Employee Retention in Chinese SMEs: a case study of a retail pharmacy

With the increasing number of small and medium-sized enterprises (SMEs) in China, the problem of how to decrease the turnover rate and remain more employees are becoming a crucial problem. The purpose of this dissertation is to explore the main factors affect employee retention and turnover intention in Chinese SMEs, and analyse some aspects can improve employee retention. Finally， there is a discussion to explore the especial influence of Chinese national culture on employees’ retention and turnover intention in SMEs. To achieve the research objective, this dissertation was designed as a case study in a retail chain pharmacy – TLT pharmacy which with over ten branches in the area. A closed-ended questionnaire was conducted, and the secondary data was collected to accomplish the results of the questionnaire. 118 employees in TLT pharmacy was randomly selected as the respondents for quantitative research. The results of the research demonstrated that the five factors that compensation and rewards; job satisfaction; learning, training and promotion opportunities; relationship with managers and co-workers are positively related to employee retention. It is also suggested what aspects the company need to improve to retain employees. In the end, this research demonstrated that Chinese national culture influenced Chinese SMEs as an important and special factor

A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Time

Large language models (LLMs) have played a pivotal role in revolutionizing various facets of our daily existence. Solving attention regression is a fundamental task in optimizing LLMs. In this work, we focus on giving a provable guarantee for the one-layer attention network objective function $L(X,Y) = \sum_{j_0 = 1}^n \sum_{i_0 = 1}^d ( \langle \langle \exp( \mathsf{A}_{j_0} x ) , {\bf 1}_n \rangle^{-1} \exp( \mathsf{A}_{j_0} x ), A_{3} Y_{*,i_0} \rangle - b_{j_0,i_0} )^2$. Here $\mathsf{A} \in \mathbb{R}^{n^2 \times d^2}$ is Kronecker product between $A_1 \in \mathbb{R}^{n \times d}$ and $A_2 \in \mathbb{R}^{n \times d}$. $A_3$ is a matrix in $\mathbb{R}^{n \times d}$, $\mathsf{A}_{j_0} \in \mathbb{R}^{n \times d^2}$ is the $j_0$-th block of $\mathsf{A}$. The $X, Y \in \mathbb{R}^{d \times d}$ are variables we want to learn. $B \in \mathbb{R}^{n \times d}$ and $b_{j_0,i_0} \in \mathbb{R}$ is one entry at $j_0$-th row and $i_0$-th column of $B$, $Y_{*,i_0} \in \mathbb{R}^d$ is the $i_0$-column vector of $Y$, and $x \in \mathbb{R}^{d^2}$ is the vectorization of $X$. In a multi-layer LLM network, the matrix $B \in \mathbb{R}^{n \times d}$ can be viewed as the output of a layer, and $A_1= A_2 = A_3 \in \mathbb{R}^{n \times d}$ can be viewed as the input of a layer. The matrix version of $x$ can be viewed as $QK^\top$ and $Y$ can be viewed as $V$. We provide an iterative greedy algorithm to train loss function $L(X,Y)$ up $\epsilon$ that runs in $\widetilde{O}( ({\cal T}_{\mathrm{mat}}(n,n,d) + {\cal T}_{\mathrm{mat}}(n,d,d) + d^{2\omega}) \log(1/\epsilon) )$ time. Here ${\cal T}_{\mathrm{mat}}(a,b,c)$ denotes the time of multiplying $a \times b$ matrix another $b \times c$ matrix, and $\omega\approx 2.37$ denotes the exponent of matrix multiplication

GridMM: Grid Memory Map for Vision-and-Language Navigation

Vision-and-language navigation (VLN) enables the agent to navigate to a remote location following the natural language instruction in 3D environments. To represent the previously visited environment, most approaches for VLN implement memory using recurrent states, topological maps, or top-down semantic maps. In contrast to these approaches, we build the top-down egocentric and dynamically growing Grid Memory Map (i.e., GridMM) to structure the visited environment. From a global perspective, historical observations are projected into a unified grid map in a top-down view, which can better represent the spatial relations of the environment. From a local perspective, we further propose an instruction relevance aggregation method to capture fine-grained visual clues in each grid region. Extensive experiments are conducted on both the REVERIE, R2R, SOON datasets in the discrete environments, and the R2R-CE dataset in the continuous environments, showing the superiority of our proposed method

Efficacy of Qigong Exercise for Treatment of Fatigue: A Systematic Review and Meta-Analysis

Objective: Several studies suggested that Qigong exercise (QE) can relieve fatigue in patients diagnosed with various diseases. Our review aimed to evaluate the efficacy of QE for alleviating fatigue.Methods: A related literature search was performed in the PubMed, Web of Science, Embase, Cochrane Library, China Biology Medicine disc (CBM), China National Knowledge Infrastructure (CNKI), Wanfang, and VIP data bases from inception to November 2020. Information on fatigue, malaise, tiredness, and Qigong research data was collected.Results: Sixteen randomized controlled trials (RCTs) were reported in patients with cancer (n = 4), chronic fatigue syndrome (n = 2), and other diseases (n = 10). The QE groups showed significant improvements in total fatigue intensity [15 RCTs, p < 0.00001; standard mean difference (SMD) −0.69 (−0.95 to −0.44)]. The QE groups did not show significant improvement in quality of life [4 RCTs, p = 0.08; SMD 0.53 (−0.07 to 1.14)]. The statistically significant difference of the subgroup analyses (different primary diseases, QE types, and study quality) also remained unchanged.Conclusion: The findings of this meta-analysis indicate that QE may be beneficial for improving fatigue in patients diagnosed with various diseases. Considering the limitations of the study, we draw a very cautious conclusion regarding the resulting estimate of the effect. Further studies are warranted to better understand the benefits of QE in primary medical care

On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving

The pursuit of autonomous driving technology hinges on the sophisticated integration of perception, decision-making, and control systems. Traditional approaches, both data-driven and rule-based, have been hindered by their inability to grasp the nuance of complex driving environments and the intentions of other road users. This has been a significant bottleneck, particularly in the development of common sense reasoning and nuanced scene understanding necessary for safe and reliable autonomous driving. The advent of Visual Language Models (VLM) represents a novel frontier in realizing fully autonomous vehicle driving. This report provides an exhaustive evaluation of the latest state-of-the-art VLM, GPT-4V(ision), and its application in autonomous driving scenarios. We explore the model's abilities to understand and reason about driving scenes, make decisions, and ultimately act in the capacity of a driver. Our comprehensive tests span from basic scene recognition to complex causal reasoning and real-time decision-making under varying conditions. Our findings reveal that GPT-4V demonstrates superior performance in scene understanding and causal reasoning compared to existing autonomous systems. It showcases the potential to handle out-of-distribution scenarios, recognize intentions, and make informed decisions in real driving contexts. However, challenges remain, particularly in direction discernment, traffic light recognition, vision grounding, and spatial reasoning tasks. These limitations underscore the need for further research and development. Project is now available on GitHub for interested parties to access and utilize: \url{https://github.com/PJLab-ADG/GPT4V-AD-Exploration

Clinicopathological characteristics of gastric cancer patients with dermatomyositis and analysis of perioperative management: a case series study

BackgroundThis study aimed to investigate the clinical characteristics of gastric cancer (GC) patients with dermatomyositis (DM) and summarize the perioperative outcomes.MethodsThe clinical and pathological data of five patients diagnosed with co-occurring DM and GC (DM-GC group) were retrospectively analyzed, who were admitted to the Department of Gastrointestinal Surgery at Ren ji Hospital, Shanghai Jiao Tong University, between January 2012 and April 2023. Their data were compared with 618 GC patients (GC-1 group) from September 2016 to August 2017 and 35 GC patients who were meticulously screened from 14,580 GC cases from January 2012 and April 2023. The matching criteria included identical gender, age, tumor location, TNM stage, and surgical procedure (7 GC patients were matched for each DM-GC patient).ResultsAnalysis indicated that the DM-GC group comprised four female and one male patient. The female proportion was significantly higher (P = 0.032) than that of GC-1 group. In DM-GC group, four DM patients were diagnosed as GC within 12 months. One DM patients was diagnosed as GC within 15 months. Among them, four patients presented with varying degrees of skin rashes, muscle weakness while one patient had elevated CK levels as the typical symptom. Similarly, the preoperative tumor markers (CA-199 and CA-125) in the DM-GC group were significantly higher than normal levels (CA-199: 100 vs. 28.6%, P = 0.002; CA-125: 40 vs. 2.9%, P = 0.003) compared to GC-2 group. Moreover, postoperative complication incidence and the length of hospital stay were significantly higher in the DM-GC than GC-2 group [complication rate: 40 vs. 8.6%, P = 0.047; hospital stay: 15 days (range: 9–28) vs. 9 days (range: 8–10), P = 0.021].ConclusionGC Patients with dermatomyositis are more prone to experience postoperative complications and longer hospital stay

Employee Retention in Chinese SMEs: a case study of a retail pharmacy

With the increasing number of small and medium-sized enterprises (SMEs) in China, the problem of how to decrease the turnover rate and remain more employees are becoming a crucial problem. The purpose of this dissertation is to explore the main factors affect employee retention and turnover intention in Chinese SMEs, and analyse some aspects can improve employee retention. Finally， there is a discussion to explore the especial influence of Chinese national culture on employees’ retention and turnover intention in SMEs. To achieve the research objective, this dissertation was designed as a case study in a retail chain pharmacy – TLT pharmacy which with over ten branches in the area. A closed-ended questionnaire was conducted, and the secondary data was collected to accomplish the results of the questionnaire. 118 employees in TLT pharmacy was randomly selected as the respondents for quantitative research. The results of the research demonstrated that the five factors that compensation and rewards; job satisfaction; learning, training and promotion opportunities; relationship with managers and co-workers are positively related to employee retention. It is also suggested what aspects the company need to improve to retain employees. In the end, this research demonstrated that Chinese national culture influenced Chinese SMEs as an important and special factor

Review of Advanced Effusive Cooling for Gas Turbine Blades

Turbine inlet temperature has continuously increased to improve gas turbine performance during the past few decades. Although internal convection cooling and traditional film cooling have contributed significantly to the current achievement, advanced cooling schemes are needed to minimize the coolant consumption and maximize the cooling efficiency for future gas turbines. This paper conducts a comprehensive review of advanced effusive cooling schemes for gas turbine blades. First, the background and the history of turbine blade cooling are introduced. Then, the metrics of effusive cooling efficiency are defined. Next, effusion cooling, impingement/effusion cooling, and transpiration cooling are reviewed. The flow and heat transfer mechanisms of the cooling schemes are emphasized, and the design trends of the cooling schemes are revealed. Finally, the conclusions and future research perspectives are summarized