Employees Training and Development in Chinese State Owned Companies : Case:LQ Coal-Fired Power Plant

With the development of society, talents are more and more important to each field. The final competition of companies is the talents competition. In other words, talents become the core of organizations’ development. How to allocate HR reasonably is worth to study. However, HRM is in a developing stage in China. Most issues affect the development of HRM. Chinese state owned companies are the typical representatives for studying the development of HRM in China. Training and development is the indispensable part of HRM. This study is to use induct interview method to find out the existing issues of training and development in Chinese state owned subsidiaries. The case company LQ Coal-Fired Power Plant is a third level subsidiary of a global top 500 company that is named China Huaneng Group. By analyzing the data that is collected from the case company, the main issues of training and development in the case company are found

Predict-then-Calibrate: A New Perspective of Robust Contextual LP

Contextual optimization, also known as predict-then-optimize or prescriptive analytics, considers an optimization problem with the presence of covariates (context or side information). The goal is to learn a prediction model (from the training data) that predicts the objective function from the covariates, and then in the test phase, solve the optimization problem with the covariates but without the observation of the objective function. In this paper, we consider a risk-sensitive version of the problem and propose a generic algorithm design paradigm called predict-then-calibrate. The idea is to first develop a prediction model without concern for the downstream risk profile or robustness guarantee, and then utilize calibration (or recalibration) methods to quantify the uncertainty of the prediction. While the existing methods suffer from either a restricted choice of the prediction model or strong assumptions on the underlying data, we show the disentangling of the prediction model and the calibration/uncertainty quantification has several advantages. First, it imposes no restriction on the prediction model and thus fully unleashes the potential of off-the-shelf machine learning methods. Second, the derivation of the risk and robustness guarantee can be made independent of the choice of the prediction model through a data-splitting idea. Third, our paradigm of predict-then-calibrate applies to both (risk-sensitive) robust and (risk-neutral) distributionally robust optimization (DRO) formulations. Theoretically, it gives new generalization bounds for the contextual LP problem and sheds light on the existing results of DRO for contextual LP. Numerical experiments further reinforce the advantage of the predict-then-calibrate paradigm in that an improvement on either the prediction model or the calibration model will lead to a better final performance.Comment: 30 pages, 8 figure

Acid Sphingomyelinase Regulates the Localization and Trafficking of Palmitoylated Proteins

In human, loss of Acid Sphingomeylinase (ASM/SMPD1) causes Niemann-Pick Disease, type A. ASM hydrolyzes sphingomyelins to produce ceramides but protein targets of ASM remain largely unclear. ... See full text for complete abstract

Analyzing the Hardware-Software Implications of Multi-modal DNN Workloads using MMBench

The explosive growth of various types of big data and advances in AI technologies have catalyzed a new type of applications called multi-modal DNNs. Multi-modal DNNs are capable of interpreting and reasoning about information from multiple modalities, making them more applicable to real-world AI scenarios. In recent research, multi-modal DNNs have outperformed the best uni-modal DNN in a wide range of applications from traditional multimedia to emerging autonomous systems. However, despite their importance and superiority, very limited research attention has been devoted to understand the characteristics of multi-modal DNNs and their implications on current computing software/hardware platforms. To facilitate research and advance the understanding of these multi-modal DNN workloads, we first present MMbench, an open-source benchmark suite consisting of a set of real-world multi-modal DNN workloads with relevant performance metrics for evaluation. Then we use MMbench to conduct an in-depth analysis on the characteristics of multi-modal DNNs. We study their implications on application and programming framework, operating and scheduling system, as well as execution hardware. Finally, we conduct a case study and extend our benchmark to edge devices. We hope that our work can provide guidance for future software/hardware design and optimization to underpin multi-modal DNNs on both cloud and edge computing platforms

Genome and pan-genome assembly of asparagus bean (Vigna unguiculata ssp. sesquipedialis) reveal the genetic basis of cold adaptation

