Concept Of Dynamic Stability Research Articles

Integrating univariate and multivariate stability indices for breeding clime-resilient barley cultivars

Studying genetic variability through the phenotypic performance of genotypes is crucial in the breeding program. Therefore, evaluating both yield performance and stability across diverse environments is essential in yield trials to identify high-yield potential and stable cultivars. In this study, we employed 12 univariate and 10 multivariate stability models to analyze how genotype (G), environment (E), and their interaction (G × E) affect the yield performance of 32 barley genotypes across 10 environments. The environmental main effect explained 81.3% of the total variation, compared to 18.6% for genotypes and G × E interaction effects. Using the GGE biplot ‘which-won-where’ polygon, we categorized environments into five groups and genotypes into six groups, identifying eight genotypes with mean grain yield (GY) superior to the overall mean (4.43 tons ha− 1). Spearman’s correlation analysis indicated significant positive correlations (P < 0.01) between GY and various stability parameters such as linear regression coefficients (bi), Perkins and Jinks’s stability parameters (Bi), environmental variance (Sxi2) and Tai’s environmental effects (αi), among others, as univariate stability measures. Additionally, nonparametric measures such as Nassar and Huhn’s (SI 6 and SI 3) and Thennarasu’s (NP I (3) and NP I (4)), TOP-rank stability and the yield stability index (YSI), showed significant correlations with GY. Both univariate and multivariate stability models highlighted genotypes G32, G1, and G27 as the most stable, exhibiting minimal yield variation across environments. Furthermore, G15, followed by G13, G7, and G9, demonstrated high stability based on multivariate measures. Accordingly, it might be safe to utilize the stability parameters of different groups concerning static and dynamic concepts of stability to avoid the possibility of estimating the same concept of stability. This study emphasizes the importance of utilizing a combination of univariate and multivariate stability models to assess genotype stability comprehensively and select “ideal genotypes” that offer both high yield potential and stability.

Genotype-by-environment interaction analysis for grain yield of barley genotypes in the warm climate of Iran

In the present study, multi-environmental trials were performed on 19 newly developed barley genotypes at five test regions across the warm climate in Iran for two consecutive years. The results of additive main effects and multiplicative interaction (AMMI), GGE biplot (GGE) model, and several BLUP-based stability parameters and integrated models (WAASB and WAASBY) were used to reveal GEI patterns and identify superior genotypes with stable grain yield across test environments. Statistical analyses revealed that grain yield was influenced by significant environments (E), genotypes (G), and GEI effects. Among AMMI-, BLUP-, and grain mean-based stability parameters, the harmonic means of genotypic values (HMGV), relative performance of genotypic value (RPGV), and harmonic mean of RPGV parameters indicated a dynamic concept of stability. Moreover, results of GGE biplot analysis identified three mega-environments with different winner genotypes in test environments. Regardless of the different years, the Ahvaz, Darab, and Moghan regions were identified as Type-II environments due to their highest discrimination power and representative ability. The grouping pattern considerably followed the ranking of genotypes in GGE biplot analysis and WAASB model. In conclusion, our results revealed that genotypes G9 and G10 had grain yield higher than the reference genotype and relative stability in specific environments with favorable environmental conditions. Genotype G5 had general adaptability and stability across all test environments. This genotype can be recommended for cultivation in a wide range of environments in the warm climate of Iran.

Динамическая стабильность как категория диалектического взаимодействия хаоса и космоса в онтологии сетевого бытия

