Increasing Power Density of LSGM-Based Solid Oxide Fuel Cells Using New Anode Materials

Chemical reactions between the superior perovskite oxide-ion conductor Sr- and Mg-doped LaGaO3 (LSGM), CeO2, and NiO have been studied by powder X-ray diffraction. The results showed that an extensive reactivity occurs as a result of La migration driven by a gradient of La chemical activity. La migration across the LSGM/electrode interfaces in a fuel cell leads to the formation of resistive phases at the interface, either LaSrGa3O7 or LaSrGaO4. Use of 40 mol % La2O3 -doped CeO2 as an interlayer between anode and electrolyte as well as in the NiO-containing anode prevents all reactions found. Consequently, the air-H2 cell maximum power density was increased to nearly 900 mW/cm2 at 800°C with a 600 μm thick LSGM electrolyte. No sign of degradation was observed at 800°C over 2 weeks for an interlayered cell under a loading current density of 250 mA/cm2

Lifetime Maximization for Amplify-and-Forward Cooperative Networks

[[abstract]]Power allocation strategies are devised to maximize the network lifetime of amplify-and-forward (AF) cooperative networks. We consider the scenario where one source and multiple partners cooperate to transmit messages to the destination. The powers emitted by the users are subject to the SNR requirement at the destination. First, the power allocation strategy that demands the minimum instantaneous aggregate transmit power of all cooperating partners is described and analyzed. The optimal solution results in a form of selective relaying; namely, the user with the best channel condition is selected to help in relaying the message. However, this instantaneous power minimization strategy does not necessarily maximize the lifetime of battery-limited systems. Then, we propose three AF cooperative schemes to exploit the channel state information (CSI), the residual battery energy and the QoS requirement. It is shown that the network lifetime can be extended considerably by taking all these three factors into account.[[fileno]]2030137030021[[department]]電機工程學

Discrete Power Allocation for Lifetime Maximization in Cooperative Networks

[[abstract]]Discrete power allocation strategies for amplifyand- forward cooperative networks are proposed based on selective relaying methods. The goal of power allocation is to maximize the network lifetime, which is defined as the duration of time for which the outage probability at the destination can be maintained above a certain level. The discrete power levels enable a low cost implementation and a close integration with high speed digital circuits. We propose three power allocation strategies that take into consideration both the channel state information (CSI) and the residual energy information (REI) at each node. By modeling the residual energy of each node as the states of a Markov Chain, we are able to derive the network lifetime analytically by the expected number of transitions to the absorbing states, i.e., the energy states for which the outage probability is no longer achievable. The performance of the three strategies are compared through numerical simulations and a significant improvement in network lifetime is shown, when compared with the case considering only the local CSI.[[fileno]]2030137030010[[department]]電機工程學

Experience with adjuvant chemotherapy for pseudomyxoma peritonei secondary to mucinous adenocarcinoma of the appendix with oxaliplatin/fluorouracil/leucovorin (FOLFOX4)

<p>Abstract</p> <p>Background</p> <p>Pseudomyxoma peritonei (PMP) is a rare condition characterized by mucinous tumors, disseminated intra-peritoneal implants, and mucinous ascites. So far its diagnosis remains challenging to most clinicians.</p> <p>Case presentation</p> <p>A 55-year-old male patient had suffered from acute onset of abdominal pain and abdominal distension for one day prior to his admission. Physical examination revealed tenderness over the right lower quadrant of the abdomen without diffuse muscle guarding. A large amount of ascites was identified by abdominal computed tomography (CT) scan. Paracentesis showed the appearance of sticky mucinous ascites. He underwent laparotomy under the impression of pseudomyxoma peritonei. There was a lot of mucinous ascites, one appendiceal tumor and multiple peritoneal implants disseminated from the subphrenic space to the recto-vesicle pouch. Pseudomyxoma Peritonei caused by mucinous adenocarcinoma of appendiceal origin, was confirmed by histopathology. We performed an excision of the appendiceal tumor combined with copious irrigation and debridement. After the operation, he received 10 cycles of systemic chemotherapy with FOLFOX4 regimen, without specific morbidity. Follow-up of abdominal CT and colonoscopy at post-operative 17 months showed excellent response without evidence of local recurrence or distal metastasis. He made an uneventful recovery (up to the present) for 21 months after the operation.</p> <p>Conclusion</p> <p>This case report emphasizes the possible new role of systemic chemotherapy in the treatment of patients with this rare clinical syndrome.</p

The mPEG-PCL Copolymer for Selective Fermentation of Staphylococcus lugdunensis Against Candida parapsilosis in the Human Microbiome.