Asparagus bean (Vigna unguiculata ssp. sesquipedialis) is an important cowpea subspecies. We assembled the genomes of Ningjiang 3 (NJ, 550.31 Mb) and Dubai bean (DB, 564.12 Mb) for comparative genomics analysis. The whole-genome duplication events of DB and NJ occurred at 64.55 and 64.81 Mya, respectively, while the divergence between soybean and Vigna occurred in the Paleogene period. NJ genes underwent positive selection and amplification in response to temperature and abiotic stress. In species-specific gene families, NJ is mainly enriched in response to abiotic stress, while DB is primarily enriched in respiration and photosynthesis. We established the pan-genomes of four accessions (NJ, DB, IT97K-499-35 and Xiabao II) and identified 20,336 (70.5%) core genes present in all the accessions, 6,507 (55.56%) variable genes in two individuals, and 2,004 (6.95%) unique genes. The final pan genome is 616.35 Mb, and the core genome is 399.78 Mb. The variable genes are manifested mainly in stress response functions, ABC transporters, seed storage, and dormancy control. In the pan-genome sequence variation analysis, genes affected by presence/absence variants were enriched in biological processes associated with defense responses, immune system processes, signal transduction, and agronomic traits. The results of the present study provide genetic data that could facilitate efficient asparagus bean genetic improvement, especially in producing cold-adapted asparagus bean

Disruption of splicing-regulatory elements using CRISPR/Cas9 to rescue spinal muscular atrophy in human iPSCs and mice

We here report a genome-editing strategy to correct spinal muscular atrophy (SMA). Rather than directly targeting the pathogenic exonic mutations, our strategy employed Cas9 and guide-sgRNA for the targeted disruption of intronic splicing-regulatory elements. We disrupted intronic splicing silencers (ISSs, including ISS-N1 and ISS + 100) of survival motor neuron (SMN) 2, a key modifier gene of SMA, to enhance exon 7 inclusion and full-length SMN expression in SMA iPSCs. Survival of splicing-corrected iPSC-derived motor neurons was rescued with SMN restoration. Furthermore, co-injection of Cas9 mRNA from Streptococcus pyogenes (SpCas9) or Cas9 from Staphylococcus aureus (SaCas9) alongside their corresponding sgRNAs targeting ISS-N1 into zygotes rescued 56% and 100% of severe SMA transgenic mice (Smn , SMN2 ). The median survival of the resulting mice was extended to >400 days. Collectively, our study provides proof-of-principle for a new strategy to therapeutically intervene in SMA and other RNA-splicing-related diseases. -/- tg/

Methylprednisolone as Adjunct to Endovascular Thrombectomy for Large-Vessel Occlusion Stroke

Importance It is uncertain whether intravenous methylprednisolone improves outcomes for patients with acute ischemic stroke due to large-vessel occlusion (LVO) undergoing endovascular thrombectomy. Objective To assess the efficacy and adverse events of adjunctive intravenous low-dose methylprednisolone to endovascular thrombectomy for acute ischemic stroke secondary to LVO. Design, Setting, and Participants This investigator-initiated, randomized, double-blind, placebo-controlled trial was implemented at 82 hospitals in China, enrolling 1680 patients with stroke and proximal intracranial LVO presenting within 24 hours of time last known to be well. Recruitment took place between February 9, 2022, and June 30, 2023, with a final follow-up on September 30, 2023.InterventionsEligible patients were randomly assigned to intravenous methylprednisolone (n = 839) at 2 mg/kg/d or placebo (n = 841) for 3 days adjunctive to endovascular thrombectomy. Main Outcomes and Measures The primary efficacy outcome was disability level at 90 days as measured by the overall distribution of the modified Rankin Scale scores (range, 0 [no symptoms] to 6 [death]). The primary safety outcomes included mortality at 90 days and the incidence of symptomatic intracranial hemorrhage within 48 hours. Results Among 1680 patients randomized (median age, 69 years; 727 female [43.3%]), 1673 (99.6%) completed the trial. The median 90-day modified Rankin Scale score was 3 (IQR, 1-5) in the methylprednisolone group vs 3 (IQR, 1-6) in the placebo group (adjusted generalized odds ratio for a lower level of disability, 1.10 [95% CI, 0.96-1.25]; P = .17). In the methylprednisolone group, there was a lower mortality rate (23.2% vs 28.5%; adjusted risk ratio, 0.84 [95% CI, 0.71-0.98]; P = .03) and a lower rate of symptomatic intracranial hemorrhage (8.6% vs 11.7%; adjusted risk ratio, 0.74 [95% CI, 0.55-0.99]; P = .04) compared with placebo. Conclusions and Relevance Among patients with acute ischemic stroke due to LVO undergoing endovascular thrombectomy, adjunctive methylprednisolone added to endovascular thrombectomy did not significantly improve the degree of overall disability.Trial RegistrationChiCTR.org.cn Identifier: ChiCTR210005172