The increasing information flow has led to, inter alia, the dominant role of networking in communications. Devirtualization of networking in information and physical networks has made it possible to introduce network discourse into modern philosophy. The study of writings by Laozi, Confucius and their followers demonstrates that network discourse and network thinking were developed in the philosophical works of ancient Chinese scholars as representatives of Eastern philosophical discourse. At the same time, Western philosophical discourse, which can be traced to Plato and Aristotle, rests on linear logic and linear thinking. It is only towards the end of the 20th century that the linear/network thinking opposition weakened with the recognition of network interaction, under the influence of a profound transformation during the transition to a new stage of civilization’s development, that is, to the information/digital society. This can be illustrated by the evolution of the perception of the categories chaos and cosmos in Western (linear) and Eastern (network) philosophical discourse as the basis of the development of the modern representation of dynamic stability of the network interaction system. Using the information and communication method, this paper analyses Western and Eastern philosophical discourse from the Axial Age to the present day and substantiates the introduction of the category of dynamic stability. The latter stands for a dialectically connected process of creation/destruction of communications between actors of a network interaction under the influence of the dynamics of information exchange, which indicates that a network interaction system is autopoietic. Further development of the concept of dynamic stability requires creating a mathematical apparatus for calculating measures, that is, information entropy, of a dynamically stable network. These purely abstract studies are expected to be of practical importance for the development of social networks of interpersonal and intergroup communication.

STABILITAS PARAMETRIK HASIL 14 GENOTIPE TOMAT (Solanum lycopersicum L.) DI EMPAT LINGKUNGAN DATARAN RENDAH

This study aimed to obtain information stability results 14 tomato genotypes grown in four lowland locations using multiple methods of parametric stability analysis. The experiments were conducted at four locations, namely Purwakarta, Lombok, Tajur and Leuwikopo. Experiments at each location using Randomized Complete Block Design (RCBD) with three replications which replicates nested within location. The method used were Francis and Kannenberg, Wrickle ekovalens, Finlay and Wilkinson, Eberhart and Russel, Wrickle ekovalens and AMMI .&#x0D; Research carried out shows based on the concept of static stability using the method of Francis and Kannenberg and Russell Eberhart, who declared stable genotype were IPBT3, IPBT53 and IPBT78. Based on the concept of dynamic stability using Wrikle ekovalens and Finlay &amp; Wilkinson methods, stable genotype were IPBT3, IPBT8, IPBT33, IPBT34, IPBT57, IPBT60, IPBT64 and Intan. IPBT3, IPBT33, IPBT34, IPBT60 and Intan as stable genotypes under AMMI methods.

Constructing a resilient ecological network by considering source stability in the largest Chinese urban agglomeration

The dynamics of ecological sources and their impact on the resilience of ecological networks (ENs) have attracted increasing attention from both researchers and managers. Although a couple of studies have recognized the source-loss effects on network resilience, there is a knowledge gap in integrating spatiotemporal changes of the sources while constructing resilient ENs. Here, we propose the concept of dynamic stability (DS) to explore the sources’ changes over a certain period and improve source identification by grading the DS in the largest urban agglomeration located in the middle reaches of the Yangtze River in China. An investigation of the five selected ecosystem service (ES) indicators in 2000, 2010, and 2018 identified 49, 54, and 68 preliminary sources, respectively, from which 11, 14, and three sources were extracted, respectively, with high, moderate, and low levels of DS, respectively. A three-tier EN was constructed by considering both the ESs and DSs of the extracted sources. The constructed network was scale-free and featured in small world in topology analysis. Moreover, a carefully designed attack test found that this EN was of good resilience as the three critical nodes that might cause a marked decay of resilience were in high or moderate DSs and were preferentially protected by the Ecological Conservation Red Line policy in China. In conclusion, the improved approach of considering the DSs of sources may help to precisely identify and protect the critical nodes threatening network resilience, which is highly desired in constructing ENs facing various rapid changes, especially in large-scale urbanized areas.

Selection of High Yield and Stable Maize Hybrids in Mega-Environments of Java Island, Indonesia

