Active Management of the Third Stage of Labour: Knowledge and Challenges of Obstetric Caregivers in Selected Health Facilities in Fako Division, Cameroon

Background: In Cameroon, the decrease in MMR (Maternal Mortality Ratio) from PPH (Postpartum Haemorrhage) despite the reported use of the Active Management of the Third Stage of Labour (AMTSL) is slower than what is required to achieve the Third Sustainable Development Goal (SDG3) hence the need to question obstetric caregivers’ competence in AMTSL, as well as the factors hindering its proper use. We therefore aimed to assess obstetric caregivers’ knowledge about AMTSL, as well as the determinants and barriers of AMTSL in selected hospitals in Fako Division, Cameroon. Methods: This was a hospital-based cross-sectional study of 150 participants recruited in 27 health facilities in Buea, Limbe and Tiko health districts from January 15, 2020, to March 31, 2020. Participants’ socio-demographic and qualification characteristics, knowledge and challenges, and the references guiding their practice of AMTSL were collected using a structured questionnaire. AMTSL knowledge was categorized as poor or good and the determinants of good AMTSL knowledge were evaluated. The data was analyzed in SPSS version 25.0. Results: Of the 150 caregivers interviewed, only 48.7% had good knowledge of AMTSL. In logistic models, participants’ use of AMTSL increased Good knowledge of AMTSL (AOR: 12.96, CI: 1.12 - 150.3, p = 0.04). Unavailability of drugs and/or equipment, insufficient staff coverage and lack of knowledge and training of the staff were the major challenges reported. Conclusion: Obstetric caregivers in Fako division have knowledge gaps and face numerous challenges in AMTSL use, which could account for the consistently high MMR from PPH. Filling this knowledge gap and mitigating the challenges of these caregivers would certainly accelerate progress towards the achievement of SDG3.

Optimal Operation of Flexible Distribution Networks for Security Improvement Considering Active Management

This paper presents a stochastic optimal operation problem of gas turbine integrated distribution networks in the presence of active management schemes,which is formulated as a multi-objective chance-constrained mixed integer nonlinear programming problem.The control variables are the on-load tap-changer tap position,the power provided by the distributed generation(DG),the DG power factor angle,the load participating in demand side management and the switch status.The objectives defined in this paper are to simultaneously minimize the expectation cost and variation coefficient of security distance.Uncertainties related to DG output and load fluctuation and fault power restoration under contingencies are also considered in the optimization problem.The collaboration of normal boundary intersection and the dynamic niche differential evolution algorithm is proposed to handle the optimal operation mode.Simulation results are presented and demonstrate the effectiveness of the proposed model.Compared with the operation result without the consideration of security,the security-constrained operation can reduce the expectation cost.Therefore,the proposed optimization is reasonable and valuable.

A Multi-objective Chance-constrained Information-gap Decision Model for Active Management to Accommodate Multiple Uncertainties in Distribution Networks

The load demand and distributed generation(DG)integration capacity in distribution networks(DNs)increase constantly,and it means that the violation of security constraints may occur in the future.This can be further worsened by short-term power fluctuations.In this paper,a scheduling method based on a multi-objective chance-constrained information-gap decision(IGD)model is proposed to obtain the active management schemes for distribution system operators(DSOs)to address these problems.The maximum robust adaptability of multiple uncertainties,including the deviations of growth prediction and their relevant power fluctuations,can be obtained based on the limited budget of active management.The systematic solution of the proposed model is developed.The max term constraint in the IGD model is converted into a group of normal constraints corresponding to extreme points of the max term.Considering the stochastic characteristics and correlations of power fluctuations,the original model is equivalently reformulated by using the properties of multivariate Gaussian distribution.The effectiveness of the proposed model is verified by a modified IEEE 33-bus distribution network.The simulation result delineates a robust accommodation space to represent the adaptability of multiple uncertainties,which corresponds to an optional active management strategy set for future selection.

