Infrequent dream recall associated with low performance but high overnight improvement on mirror-tracing

2015 ◽  
Vol 24 (4) ◽  
pp. 372-382 ◽  
Author(s):  
Gaëlle Dumel ◽  
Michelle Carr ◽  
Louis-Philippe Marquis ◽  
Cloé Blanchette-Carrière ◽  
Tyna Paquette ◽  
...  
Keyword(s):  
Dream Recall ◽  
Mirror Tracing ◽  
Low Performance

FREQUENCY OF DREAM RECALL BY CHILDREN AND THEIR MOTHERS

2006 ◽  
Vol 103 (7) ◽  
pp. 657 ◽  
Author(s):  
MICHAEL SCHKEDL
Keyword(s):  
Dream Recall

RELIABILITY AND STABILITY OF A DREAM RECALL FREQUENCY SCALE

2004 ◽  
Vol 98 (4) ◽  
pp. 1422 ◽  
Author(s):  
MICHAEL SCHREDL
Keyword(s):  
Dream Recall ◽  
Dream Recall Frequency ◽  
Frequency Scale

ANALISIS KINERJA PABRIK TEH HITAM “PAHIT MADU”

2013 ◽  
Vol 13 (3) ◽  
Author(s):  
Djawardi Djawardi ◽  
Yustiar Gunawan
Keyword(s):  
Heat Exchanger ◽  
Production Process ◽  
Black Tea ◽  
Production Equipment ◽  
Standard Means ◽  
Fluid Bed ◽  
Calculation Results ◽  
Low Performance ◽  
Equipment Utilization

The business unit's black tea processing of Perkebunan Nusantara suffered a loss of approximately Rp.60 billion. This is caused by the failure to achieve the quality and quantity of production which has been targeted by the management. Black tea processing factory "Pahit Madu" is required to improve the performance of the production process. To improve the production of black tea starts from improved production equipment through improved equipment utilization. One method ofmeasuring the effectiveness of using an apparatus is Overall EquipmentEffectiveness (OEE). OEE calculation results show that black tea factory "Pahit Madu" for four (4) years under the standard. Means, the effectiveness of utilization of equipment in the factory black tea "Pahit Madu" was still very low. This was shown by the low performance equipment in the milling unit, drying unit and sortation unit. Toimprove the performance of the plant should begin by increasing the Cutting Tearing Curling (CTC) machine in milling stations, machines Fluid Bed Dryer (FBD) and Heat Exchanger (HE) at the drying stations, and Winnower machines at the sortation stations.

Sarcopenia is an actual problem in chronic kidney disease of the 5d stage

2020 ◽  
Vol 24 (1) ◽  
pp. 60-66
Author(s):  
I. V. Lavrishcheva ◽  
A. Sh. Rumyantsev ◽  
M. V. Zakharov ◽  
N. N. Kulaeva ◽  
V. M. Somova
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Muscle Mass ◽  
Chronic Kidney Disease Stage ◽  
Age Groups ◽  
Disease Stage ◽  
Actual Problem ◽  
European Working ◽  
Low Performance ◽  
6 Minute Walk Test

BACKGROUND. The lack of data on the epidemiology of presarcopenia/sarcopenia leads to an underestimation of the role of this condition in the structure of morbidity and mortality of haemodialysis patients in theRussian Federation. THE AIM: to study the epidemiological aspects of presarcopenia /sarcopenia in patients with chronic kidney disease stage 5d. PATIENTS AND METHODS. This study comprised 317 patients receiving programmed bicarbonate haemodialysis for 8.2 ± 5.1 years, among them 171 women and 146 men, the average age was 57.1 ± 11.3 years. The assessment of the presence of sarcopenia was performed using the method recommended by the European Working Group on Sarcopenia in Older People. RESULTS. The prevalence of presarcopenia was 0.7 % and sarcopenia 29.6 %. The incidence of skeletal muscle mass deficiency according to muscle mass index (IMM) was 30.3 %, 48.7 % showed a decrease in muscle strength according to dynamometry, and low performance of skeletal muscles according to 6 minute walk test was determined in 42.8 %. Sarcopenia patients were significantly characterized by lower body mass index, as well as higher body fat mass values. The duration of haemodialysis (χ2 = 22.376, p = 0.0001) and the patient's age (χ2 = 10.545 p = 0.014) were an independent risk factors for the development of sarcopenia. CONCLUSION. Sarcopenia is recorded more frequently in hemodialysis patients than presarcopenia. Its prevalence increases among patients of older age groups and with a hemodialysis duration of more than 5 years. The age and experience of dialysis make their independent contribution to the development of this syndrome.