Determination of grain yields of stable and high-yielding maize hybrids in a wide environment requires high accuracy. Many stability measurement methods have been used in multi-environment experiments. However, the relationships among the different methods are still difficult to understand. The objectives of this study were to 1. Identify the effect of growing season and location (Environments = E), hybrids (Genotypes = G), and their interactions (GEIs) on grain yields; 2. Select high-yielding and stable maize hybrids in a wide range of environments; 3. Determine the relationship between each stability estimation; and 4. Determine the mega-environment of maize hybrid and identify the best locations for testing. Field experiments were conducted at ten locations in Java Island, Indonesia, for two growing seasons using a randomized completed block design with three replications. The experimental results showed that the main effects of the growing season, location, hybrid, and GEIs, significantly affected maize hybrid yields. Stability estimations of TOP, S(3), S(6), NP(2), NP(3), KR, NP(4), CVi, and bi, belong to the concept of dynamic stability that can be used to select maize hybrids in favorable environments, while other estimations were classified as in the static stability. Three maize hybrids were successfully selected, with high and stable yields based on numerical and visual stability estimations, namely SC2, SC7, and SC9. The three hybrids can be used as candidates for sustainable maize development programs. The dry season, the rainy season, and the combination of two growing seasons produced three mega-environments. GJRS and KARS were the most discriminative environments. Both environments can be used as favorable environments for selecting the ideal maize hybrid.

Analysis of Grain Yield Stability of Triticale (×Triticosecale wittmack) Based on the Some Parametric and Non-Parametric Index under Semi-arid Conditions

Field experiment was conducted during the three consecutive cropping seasons (2017–2018, 2018–2019 and 2019–2020) at the experimental field of ITGC, Setif, Algeria to study the selection of adapted and stable genotypes of triticale based on the use of some parametric and non-parametric index. The program STABILITYSOFT was used to calculate the parametric and non-parametric index. The graphic distribution of the genotypes tested based on the relationship between the mean grain yield and regression coefficient (bi), proved that the suitable genotypes for the tested conditions are G2, and G3. The association between Wricke’secovalence (Wi²), the coefficient of variance (CVi), the mean variance component (θi ) and the Stability variance (σ²i) indices with the grain yield proved that the best genotypes for growing under these conditions were G2 and G3.In addition, the selection based on the non-parametric index showed that the genotypes G1, G2 and G3 were the most stables. The combination selection based on highest grain yield and the parametric indices proved that the genotypes G2 and G3 are the more stable and more adapted under semi-arid conditions. The results of spearman’s rank correlation and PCA analysis for grouping the different parametric stability statistics studied showed that stability indices could be classified into four groups. Moreover, and based on the static and dynamic concepts, the parametric indices bi and CVi are related to the static concept, while the other indices were associated with dynamic stability concept. Overall, the results of this study confirmed that the parametric and non-parametric methods were the suitable tools to identify the most stable triticale genotypes at various environmental conditions.

Nonparametric Analysis of Genotype Grain Yield Performance of Barley Trials Based on Ranks

Plant breeding has been concerned with genotype by environment (GE) interaction and high yielding genotypes with stable performance are desirable while this target is difficult to achieve due to high environmental variations and unpredictable GE interaction. Stability of grain yield performance of 18 barley genotypes was evaluated at 5 locations for 3 years in the rainfed conditions and it was studied through 25 nonparametric stability methods. Four nonparametric tests indicated highly significant GE interaction due to differential performance of genotypes across fifteen environments. Regarding mean yield and six Hühn’s statistics, genotype G12 (1946 kg ha-1) was the most favorable genotype while based on the RN1, G4, G10 and G11 were the most stable genotypes. Genotypes G4, G8 and G10 were the most favorable genotypes according to rank-sum while genotypes G2, G13 and G18 were the most favorable genotypes based on nonparametric superiority. The relative interactivity index identified G4, G16 and G8 as the most stable genotypes while the genotypic classification identified G1, G2, G13 and G18 as the most stable genotypes. Clustering of the nonparametric stability methods indicated that there were two groups with different static and dynamic characteristics. In this study, five nonparametric stability methods as GC, FM, PA, RN2 and KR2 were associated with high grain yield and reflected the dynamic concept of stability, but the other twenty nonparametric stability methods were not positively correlated with yield and characterized a static concept of stability. Finally, genotypes genotype G13 (2114.13 kg ha-1) and G18 (2062.69 kg ha-1) were found to be the most favorable genotypes and are thus recommended for commercial release in semiarid areas of Iran.

The form and evolution of international migration networks, 1990-2015.