A Fully Adaptive Active Queue Management Method for Congestion Prevention at the Router Buffer

Active queue management(AQM)methods manage the queued packets at the router buffer,prevent buffer congestion,and stabilize the network performance.The bursty nature of the traffic passing by the network routers and the slake behavior of the existing AQM methods leads to unnecessary packet dropping.This paper proposes a fully adaptive active queue management(AAQM)method to maintain stable network performance,avoid congestion and packet loss,and eliminate unnecessary packet dropping.The proposed AAQM method is based on load and queue length indicators and uses an adaptive mechanism to adjust the dropping probability based on the buffer status.The proposed AAQM method adapts to single and multiclass traffic models.Extensive simulation results over two types of traffic showed that the proposed method achieved the best results compared to the existing methods,including Random Early Detection(RED),BLUE,Effective RED(ERED),Fuzzy RED(FRED),Fuzzy Gentle RED(FGRED),and Fuzzy BLUE(FBLUE).The proposed and compared methods achieved similar results with low or moderate traffic load.However,under high traffic load,the proposed AAQM method achieved the best rate of zero loss,similar to BLUE,compared to 0.01 for RED,0.27 for ERED,0.04 for FRED,0.12 for FGRED,and 0.44 for FBLUE.For throughput,the proposed AAQM method achieved the highest rate of 0.54,surpassing the BLUE method’s throughput of 0.43.For delay,the proposed AAQM method achieved the second-best delay of 28.51,while the BLUE method achieved the best delay of 13.18;however,the BLUE results are insufficient because of the low throughput.Consequently,the proposed AAQM method outperformed the compared methods with its superior throughput and acceptable delay.

The diameter of beech snags is an important factor for saproxylic beetle richness: Implications for forest management and conservation

Snags are an important component of beech forests that promote biodiversity.However,their occurrence is completely marginal in managed stands.Creating snags in these stands would greatly enhance biodiversity.We investigated whether snag dimensions were important for saproxylic beetle richness since they were easily transferable parameters to forest management and assessed the presence of other snag microhabitats affecting beetle communities.Data collection was performed using passive flight traps placed on thirty snags in a recent beech reserve.A total of 6706 adults belonging to 231 saproxylic species(53 Red List species,23%)were captured.The results showed that the most important snag parameters were the diameter(thickness)and canopy openness of the surrounding stands.The occurrence of Fomes fomentarius,the volume of snag and decay class 3 were marginally significant in terms of the preference of all saproxylic species.Alpha diversity was reduced by an advanced degree of decay and a surprisingly deep stem cavity.After dividing snag thickness into categories(<35 cm;35–70 cm and>70 cm DBH),we found that categories with snag diameter greater than 35 cm showed little differences in all saproxylic and Red List species richness and diversity indices and exhibited the highest similarity in beetle communities.Regarding recommendations to forest managers in terms of optimization and simplification of practical procedures,we suggest actively creating high stumps to act as snags greater than 35 cm in DBH diameter to promote biodiversity in beech management stands.

A FUZZY-LOGIC CONTROL ALGORITHM FOR ACTIVE QUEUE MANAGEMENT IN IP NETWORKS

Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the pre- dominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theo- retical analysis and Network Simulator (NS) simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router's ability in network congestion control in IP network.

Active forest management accelerates carbon storage in plantation forests in Lishui,southern China

