A theoretical model for predicting Schottky-barrier height of the nanostructured silicide-silicon junction

ABSTRACT In this work, we have performed the first-principles calculations to investigate the Schottky barrier height (SBH) of various nanostructured silicide-silicon junctions. As for the silicides, PtSi, NiSi, TiSi2, and YSi2 have been used. We find that EFiF = EFi – EF, where EFi and EF are the intrinsic Fermi level of the semiconductor part and the Fermi level of the junction, respectively, is unchanged by nanostructuring. From this finding, we suggest a model, a symmetric increase of the SBH (SI) model, to properly predict SBHs of nanostructured silicide-silicon junctions. We also suggest two measurable quantities for the experimental validation of our model. The effect of our SI model applied to nanostructures such as nanowires and ultra-thin-bodies is compared with that of the widely used previous SBH model

Genetic Algorithm for Job Scheduling with Maintenance Consideration in Semiconductor Manufacturing Process

This paper presents wafer sequencing problems considering perceived chamber conditions and maintenance activities in a single cluster tool through the simulation-based optimization method. We develop optimization methods which would lead to the best wafer release policy in the chamber tool to maximize the overall yield of the wafers in semiconductor manufacturing system. Since chamber degradation will jeopardize wafer yields, chamber maintenance is taken into account for the wafer sequence decision-making process. Furthermore, genetic algorithm is modified for solving the scheduling problems in this paper. As results, it has been shown that job scheduling has to be managed based on the chamber degradation condition and maintenance activities to maximize overall wafer yield.open

The relationship of ovarian endometrioma and its size to the preoperative serum anti-Mullerian hormone level

Objectives: The aim of this study is to evaluate the impact of ovarian endometrioma according to its size on the serumanti-Mullerian hormone (AMH) levels compared to that of other benign ovarian cysts.Material and methods: The current study retrospectively evaluated preoperative serum AMH level and its association to presentingovarian cyst size which were measured in clinical setting. Women with surgically diagnosed endometrioma or other benignovarian cysts were included. All patients underwent transvaginal or transrectal ultrasonography to determine the size of theovarian cysts. Preoperative serum AMH level was checked and evaluated according to histologic type of the cyst, which wereendometrioma or other benign ovarian cysts, respectively. Both groups were classified into ≤ 4 cm, > 4 cm and ≤ 8 cm, > 8 cmand ≤ 12 cm, > 12 cm according to the diameter of cyst and analyzed the difference of mean AMH levels in both groups.Results: There was no significant difference in preoperative serum AMH level between the two groups (3.36 ± 2.3 versus3.76 ± 2.64, p = 0.331). The difference of preoperative AMH levels according to categorized cyst size also was not statisticallysignificant in both groups.Conclusions: Preoperative serum AMH levels were not statistically different between endometrioma and other benignovarian cyst groups and were not related to the size of endometrioma

Risk factors related to the recurrence of endometrioma in patients with long-term postoperative medical therapy

Objectives: The purpose of this study was to identify clinical risk factors for the recurrence of ovarian endometrioma after ovarian cystectomy in Korean women with long-term postoperative medical therapy.Material and Methods: A total of 134 patients who were surgically treated for endometriotic cysts at Pusan National University Hospital were included in this retrospective study. All patients received long-term postoperative medical treatment for at least 12 months after the first-line conservative surgery. Several epidemiologic variables were analyzed as possible risk factors for recurrence. Endometrioma recurrence was considered when a cystic mass was observed on transvaginal or transrectal sonography. Statistical analysis was performed using independent t-tests for parametric continuous variables.Results: The mean follow-up period for the 134 patients was 56.5 ± 14.3 months (range, 36–120 months) and the mean duration of the medical therapy was 17.9 ± 17.3 months (range, 12–120 months). The overall recurrence rate was 35/134 (26.12%). Our univariate analysis showed statistically significant differences between the recurrent and non-recurrent groups in terms of weight (P = 0.013), body mass index (P = 0.007), age at the time of surgery (P = 0.013), the diameter of the largest cyst (P = 0.001), the presence of dysmenorrhea (P < 0.0001), and postoperative pregnancy (P = 0.016). Multivariate analysis showed that body mass index (OR 1.153, 95% CI 1.003–1.326, P = 0.046), age at the time of surgery (OR 0.924, 95% CI 0.860–0.992, P = 0.029), and presence of dysmenorrhea (OR 12.226, 95% CI 3.543–42.188, P < 0.0001) were significantly correlated with the recurrence of endometrioma.Conclusions: We found that patients with dysmenorrhea after surgery, and a younger age of the patient at the time of surgery were the highest risk factors associated with the recurrence of endometrioma, despite long-term postoperative medication