Presently, there is no agreed upon data-driven approach for identifying the geographic boundaries of migration networks that international migration systems are ultimately manifested in. Drawing from research on community detection methods, we introduce and apply the Information Theoretic Community Detection Algorithm for identifying and studying the geographic boundaries of migration networks. Using a new set of estimates of country-to-country migration flows every 5 years from 1990 to 1995 to 2010-2015, we trace the form and evolution of international migration networks over the past 25 years. Consistent with the concept of dynamic stability, we show that the number, size and internal country compositions of international migration networks have been remarkably stable over time; however, we also document many short-term fluctuations. We conclude by reflecting on the spirit of our work in this paper, which is to promote consensus around tools and best practices for identifying and studying international migration networks.

Rational Behavior in Dynamic Multicriteria Games

We consider a dynamic, discrete-time, game model where n players use a common resource and have different criteria to optimize. To construct a multicriteria Nash equilibrium the bargaining solution is adopted. To design a multicriteria cooperative equilibrium, a modified bargaining scheme that guarantees the fulfillment of rationality conditions is applied. The concept of dynamic stability is adopted for dynamic multicriteria games. To stabilize the multicriteria cooperative solution a time-consistent payoff distribution procedure is constructed. The conditions for rational behavior, namely irrational-behavior-proofness condition and each step rational behavior condition are defined for dynamic multicriteria games. To illustrate the presented approaches, a dynamic bi-criteria bioresource management problem with many players is investigated.

Dynamic multicriteria games with asymmetric players

In this paper a new approach to construct cooperative behavior in dynamic multicriteria games with asymmetric players is presented. To obtain noncooperative and cooperative equilibria the ideas of multi-objective optimization and game theory are combined. To construct a multicriteria Nash equilibrium the bargaining solution is adopted. To design a multicriteria cooperative equilibrium a compromise scheme that guarantees the fulfillment of rationality conditions is applied. The concept of dynamic stability is adopted for dynamic multicriteria games, and the time-consistent payoff distribution procedure is presented. A dynamic bi-criteria bioresource management problem with different discount factors is considered. The strategies and payoffs of players are obtained under cooperative and noncooperative behavior.

Use of Principal Coordinate Analysis for Measuring GE Interactions in Rain-Fed Durum Wheat Genotypes

Genotype × environment interactions complicate selection of superior genotypes for narrow and wide adaptation. Multienvironment yield trials of twenty durum wheat genotypes were conducted at five locations of Iran (Gachsaran, Gonbad, Moghan, Ilam and Khorram abad) over four years (2009-2013). Combined ANOVA of yield data of the twenty environments (year/location combined) revealed highly significant differences among genotypes and environments as well as significant genotype-environment interaction indicated differential performance of genotypes over test environments. The GE interaction was examined using multivariate analysis technique as principal coordinate analysis (PCOA). According to grand means and total mean yield, test environments were grouped into two main groups as high mean yield (H) and low mean yield (L). There were eleven H test environments and nine L test environments which analyzed in the sequential cycles. For each cycle, both scatter point diagram and minimum spanning tree plot were drawn. The identified most stable genotypes with dynamic stability concept and based on the minimum spanning tree plots and centroid distances were G12 (3342 kg ha-1), G10 (3470.3 kg ha-1), G5 (3203.0 kg ha-1), and G1 (3263.5 kg ha-1), and therefore could be recommended for unfavorable or poor conditions. Genotypes G10 (3470.3 kg ha-1) and G9 (3404.2 kg ha-1) were located several times in the vertex positions of high cycles according to the principal coordinates analysis (PCOA) and therefore could be recommended for favorable or rich conditions. Finally, the results of principal coordinates analysis in general confirmed the breeding value of the genotypes, obtained on the basis of the yield stability evaluation.