Background:China has committed to achieving peak CO_(2)emissions before 2030 and carbon neutrality before 2060;therefore,accelerated efforts are needed to better understand carbon accounting in industry and energy fields as well as terrestrial ecosystems.The carbon sink capacity of plantation forests contributes to the mitigation of climate change.Plantation forests throughout the world are intensively managed,and there is an urgent need to evaluate the effects of such management on long-term carbon dynamics.Methods:We assessed the carbon cycling patterns of ecosystems characterized by three typical plantation species(Chinese fir(Cunninghamia lanceolata(Lamb.)Hook.),oak(Cyclobalanopsis glauca(Thunb.)Oerst.),and pine(Pinus massoniana Lamb.))in Lishui,southern China,by using an integrated biosphere simulator(IBIS)tuned with localized parameters.Then,we used the state-and-transition simulation model(STSM)to study the effects of active forest management(AFM)on carbon storage by combining forest disturbance history and carbon cycle regimes.Results:1)The carbon stock of the oak plantation was lower at an early age(<50 years)but higher at an advanced age(>50 years)than that of the Chinese fir and pine plantations.2)The carbon densities of the pine and Chinese fir plantations peaked at 70 years(223.36 Mg⋅ha^(‒1))and 64 years(232.04 Mg⋅ha^(‒1)),respectively,while the carbon density in the oak plantation continued increasing(>100 years).3)From 1989 to 2019,the total carbon pools of the three plantation ecosystems followed an upward trend(an annual increase of 0.16–0.22 Tg C),with the largest proportional increase in the aboveground biomass carbon pool.4)AFM increased the recovery of carbon storage after 1996 and 2009 in the pine and Chinese fir plantations,respectively,but did not result in higher growth in the oak plantation.5)The proposed harvest planning is reasonable and conducive to maximizing the carbon sequestration capacity of the forest.Conclusions:This study provides an example of a carbon cycle coupling model that is potentially suitable for simulating China's plantation forest ecosystems and supporting carbon accounting to monitor peak CO_(2)emissions and reach carbon neutrality.

A simulation study of using active traffic management strategies on congested freeways

The main objective of this study is to evaluate the effectiveness of using active traffic management （ATM） strategies on freeways in terms of the driver＇s behavior and operational impacts. A few test beds were selected to evaluate the impacts of ATM such as speed harmonization, shoulder utilization, and ramp metering. Test beds used in this study were at places where an ATM is either proposed or previously implemented, i.e., where data exists for condi- tions prior to and after the implementation of ATM. Data collected from the test beds were used in a simulation model to evaluate the impacts of each ATM strategy on speed, travel time, and crash rates. Simulation results indicated that the implementation of speed harmonization on US 90 showed a 14% reduction in crashes and a 2%-3% increase in freeway speed; the implementation of hard shoulders on US 90 showed a 39% increase in travel time, 22% increase in freeway capacity and 60% decrease in delays; and the implementation of ramp metering on US 59 between Bissonnet St. and Fondern road showed a decrease of 23 % in freeway travel time, a 14% increase in freeway speed and 11% decrease in accident rates.

Active Queue Management Exploiting the Rate Information in TCP-IP Networks

In this paper, we propose a new mechanism called explicit rate notification(ERN) to be used in end-to-end communications. The ERN scheme encodes in the header of transmission control protocol(TCP) packets information about the sending rate and the round trip time(RTT) of the flows. This new available information to the intermediate nodes(routers) is used to improve fairness, increase utilization, decrease the number of drops, and minimize queueing delays. Thus, it induces a better management of the queue. A comparison of our scheme with preexistent schemes, like the explicit congestion notification scheme, shows the effectiveness of the proposed mechanism.

An Active Queue Management Algorithm: CRED

By applying the method of average and variance, a new queue management algorithm named the Classified-Random Early Detection （CRED） algorithm is presented which can identify the media streaming, TCP traffic and other UDP traffic at the edge routers. The algorithm discriminates the slow start and the congestion control phase of the TCP traffic and combines the TCP congestion control with the IP congestion control to alleviate the congestion effectively. Simulation shows that CRED can not only make the media streaming obtain the resources needed but also protect the TCP traffic transmitted effectively and reliably.