PADA: Power-aware development assistant for mobile sensing applications

� 2016 ACM. We propose PADA, a new power evaluation tool to measure and optimize power use of mobile sensing applications. Our motivational study with 53 professional developers shows they face huge challenges in meeting power requirements. The key challenges are from the significant time and effort for repetitive power measurements since the power use of sensing applications needs to be evaluated under various real-world usage scenarios and sensing parameters. PADA enables developers to obtain enriched power information under diverse usage scenarios in development environments without deploying and testing applications on real phones in real-life situations. We conducted two user studies with 19 developers to evaluate the usability of PADA. We show that developers benefit from using PADA in the implementation and power tuning of mobile sensing applications.N

Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals

Vibration measurement and monitoring are essential in a wide variety of applications. Vibration measurements are critical for diagnosing industrial machinery malfunctions because they provide information about the condition of the rotating equipment. Vibration analysis is considered the most effective method for predictive maintenance because it is used to troubleshoot instantaneous faults as well as periodic maintenance. Numerous studies conducted in this vein have been published in a variety of outlets. This review documents data-driven and recently published deep learning techniques for vibration-based condition monitoring. Numerous studies were obtained from two reputable indexing databases, Web of Science and Scopus. Following a thorough review, 59 studies were selected for synthesis. The selected studies are then systematically discussed to provide researchers with an in-depth view of deep learning-based fault diagnosis methods based on vibration signals. Additionally, a few remarks regarding future research directions are made, including graph-based neural networks, physics-informed ML, and a transformer convolutional network-based fault diagnosis method

Root avoidance of toxic metals requires the GeBP-LIKE 4 transcription factor in Arabidopsis thaliana

Plants reorganize their root architecture to avoid growth into unfavorable regions of the rhizosphere. In a screen based on chimeric repressor gene-silencing technology, we identified the Arabidopsis thaliana GeBP-LIKE 4 (GPL4) transcription factor as an inhibitor of root growth that is induced rapidly in root tips in response to cadmium (Cd). We tested the hypothesis that GPL4 functions in the root avoidance of Cd by analyzing root proliferation in split medium, in which only half of the medium contained toxic concentrations of Cd. The wild-type (WT) plants exhibited root avoidance by inhibiting root growth in the Cd side but increasing root biomass in the control side. By contrast, GPL4-suppression lines exhibited nearly comparable root growth in the Cd and control sides and accumulated more Cd in the shoots than did the WT. GPL4 suppression also altered the root avoidance of toxic concentrations of other essential metals, modulated the expression of many genes related to oxidative stress, and consistently decreased reactive oxygen species concentrations. We suggest that GPL4 inhibits the growth of roots exposed to toxic metals by modulating reactive oxygen species concentrations, thereby allowing roots to colonize noncontaminated regions of the rhizosphere.117Ysciescopu

Sandra Helps You Learn: The More You Walk, The More Battery Your Phone Drains

Emerging continuous sensing apps introduce new major factors governing phones' overall battery consumption behaviors: (1) added nontrivial persistent battery drain, and more importantly (2) different battery drain rate depending on the user's different mobility condition. In this paper, we address the new battery impacting factors significant enough to outdate users' existing battery model in real life. We explore an initial approach to help users understand the cause and effect between their physical activity and phones' battery life. To this end, we present Sandra, a novel mobility-aware smartphone battery information advisor, and study its potential to help users redevelop their battery model. We perform an extensive explorative study and deployment for 30 days with 24 users. Our findings reveal what they essentially learned, and in which situations they found Sandra very helpful. We share the lessons learned to help in the design of future mobility-aware battery advisors.1

HIGH CROSSOVER RATE1 encodes PROTEIN PHOSPHATASE X1 and restricts meiotic crossovers in Arabidopsis.

Meiotic crossovers are tightly restricted in most eukaryotes, despite an excess of initiating DNA double-strand breaks. The majority of plant crossovers are dependent on class I interfering repair, with a minority formed via the class II pathway. Class II repair is limited by anti-recombination pathways; however, similar pathways repressing class I crossovers have not been identified. Here, we performed a forward genetic screen in Arabidopsis using fluorescent crossover reporters to identify mutants with increased or decreased recombination frequency. We identified HIGH CROSSOVER RATE1 (HCR1) as repressing crossovers and encoding PROTEIN PHOSPHATASE X1. Genome-wide analysis showed that hcr1 crossovers are increased in the distal chromosome arms. MLH1 foci significantly increase in hcr1 and crossover interference decreases, demonstrating an effect on class I repair. Consistently, yeast two-hybrid and in planta assays show interaction between HCR1 and class I proteins, including HEI10, PTD, MSH5 and MLH1. We propose that HCR1 plays a major role in opposition to pro-recombination kinases to restrict crossovers in Arabidopsis.Marie Curie International Training Network COMREC European Research Council (ERC) National Research Foundation of Korea Suh Kyungbae Foundatio