Integrating different stability models to investigate genotype × environment interactions and identify stable and high-yielding barley genotypes

Barley is the fourth largest grain crop globally with varieties suited to temperate, subarctic, and subtropical areas. The identification and subsequent selection of superior varieties are complicated by genotype-by-environment interactions. The main objective of this study was to use parametric and non-parametric stability measures along with a GGE biplot model to identify high-yielding stable barley genotypes in Iran. Eighteen barley genotypes (16 new genotypes and two control varieties) were evaluated in a randomized complete block design with four replications at five locations over three growing seasons (2013–2014, 2014–2015, 2015–2016). The combined analysis of variance indicated that the environment main effect accounted for > 69% of all variation, compared with < 31% for the combined genotype (G) and genotype-by-environment interaction effects. The mean grain yield of each genotype across the five test sites and three seasons ranged from 1900 to 2302 kg ha−1. Using Spearman’s rank correlation and principal component analyses, the stability measures were divided into three groups: the first included mean yield, TOP and b, which are related to the dynamic concept of stability, the second comprised θi, W 2 , σ 2 , CVi, $$S_{di}^{2}$$ , KR, and the non-parametric measures, S(i) and NP(i), which are related to the static concept of stability, and the third included θi and R2. The GGE biplot analysis indicated that, of the five test locations, Gonbad and Moghan had the most discriminating and representative environments. Hence, these locations are recommended as ideal test locations in Iran for the selection of superior genotypes. The numerical and graphical methods both produced similar results, identifying genotypes G12, G13, and G17 as the best material for rainfed conditions in Iran; these genotypes should be promoted for commercial production.

Reoperation rates and risk factors for revision 4 years after dynamic stabilization of the lumbar spine

Background ContextThe concept of dynamic stabilization (DS) of the lumbar spine for treatment of degenerative instability has been introduced almost two decades ago. Dynamic stabilization follows the principle of controlling movement in the coronal plane by providing load transfer of the spinal segment without fusion and, at the same time, reducing side effects such as adjacent segment disease (ASD). So far, only little is known about revision rates after DS due to ASD and screw loosening (SL). PurposeThe present study aimed to evaluate the longitudinal revision rates following dynamic pedicle screw stabilization in the lumbar spine and to determine specific risk factors predictive for ASD, SL, and overall reoperation in a large cohort with considerable follow-up. DesignWe carried out a post hoc analysis of a prospectively collected database in a level I spine center. Patients ExampleThe patient sample comprised 283 (151 female/132 male) consecutive patients suffering from painful degenerative lumbar segmental instability with or without spinal stenosis who underwent DS of the lumbar spine (Ulrich Cosmic, Ulrich Medical, Ulm, Germany) between January 2008 and December 2011. Outcome MeasuresLongitudinal reoperation rate and risk factors predictive for revision surgery were evaluated. MethodsWe analyzed the longitudinal reoperation rate due to ASD and SL and overall reoperation. Risk factors such as age, gender, body mass index, lumbar lordosis (LL), number of segments, and number of previous surgeries were taken into account. Regular and mixed model logistic regressions were performed to determine risk factors for revision surgery on a patient and on a screw level. ResultsThe mean age was 65.7±10.2 years (range 31–88). One hundred thirty-two patients were stabilized in 1 segment, 134 in 2 segments, 15 in 3 segments, and 2 patients in 4 segments. Reoperation rate for ASD and SL after 1 year was 7.4 %, after 2 years was 15.0%, and after a mean follow-up of 51.4±15 months was 22.6%. Reasons for revision were SL in 19 cases (6.6%), ASD in 39 cases (13.7%), SL and ASD in 6 cases, hematoma in 2 cases (0.7%), cerebrospinal fluid fistulae in 3 cases (1.1%), infection in 6 cases (2.1%), and implant failure in 1 case (0.4%). The patients' age, the number of stabilized segments, and the number of previous surgeries and postoperative LL had a significant influence on the probability for revision surgery. ConclusionsReoperation rates after DS of the lumbar spine are comparable with rigid fixations. The younger the patient and the more segments are involved, the lower the LL and the more previous surgeries were found, the higher was the risk of revision. Risk of revision was almost twice as high in men compared with women. We therefore conclude that for clear clinical indication and careful evaluation of preoperative imaging data, DS using the Cosmic system seems to be a possible option. The presented data will help to further tailor indication and patient selection.