Understanding the Persistent Low Performance of African Agriculture

2006 ◽  
Author(s):  
Sylvain Dessy ◽  
Jacques Ewoudou ◽  
Isabelle Ouellet
Keyword(s):  
Low Performance ◽  
African Agriculture

Resilient Factors in Students with Disabilities

2018 ◽  
Vol 5 (2) ◽  
pp. 23 ◽  
Author(s):  
Gustavo Rafael Escobar Delgado ◽  
Anicia Katherine Tarazona Meza ◽  
Andy Einstein García García
Keyword(s):  
Academic Performance ◽  
Students With Disabilities ◽  
Latin American ◽  
Descriptive Study ◽  
The Other ◽  
Disabled Students ◽  
Low Performance ◽  
The Relationship ◽  
Latin American Population

The research analyzes the relationship between factors of resilience and academic performance in disabled students studying at the Technical University of Manabí. It is a correlational descriptive study conducted with a population of 88 disabled students, of which two groups were selected, one with high academic performance and the other with low performance. A questionnaire was designed and applied to determine the level of quality of life and risk factors of adolescents. Resilience was measured with the SV-RES scale created for the Latin American population.

scholarly journals Dream Recall/Affect and the Hypothalamic–Pituitary–Adrenal Axis

2021 ◽  
Vol 3 (3) ◽  
pp. 403-408
Author(s):  
Athanasios Tselebis ◽  
Emmanouil Zoumakis ◽  
Ioannis Ilias
Keyword(s):  
Hpa Axis ◽  
Glucocorticoid Receptors ◽  
Hypothalamic Pituitary Adrenal Axis ◽  
Free Form ◽  
Dream Recall ◽  
Hypothalamic Pituitary Adrenal ◽  
Adrenal Axis ◽  
Concise Review ◽  
Pathological Conditions ◽  
Pituitary Adrenal Axis

In this concise review, we present an overview of research on dream recall/affect and of the hypothalamic–pituitary–adrenal (HPA) axis, discussing caveats regarding the action of hormones of the HPA axis (mainly cortisol and its free form, cortisol-binding globulin and glucocorticoid receptors). We present results of studies regarding dream recall/affect and the HPA axis under physiological (such as waking) or pathological conditions (such as in Cushing’s syndrome or stressful situations). Finally, we try to integrate the effect of the current COVID-19 situation with dream recall/affect vis-à-vis the HPA axis.

scholarly journals Recalling and Forgetting Dreams: Theta and Alpha Oscillations during Sleep Predict Subsequent Dream Recall

2011 ◽  
Vol 31 (18) ◽  
pp. 6674-6683 ◽  
Author(s):  
C. Marzano ◽  
M. Ferrara ◽  
F. Mauro ◽  
F. Moroni ◽  
M. Gorgoni ◽  
...  
Keyword(s):  
Dream Recall ◽  
Alpha Oscillations

scholarly journals Traffic Type Recognition Method for Unknown Protocol—Applying Fuzzy Inference

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 36
Author(s):  
Sang-Won Kim ◽  
Kee-Cheon Kim
Keyword(s):  
Fuzzy Inference ◽  
Static Field ◽  
Theoretical Background ◽  
Alignment Algorithm ◽  
Traffic Classification ◽  
Recognition Method ◽  
Inference System ◽  
Traffic Characteristics ◽  
Sequence Alignment Algorithm ◽  
Low Performance

In this paper, we propose a system that can recognize traffic types without prior knowledge of static features such as protocol header information by combining protocol analysis based on an ecological sequence alignment algorithm in a bioinformatics and fuzzy inference system. The algorithm proposed in this paper obtained up to a 91% level of performance at a similar level to several existing algorithms in experiments using datasets containing various types of traffic. In addition, it showed an excellent accuracy of 82.5% or more even under severe conditions that lowered the amount of data to a level of at least 40% or only included data in the middle of the traffic. This shows that the problem of dependence on initial data that frequently occurs in existing machine learning and deep learning-based traffic classification algorithms does not appear in the proposed algorithm. Furthermore, based on the ability to directly extract traffic characteristics without being dependent on static field values, it has secured the ability to respond with a small number of data by taking advantage of the flexibility of the membership function of the fuzzy inference engine. Through this, the applicability to low-power and low-performance environments such as IoT networks was confirmed. In this paper, we describe in detail the theoretical background for constructing such an algorithm and relevant experiments and considerations for actual verification.

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