Two-Dimensional Electronic Spectroscopy with Active Phase Management

Two-dimensional elec tronic spec troscopy(2DES)is a powerful met hod to probe the coherent electron dynamics in complicated systems.Stabilizing the phase difference of the incident ultrashort pulses is the mos t challenging par t for experimen tal demonstration of 2DES.Here,we present a tuto rial review on the 2DES proto cols based on active phase managements which are originally developed for quantum optics experiments.We introduce the 2DES techniques in box and pump-probe geometries with phase stabilization realized by interferometry,and outline the fully collinear 2DES approach with the frequency tagging by acoustic optical modulators and frequency combs.The combination of active phase managements,ultrashort pulses and other spectroscopic methods may open new opportunities to tackle essential challenges related to excited states.

A Robust Algorithm in Active Queue Management

A variable structure based control scheme was proposed for Active Queue Management(AQM) by using sliding model algorithm and reach law method. This approach aims to address the tradeoff between good performance and robustness with respect to the uncertainties of the round-trip time and the number of active connections. Ns simulations results show that the proposed design significantly outperforms the peer AQM schemes in terms of fluctuation in the queue length, packet throughput, and loss ratio. The conclusion is that proposed scheme is in favor of the achievement to AQM objectives due to its good transient and steady performance.

Multi-indicator Active Queue Management Method

A considerable number of applications are running over IP networks.This increased the contention on the network resource,which ultimately results in congestion.Active queue management(AQM)aims to reduce the serious consequences of network congestion in the router buffer and its negative effects on network performance.AQM methods implement different techniques in accordance with congestion indicators,such as queue length and average queue length.The performance of the network is evaluated using delay,loss,and throughput.The gap between congestion indicators and network performance measurements leads to the decline in network performance.In this study,delay and loss predictions are used as congestion indicators in a novel stochastic approach for AQM.The proposed method estimates the congestion in the router buffer and then uses the indicators to calculate the dropping probability,which is responsible for managing the router buffer.The experimental results,based on two sets of experiments,have shown that the proposed method outperformed the existing benchmark algorithms including RED,ERED and BLUE algorithms.For instance,in the first experiment,the proposed method resides in the third-place in terms of delay when compared to the benchmark algorithms.In addition,the proposed method outperformed the benchmark algorithms in terms of packet loss,packet dropping,and packet retransmission.Overall,the proposed method outperformed the benchmark algorithms because it preserves packet loss while maintaining reasonable queuing delay.

Fuzzy variable structure algorithms for active queue management with delay compensation

Based on the linearized model of the TCP connections through the congested routers, this paper puts forward an active queue management algorithm (FVS-T). The algorithm utilizes the fuzzy variable structure control algorithm with delay factor to compensate time varying round-trip times (RTT) and uncertainties with respect to the number of active TCP sessions. By analyzing the robustness and performance of the control scheme for the nonlinear TCP/AQM model, we show that the proposed design has good performance and robustness, which are central to the notion of AQM. Implementation issues were discussed and ns simulations were provided to validate the design and compare its performance to other peer schemes in different scenarios. The results show that the proposed design significantly outperforms the other congestion schemes in terms of packet loss ratio, throughput and buffer fluctuation.

RED-DTB: A Dual Token Bucket Based Queue Management Algorithm

Improving the Quality of Service (QoS) of Internet traffic is widely recognized as a critical issue for the next-generation networks. In this paper, we present a new algorithm for the active queue management, namely RED-DTB. This buffer control technique is used to enforce approximate fairness among a large number of concurrent Internet flows. Like RED (Random Early Detection) algorithm, the RED-DTB mechanism can be deployed to actively respond to the gateway congestion, keep the gateway in a healthy state, and protect the fragile flows from being stolen bandwidth by greedy ones. The algorithm is based on the so-called Dual Token Bucket (DTB) pattern. That is, on the one hand, every flow is rate-limited by its own token bucket, to ensure that it can not consume more than its fair share of bandwidth; On the other hand, to make some compensations to less aggressive flows, such as connections with larger round trip time or smaller sending window, and to gain a relatively higher system utilization coefficient, all flows, depending on their individual behavior, may have a chance to fetch tokens from the public token bucket when they run out of their own share of tokens. The algorithm is analyzed and evaluated by simulations, and is proved to be effective in protecting the gateway buffer and controlling the fair allocation of bandwidth among flows.