The use of parametric and non-parametric measures for selecting stable and adapted barley lines

ABSTRACTThis research was carried out to estimate yield stability of 18 barley breeding lines using different parametric and non-parametric statistics across 15 environments during 2012–2015 growing seasons. The results of combined analysis of variance (ANOVA) and additive main effect and multiplicative interaction (AMMI) analysis showed that environments (E), genotypes (G), GE interaction, as well as the first four interaction principal component axes were highly significant, suggesting that the lines interacted differentially with environments, so further general adaptability and stability analysis across environments should be followed before being introduced for cultivation. Based on correlation coefficient and principal components analysis (PCA), most of the non-parametric statistics were significantly inter-correlated with parametric statistics, hence seem to be suitable alternatives to complement parametric statistics. Furthermore, according to the static and dynamic concepts of stability, the results revealed that stability statistics can be clustered into three groups. The overall stability analysis following different stability methods concluded that four lines (G5, G7, G17 and G20) were highly stable for grain yield in rain-fed conditions of subtropical regions of Iran. Thus, these lines can be recognized as the most stable lines for cultivation in diverse environments of semi-warm regions of Iran.

Genotype by environment interaction and yield stability in sugarcane

Genotype by environment interaction (GEI) reduces the association between phenotype and genotype which result in relative ranking and stability differences of genotypes across environment. The objectives of this research were (i) to select sugarcane genotypes of high yield and stable (ii) to study the interrelationships among various parametric and no parametric stability statistics. Seventeen experimental genotypes and three check cultivars of sugarcane were evaluated at seven environment using randomized completely block design. Methodologies based on analysis parametric (Regression-bi-S 2 d i , Shukla variance, Ecovalence-W, Coefficient of variation-CV, index of Lin and Binns-PI and AMMI value) and non-parametric statistics (Nassar and Huehn- Si (1) , Si (2) , Si (3) , Si (6) , Kang-RS, Fox-TOP, and Thennarasu- NPi (1) , NPi (2) , NPi (3) , NPi (4) ) were used for Ton of Pol per hectare (TPH). Genotypes and environment showed high significant difference ( P <0.01) while GEI was significant ( P <0.05). The parametric stability analysis identified the genotypes V99-236 and V00-50 as the most stable and high TPH. With non-parametric statistics were identified the genotypes V00-50, V99-236 and V98-120 as most stable. The analysis distinguished two groups of statistics using biplot: the first group (G1) formed by PI, CV, ASV, TOP, Si (3) , Si (6) , NPi (2) , NPi (3) and NPi (4) statistics were located under the concept of dynamic stability since they are associated with TPH. The other group (G2), formed by Shukla, W, S 2 d i , bi, RS, Si (2) , Si (1) , NPi (1) statistics, fell within the static concept. Finally, genotypes V99-236 and V00-50 can be recommended as the most stable genotype in terms of both, stability and TPH.

Nonparametric statistical methods for analysis of genotype × environment interactions in plant pathology

Host genotype × environment (GE) interaction is a commonly observed phenomenon in experiments in plant pathology and can be analysed using different statistical models which can include parametric or nonparametric methods. Using data based on ordinal scales (commonly used to measure disease in plant pathology) or continuous scales, the disease responses of host genotypes across environments and resulting GE interactions have been analysed using 26 different nonparametric methods. An analysis of two datasets for severity of gray leaf spot of maize (10 northern or southern adapted genotypes planted at 10 or 11 locations in the US, respectively) revealed differences among host genotypes, environments and the GE interactions. A factor analysis was performed on the rank correlation matrix arising from the application of each nonparametric method. The 26 methods can be categorized, for both sets of experimental data, in two major groups: (i) those which are mostly associated with level of disease severity and show little or no correlation with the static type of stability concept, and (ii) those in which both level of disease severity and stability of performance are considered simultaneously to reduce the effect of the GE interaction. This analysis separated nonparametric methods based on a dynamic concept of stability from those which are based on the static type of stability. Comparison of original and corrected nonparametric statistics indicated that, the identification of the most resistant cultivar for a specific environment based on both genotype and GE interaction would be useful to plant pathologists since estimates based only on genotype and environment effects are insufficient. Following measures based on corrected Ketata’s rank, original Ketata’s rank, Fox’s statistic and rank-sum, the NP2 statistic of Thennarasu (average of summation of absolute values of adjusted ranks from the median) was found to be useful in detecting the phenotypic stability of disease severity in a dataset. Nonparametric methods can be useful alternatives to parametric methods and allow valid conclusions to be drawn while assessing the GE interaction in experiments undertaken in plant pathology or plant breeding.

