The Measurement of Strategic Human Capital and Value Creation－A case study of Smartphone Manufacturer

人力資本的衡量，為智慧資本領域中相當重要的一環。但過往的研究與討論，卻都陷入「靜態」與「歷史」資料的分析，對於企業在管理與決策時，並無法提供適時、適當且適切之資訊。本研究利用動態競爭分析之概念，改善人力資本資訊在使用上不足之處，並據以建立預測企業未來發展及表現的衡量基礎。 本研究採個案研究法，以我國智慧型手機製造企業為研究對象，利用公開資訊的蒐集與分析，探討其發展過程中有關策略性人力資本的變動，衡量個案公司在投入面、管理面及產出面之智慧資本，並與顧客資本及創新資本相結合，同步利用量化及質化之方式對策略性人力資本之衡量與其所創造之價值進行分析，進而做出下列結論： 一、策略將嚴重影響企業人力資本的內涵與價值。 二、策略執行的效度與效率會因管理階層對策略之決心與態度而有差異。 三、組織中團隊功能異質性的提升，有助於企業發展創新策略。 四、組織中團隊教育背景異質性的下降，有於助企業集中資源，聚焦策略，並增加產品發展及技術創新之強度。The measurement of human capital is always a crucial part of intellectual capital issue. However, researchs and discussions both are focus on the “static” and “historical” data analysis in the past. It is bounded to provide timely, appropriate information to assist management formulating strategy and making decisions. This study is aim to improve the weakness of statistical human capital’s information and establish the forward-looking forecasting scheme to measure enterprise’s performance. This study select one smartphone manufacturer in Taiwan as an sample, by adopting the method of case study, we collect public information and deeply analyze the various factors about strategic human capital, including the heterogeneity of team member by functional attributes and by educational disciplines. We integrate strategic human capital data with customer capital and innovation capital, measure enterprise’s performance in input, management and output aspects both in quantitative and qualitative method simultaneously, and create the value of combination with these intellectual capitals. Then make the following conclusions: First, the strategy always will seriously affect the meaning and value of human capital. Second, the determination and attitude of management will influence the validity and efficiency of strategy. Third, the higher heterogeneity of team member in functional attributes has positive help when developing innovative strategies. Fourth, the lower heterogeneity of team member in educational disciplines has positive help to centralize business resources, focus on specific strategy, and increase the strength of product development and technology innovation

基于“形色APP”筛选广州中心城区致敏花粉植物

目的调查广州中心城区致敏花粉植物的分布情况，为防治季节性过敏性鼻炎（花粉症）和合理的城市绿化建设提供科学的依据。方法使用“形色APP”识别广州中心城区内13个调查区域的植物，筛选出调查区域内可产生致敏花粉的植物。结果共计发现102个科，265个属，311个种植物，有38个属的植物为可产生致敏花粉植物，占比为14.3%；其中，广州本土植物为20个（52.6%），非广州本土植物为18种（47.4%），非本土致敏花粉植物种类将近达广州城区致敏花粉植物种类总数的一半，且每一个属的非本土致敏花粉植物分布密度大于本土致敏花粉植物的。禾本科分布最广，全部调查地点皆可见，发现率为100%，禾本科下分属的致敏花粉植物最多，为6种（15.8%），分别为狗牙根属、稗属、狗尾草属、狼尾草属、芦苇属和马唐属。11个调查地点可见杧果属和羊蹄甲属，发现率为84.6%。结论广州市中心城区出现了不合理的城市绿化的现象，栽植了不少致敏花粉植物，有38个属（14.3%）的植物属于可产生致敏花粉的植物，本土（52.6%）与非本土（47.4%）致敏花粉植物将近各占一半，从源头上增加了气传致敏花粉的种类和数量，可能会导致花粉症的发病风险上升。城市绿化规划时，应减少致敏花粉植物的栽植

Determination of the number of ψ(3686) events taken at BESIII

The number of ψ(3686) events collected by the BESIII detector during the 2021 run period is determined to be (2259.3±11.1)×106 by counting inclusive ψ(3686) hadronic events. The uncertainty is systematic and the statistical uncertainty is negligible. Meanwhile, the numbers of ψ(3686) events collected during the 2009 and 2012 run periods are updated to be (107.7±0.6)×106 and (345.4±2.6)×106, respectively. Both numbers are consistent with the previous measurements within one standard deviation. The total number of ψ(3686) events in the three data samples is (2712.4±14.3)×10^

Measurement of integrated luminosity of data collected at 3.773 GeV by BESIII from 2021 to 2024

We present a measurement of the integrated luminosity e+e- of collision data collected by the BESIII detector at the BEPCII collider at a center-of-mass energy of Ecm = 3.773 GeV. The integrated luminosities of the datasets taken from December 2021 to June 2022, from November 2022 to June 2023, and from October 2023 to February 2024 were determined to be 4.995±0.019 fb-1, 8.157±0.031 fb-1, and 4.191±0.016 fb-1, respectively, by analyzing large angle Bhabha scattering events. The uncertainties are dominated by systematic effects, and the statistical uncertainties are negligible. Our results provide essential input for future analyses and precision measurements

Prediction of Energy Resolution in the JUNO Experiment

International audienceThis paper presents the energy resolution study in the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The study reveals an energy resolution of 2.95% at 1 MeV. Furthermore, the study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data taking. Moreover, it provides a guideline in comprehending the energy resolution characteristics of liquid scintillator-based detectors

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel