Factors associated with job satisfaction among district hospital health workers in Northern Vietnam : a cross-sectional study

Background: In many developing countries, including Vietnam, little is known about job satisfaction among lower level-health staff. The purpose of this study was to assess job satisfaction and its determinants among district hospital health staff. Methods: In a cross-sectional quantitative study, 128 health staff from a rural district hospital in Northern Vietnam were approached for data collection. Regression techniques were adopted to assess factors associated with several types of job satisfaction. Results: Overall job satisfaction was moderately high, ranging from 69% to 91%. Across all dimensions, health workers showed their highest satisfaction with co-worker relationships, while, in comparison, it was much lower for their supervisor's style and relationship. However, they claimed their lowest satisfaction with compensation and benefits. In final multivariate models, females and those satisfied with knowledge, skills and job performance were most likely to be satisfied with relationships with co-workers. Staff who were married, received a low pay, who were not satisfied with supervisor style and relationships and who were not satisfied with staff training, development opportunities were least likely to be satisfied with compensation and benefits. Conclusions: The study findings highlight an important need for designing an intervention program that considers organizational factors. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd

Waverider, volume 2

The results of a study concerning a High-Speed Civilian Transport Aircraft are discussed. An evaluation of the viability of four configurations is presented. One design considered in the Waverider configuration. The Waverider creates lift at high speeds through the use of shock waves. This shocklift when combined with conventionally created lift provides high lift/drag values at higher speeds than conventional configurations. The Waverider cruises at Mach 5.5, has a range of 6,500 nautical miles, and seats 250 passengers. The aircraft is operable from existing airfields and does not require any special traffic control considerations when operating in controlled airspace

Domain Generalisation via Risk Distribution Matching

We propose a novel approach for domain generalisation (DG) leveraging risk distributions to characterise domains, thereby achieving domain invariance. In our findings, risk distributions effectively highlight differences between training domains and reveal their inherent complexities. In testing, we may observe similar, or potentially intensifying in magnitude, divergences between risk distributions. Hence, we propose a compelling proposition: Minimising the divergences between risk distributions across training domains leads to robust invariance for DG. The key rationale behind this concept is that a model, trained on domain-invariant or stable features, may consistently produce similar risk distributions across various domains. Building upon this idea, we propose Risk Distribution Matching (RDM). Using the maximum mean discrepancy (MMD) distance, RDM aims to minimise the variance of risk distributions across training domains. However, when the number of domains increases, the direct optimisation of variance leads to linear growth in MMD computations, resulting in inefficiency. Instead, we propose an approximation that requires only one MMD computation, by aligning just two distributions: that of the worst-case domain and the aggregated distribution from all domains. Notably, this method empirically outperforms optimising distributional variance while being computationally more efficient. Unlike conventional DG matching algorithms, RDM stands out for its enhanced efficacy by concentrating on scalar risk distributions, sidestepping the pitfalls of high-dimensional challenges seen in feature or gradient matching. Our extensive experiments on standard benchmark datasets demonstrate that RDM shows superior generalisation capability over state-of-the-art DG methods.Comment: Accepted at 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2024

Poverty Targeting and Impact of a Governmental Micro-credit Program in Vietnam

It is argued that without collateral the poor often face binding borrowing constraints in the formal credit market. This justifies a micro-credit program, which is operated by the Vietnam Bank for Social Policies to provide the poor with preferential credit. This paper examines poverty targeting and impact of the micro-credit program. It is found that the program is not very pro-poor in terms of targeting. Among the participants, the non-poor account for a larger proportion of loans. The non-poor also tend to receive larger amounts of credit compared to the poor. However, the program has positive impact on poverty reduction of the participants. This positive impact is found for all the three Foster-Greer-Thorbecke poverty measures.Micro-credit, poverty, poverty targeting, impact evaluation, instrumental variables, fixed-effect model

ROBUST DYNAMIC ID-BASED REMOTE MUTUAL AUTHENTICATION SCHEME

Dynamic ID based authentication scheme is more and more important in insecure wireless environment and system. Two of kinds of attack that authentication schemes must resist are stealing identity and reflection attack which is a potential way of attacking a challenge- response authentication system using the same protocol in both direc­tions. It must be guaranteed to prevent attackers from reusing informa­tion from authentication phase and the scheme of Yoon and Yoo satisfies those requirements. However, their scheme can not resist insider and impersonation attack by using lost or stolen smart card. In this paper, we demonstrate that Yoon and Yoo’s scheme is still vulnerable to those attacks. Then, we present an improvement to their scheme in order to isolate such problems

NOVEL HPLC-UV METHOD USING VOLATILE BUFFER FOR SIMULTANEOUS DETERMINATION OF AMLODIPINE BESYLATE AND ATORVASTATIN CALCIUM

Objective: The purpose of this work was to develop and validate a novel HPLC-UV method using triethylamine (TEA) as a volatile buffer for simultaneous determination of amlodipine besylate (AML) and atorvastatin calcium (ATV).Methods: System suitability, linearity, limit of detection (LOD), limit of quantification (LOQ), selectivity, accuracy, and precision was validated using Hitachi L-2000 system with detector: DAD L-2455 at a detected wavelength of 245 nm. Stationary phase: Phenomenex Luna RP-C18 (250 mm x 4.6 mm, 5 µm) and mobile phase: acetonitrile-methanol-TEA pH 4.0 (ratio 52:18:30 v/v/v) were used. Samples' volume of 20 µl was run at room temperature with the flow rate at 1 ml/min.Results: The linearity demonstrated good correlation in the concentration range at 2-40 ppm and 4-80 ppm for AML and ATV, respectively. The method was repeatable with relative standard deviation (RSD) of the intermediate precision test less than 1%. The recovery rate was 100.03% and 99.58% for AML and ATV, respectively. The method was also validated for dissolution studies with excellent compatibility.Conclusion: A new, simple and easy HPLC-UV method was successfully developed and validated for the determination of AML and ATV in both quantification test and dissolution test.Keywords: Amlodipine, Atorvastatin, Simultaneous, Dissolution, HPLC, Quantification, Volatile buffe

On Dissimilarity Measures at the Fuzzy Partition Level

International audienceOn the one hand, a user vocabulary is often used by soft-computing-based approaches to generate a linguistic and subjective description of numerical and categorical data. On the other hand, knowledge extraction strategies (as e.g. association rules discovery or clustering) may be applied to help the user understand the inner structure of the data. To apply knowledge extraction techniques on subjective and linguistic rewritings of the data, one first has to address the question of defining a dedicated distance metric. Many knowledge extraction techniques indeed rely on the use of a distance metric, whose properties have a strong impact on the relevance of the extracted knowledge. In this paper , we propose a measure that computes the dissimilarity between two items rewritten according to a user vocabulary

Cognitive full-duplex relay networks under the peak interference power constraint of multiple primary users

Abstract This paper investigates the outage performance of cognitive spectrum-sharing multi-relay networks in which the relays operate in a full-duplex (FD) mode and employ the decode-and-forward (DF) protocol. Two relay selection schemes, i.e., partial relay selection (PRS) and optimal relay selection (ORS), are considered to enhance the system performance. New exact expressions for the outage probability (OP) in both schemes are derived based on which an asymptotic analysis is carried out. The results show that the ORS strategy outperforms PRS in terms of OP, and increasing the number of FD relays can significantly improve the system performance. Moreover, novel analytical results provide additional insights for system design. In particular, from the viewpoint of FD concept, the primary network parameters (i.e., peak interference at the primary receivers, number of primary receivers, and their locations) should be carefully considered since they significantly affect the secondary network performance