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Congestion control is one of the main obstacles in cyberspace traffic.Overcrowding in internet traffic may cause several problems;such as high packet hold-up,high packet dropping,and low packet output.In the course of data transmission for various applications in the Internet of things,such problems are usually generated relative to the input.To tackle such problems,this paper presents an analytical model using an optimized Random Early Detection(RED)algorithm-based approach for internet traffic management.The validity of the proposed model is checked through extensive simulation-based experiments.An analysis is observed for different functions on internet traffic.Four performance metrics are taken into consideration,namely,the possibility of packet loss,throughput,mean queue length and mean queue delay.Three sets of experiments are observed with varying simulation results.The experiments are thoroughly analyzed and the best packet dropping operation with minimum packet loss is identified using the proposed model.

Research on Applications of Humanism Management Thoughts and Positive Incentive on Contemporary Enterprise Management Activities

In this paper, we conduct research on the applications of humanism management thoughts and positive incentive on contemporary enterprise management activities. The success or failure of an enterprise, it has connected with the enterprise staff. Modem enterprise to make the enterprise in the competitive market of the brand is enduring, its survival is to be active play to the initiative, enthusiasm and creativity of employees, emphasizing the subject status of the employees and the leading role which is to emphasize the importance of basic management in enterprise management. Our research provides managers with the state-of-the-art methodology of management which will enhance the overall performance and the efficiency of business operating.

Active energy management strategies for active distribution system

Active energy management is an effective way to realize the flexible utilization of distributed energy resources to suit the characteristics of active distribution system.Advanced active energy management strategies need to be designed to coordinate the optimization of‘generation,network,load’.An active management model is built for the local distribution system integrated with the generation curtailment mechanism and the charging/discharging management of plug-in electric vehicles.Furthermore,different strategies based on the energy management model are presented.The model and strategies are tested and discussed in a modified distribution system,and the impacts with different load profiles are also analyzed.

Fuzzy variable structure delay control algorithms and their applications to AQM

This paper analyzes the fuzzy variable structure control algorithms for delay systems and describes the compensation mechanism of the integral factor to the effect of the delay. Based on the linearized model of the congestion-avoidance flow-control mode of transmission control protocol (TCP), we present delay control algorithms for active queue management (AQM) and discuss the parameter tuning of the algorithms. The NS (network simulator) simulation results show that the proposed control scheme for the nonlinear TCP/AQM model has good performance and robustness with respect to the uncertainties of the round-trip time (RTT) and the number of active TCP sessions. Compared to other similar schemes, our algorithms perform better in terms of packet loss ratio, throughput and butter fluctuation.

Diffserv AQM algorithm for edge and core routers

The existing active queue management （AQM） algorithm acts on subscribers and edge routers only, it does not support differentiate-serve （Diffserv） quality of service （QoS）, while the existing diffserv QoS has not considered the link capacities between edge routers and connected core routers. When a core router in a two layers’ network experiences congestion, the connected edge routers have no ability to adjust their access data rates. Thus, it is difficult to achieve the congestion control for the large scale network with many edge routers and core routers. To solve these problems, two difffserve AQM algorithms are proposed for the congestion control of multilayer network. One diffserv AQM algorithm implements fair link capacities of edge routers, and the other one implements unequal link capacities of edge routers, but it requires the core routers to have multi-queues buffers and Diffserv AQM to support. The proposed algorithms achieve the network congestion control by operating AQM parameters on the conditions of proposed three theorems for core and edge routers. The dynamic simulation results demonstrate the proposed control algorithms for core and edge routers to be valid.