters compared to the previous works with a minimal decrease in task performances compared with fine-tuned pre-trained models. We further find that AdapterBias automatically learns to assign more significant representation shifts to the tokens related to the task in consideration.Comment: The first two authors contributed equally. This paper was published in Findings of NAACL 202

Well-differentiated gall bladder hepatoid carcinoma producing alpha-fetoprotein: a case report

<p>Abstract</p> <p>Introduction</p> <p>Gall bladder carcinoma is rare, and metastatic gall bladder carcinoma from hepatocellular carcinoma has been reported in only a few patients.</p> <p>Case presentation</p> <p>We present a 73-year-old man with a history of hepatitis B virus-related liver cirrhosis and hepatocellular carcinoma. He received transcatheter arterial chemoembolization, and was diagnosed to have an alpha-fetoprotein producing gall bladder tumor with intraluminal growth. Open cholecystectomy was performed. Pathologic examination of the lesion revealed a well-differentiated hepatoid carcinoma. The lesion was thought most likely to be a metastatic lesion from previous hepatocellular carcinoma. His alpha-fetoprotein level dropped to normal levels five months after the surgery.</p> <p>Conclusion</p> <p>This unusual intraluminal growing tumor proved to be a well-differentiated hepatoid carcinoma, most likely a metastatic lesion from previous hepatocellular carcinoma. This case reminds clinicians that in looking for likely hepatocellular carcinoma recurrence, when no detectable hepatic lesion can account for an elevated alpha-fetoprotein level, the gall bladder should be included in the search for the site of metastasis.</p

Immune reconstitution inflammatory syndrome of Kaposi’s sarcoma in an HIV-infected patient

We present a case of Kaposi’s sarcoma-related immune reconstitution inflammatory syndrome in an HIV-infected patient who developed fever, worsening pulmonary infiltrates with respiratory distress, and progression of skin tumors at the popliteal region and thigh that resulted in limitation on movement of the right knee joint at 3.5 months following a significant increase of CD4 count after combination antiretroviral therapy

A reduced risk of stroke with lithium exposure in bipolar disorder: a population‐based retrospective cohort study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115969/1/bdi12336.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/115969/2/bdi12336_am.pd

Combined Application Therapies of Stem Cells and Drugs in the Neurological Disorder Attenuation

Neurological disorders (NDs) are diseases of the central and peripheral nervous system that affected the hundreds of millions of people worldwide. Temporal lobe epilepsy (TLE) is a common NDs with hallucinations and disturbance of consciousness that cause the abnormal neurological activity in any part of brain. Neuroinflammation (NI) has been identified in epilepsy-related tissue from both experimental and clinical evidence and suspected to participate in the formation of neuronal cell death, reactive gliosis and neuroplastic changes in the hippocampus, may contribute to epileptogenesis. The NI is tightly regulated by microglia, but it is thought that excessive or chronic microglial activation can contribute to neurodegenerative processes. Therefore, the modulation of microglia responses may provide a therapeutic target for the treatment of severe or chronic NI conditions. Although the condition responds well to antiepileptic drugs (AEDs), there are still unresponsive to AEDs in about 1/3 of cases. Neural stem cells are the origin of various types of neural cells during embryonic development. Currently, many results of stem cell therapies in the animal experiments and clinical trials were demonstrated the efficacious therapeutic effects in the attenuated symptoms of ND. Therefore, the combined application therapies of stem cells and drugs may be a promising candidate for the therapeutic strategies of NDs, especially TLE