Many human skin diseases, such as seborrheic dermatitis, potentially occur due to the over-growth of fungi. It remains a challenge to develop fungicides with a lower risk of generating resistant fungi and non-specifically killing commensal microbes. Our probiotic approaches using a selective fermentation initiator of skin commensal bacteria, fermentation metabolites or their derivatives provide novel therapeutics to rein in the over-growth of fungi. Staphylococcus lugdunensis (S. lugdunensis) bacteria and Candida parapsilosis (C. parapsilosis) fungi coexist in the scalp microbiome. S. lugdunensis interfered with the growth of C. parapsilosis via fermentation. A methoxy poly(ethylene glycol)-b-poly(ε-caprolactone) (mPEG-PCL) copolymer functioned as a selective fermentation initiator of S. lugdunensis, selectively triggering the S. lugdunensis fermentation to produce acetic and isovaleric acids. The acetic acid and its pro-drug diethyleneglycol diacetate (Ac-DEG-Ac) effectively suppressed the growth of C. parapsilosis in vitro and impeded the fungal expansion in the human dandruff. We demonstrate for the first time that S. lugdunensis is a skin probiotic bacterium that can exploit mPEG-PCL to yield fungicidal short-chain fatty acids (SCFAs). The concept of bacterial fermentation as a part of skin immunity to re-balance the dysbiotic microbiome warrants a novel avenue for studying the probiotic function of the skin microbiome in promoting health

Comparison of power control schemes for relay sensor networks

[[abstract]]Three power control schemes for the space-time coded amplify-and-forward (AF) relaying scheme targeting at wireless sensor network applications are examined and compared. The opportunistic scheme performs the best by considering the signal-to-noise-ratio (SNR) of the received signal. However, if the power for the relay is limited, the performance of the opportunistic scheme degrades due to the loss of active relay nodes that have better channel conditions. Since the battery lifetime of nodes for wireless sensor networks is limited and the loss of relay nodes is critical to system performance, we propose an SNR-constrained power reduction scheme to prolong the relay lifetime for the opportunistic scheme. It is demonstrated by computer simulation that the opportunistic scheme with SNR-constrained power reduction is power efficient and the relay lifetime of dense relay networks can be significantly prolonged. &copy; 2007 IEEE.[[fileno]]2030137030003[[department]]電機工程學

The development of the job satisfaction scale for hospital staff in Taiwan

The current study attempts to construct a valid and applicable job satisfaction scale for measuring the contentment level of hospital staff in Taiwan. The job description inventory (JDI) and Job Satisfaction Index (JSI) were adopted as the foundation of the job satisfaction measure for hospital staff in a selected hospital. To verify and validate the scale, data collected in 2012 and 2013, were analyzed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), respectively. Subsequently, Pearson correlations analysis was used to examine the strength and direction of the relationships between job satisfaction dimensions. Overall, the job satisfaction scale developed in this research illustrated valid and accurate measure for assessing hospital staffs' satisfaction. Both EFA and CFA results demonstrated that items consistently emerged six dimensions i.e. work environment, work achievement, compensation and benefits, education and training, promotion and evaluation, and management system. The findings also highlight that management support, work achievement, and promotion and evaluation are three critical factors that significantly contribute to high levels of job satisfaction for hospital staff

A & B == B & A: Triggering Logical Reasoning Failures in Large Language Models

Recent advancements in large language models (LLMs) have propelled Artificial Intelligence (AI) to new heights, enabling breakthroughs in various tasks such as writing assistance, code generation, and machine translation. A significant distinction of advanced LLMs, such as ChatGPT, is their demonstrated ability to "reason." However, evaluating the reasoning ability of LLMs remains a challenge as most existing evaluations focus on their accuracy on the downstream tasks rather than directly assessing their reasoning processes. Efforts have been made to develop benchmarks and metrics to assess reasoning in LLMs, but they suffer from data leakage or limited scope. In this paper, we introduce LogicAsker, an automatic approach that comprehensively evaluates and improves the logical reasoning abilities of LLMs under a set of atomic reasoning skills based on propositional and predicate logic. The results provide insights into LLMs' reasoning abilities and reveal the logical rules the LLMs did not learn well. We evaluate LogicAsker on six widely deployed LLMs, including GPT-3, ChatGPT, GPT-4, Bard, Vicuna, and Guanaco. The results show that test cases from LogicAsker can find logical reasoning failures in different LLMs with a rate of 25\% - 94\%. In addition, the test cases of LogicAsker can be further used to design demonstration examples for in-context learning, which effectively improves the logical reasoning ability of LLMs, e.g., 10\% for GPT-4. As far as we know, our work is the first to create prompts based on testing results to improve LLMs' formal reasoning ability effectively. All the code, data, and results will be released for reproduction and future research

Genome-Wide Gene-Environment Interaction Analysis Using Set-Based Association Tests

The identification of gene-environment interactions (G × E) may eventually guide health-related choices and medical interventions for complex diseases. More powerful methods must be developed to identify G × E. The “adaptive combination of Bayes factors method” (ADABF) has been proposed as a powerful genome-wide polygenic approach to detect G × E. In this work, we evaluate its performance when serving as a gene-based G × E test. We compare ADABF with six tests including the “Set-Based gene-EnviRonment InterAction test” (SBERIA), “gene-environment set association test” (GESAT), etc. With extensive simulations, SBERIA and ADABF are found to be more powerful than other G × E tests. However, SBERIA suffers from a power loss when 50% SNP main effects are in the same direction with the SNP × E interaction effects while 50% are in the opposite direction. We further applied these seven G × E methods to the Taiwan Biobank data to explore gene× alcohol interactions on blood pressure levels. The ADAMTS7P1 gene at chromosome 15q25.2 was detected to interact with alcohol consumption on diastolic blood pressure (p = 9.5 × 10−7, according to the GESAT test). At this gene, the P-values provided by other six tests all reached the suggestive significance level (p &lt; 5 × 10−5). Regarding the computation time required for a genome-wide G × E analysis, SBERIA is the fastest method, followed by ADABF. Considering the validity, power performance, robustness, and computation time, ADABF is recommended for genome-wide G × E analyses