Reported Clinical Outcomes of Coflex Dynamic Stabilization Device Vs Instrumented Decompression and Fusion in Degenerative Lumbar Stenosis

Introduction: The concept of dynamic stabilization” or “soft stabilization” was introduced with aim to provide a solution to problems related with spinal fusion. In theory, dynamic stabilization system should provide sufficient support at the inserted level allowing for load transmission of a spinal motion segment, without major restriction to motion at the affected segment allowing to relieve pain and avoiding adjacent level disease encountered with spinal fusion. Methods: Assessment of outcomes of Coflex dynamic stabilizers versus decompression and Mild to moderate degree lumbar degenerative foraminal stenosis was assessed in a prospective study between February 2008 and December 2011 at the Queen Elizabeth the Queen Mother Hospital, East Kent NHS Trust, Margate, Kent. Validated pain rating scale, Oswestry disability questionnaire, and operative data were used to compare outcomes. Results: 208 patients were included in this study. 121 patients were treated with decompression and Coflex dynamic stabilization (Group I) and 87 patients were treated decompression and lumbar fusion (Group II). All patient included were followed for a minimum period of 2 years (2 - 3.9 Years). The Majority of patients were satisfied with the results in the immediate postoperative period with 82% of patients happy with surgical outcome. Visual analogue score results improved in both groups with a mean preoperative VAS score 8.4, 4 at one year 3.2 for the decompression and coflex group (p<0.001) Conclusion: The Coflex@ inter-spinous implant is a simple surgical treatment strategy with a low risk. Early results show a good improvement of both clinical and radiological parameters.

EVALUATION OF GENOTYPE BY ENVIRONMENT INTERACTION FOR GRAIN YIELD IN DURUM WHEAT USING NON-PARAMETRIC STABILITY STATISTICS

If genotype (G) ranks change from one environment (E) to another, genotype by environment interactions (GEI) reflects the need for testing Gs in numerous Es in order to obtain reliable results. The aim of this study was to compare 16 non-parametric stability statistics (NPSSs) for GEI on grain yields of 15 durum wheat genotypes, consisting of 11 advanced lines selected from Turkish National Durum Wheat Breeding Program (TNDWBP) and four checks, tested in 12 rain-fed environments during the 2 cropping seasons (2009–2010 and 2010-2011) in Turkey. The combined ANOVA indicated that G, E and GEI effects were significant for grain yield. According to analyses of NPSSs, the highest in ranking (TOP), percentage of adaptability (PA), rank mean (RM) and yield-stability (YS) statistics were positively associated with grain yield and therefore characterized under the dynamic concept of stability. In addition, spearman rank correlation analysis revealed that only TOP, PA, RM and YS statistics would be useful for simultaneous selection for high grain yield and stability. Based on the 16 NPSSs used in this study, Dumlupinar cultivar (G15) was both the most stable and one of the highest yielding ones. On the other hand, G5 and G7 were the most stable ones among the advanced lines tested, but their yield performances were lower. As a result, this study showed that the crossing block of TNDWBP should be enriched by germplasm being capable of dynamic stability, wide adaptation and higher yielding.

Posterior dynamic stabilization: The interspinous spacer from treatment to prevention.

Introduction:Managements of lumbar stenosis evoluted over the time from decompression to dynamic stabilization preserving the motion segment passing by the rigid fixation. After long years of rigid fusion, adjacent segment disease became more and more frequent and the concept of dynamic stabilization emerged.Materials and Methods:We report our experience with posterior dynamic stabilization using an interspinous distracter (ISD). One hundred and eight patients were operated between September 2008 and January 2012 with different lumbar spine pathologies. The ages of our patients were between 45 years and 70 years, with a mean age of 55 years. With our growing experience, indication of ISD became narrowed and the interspinous spacer became an absolute tool for adjacent segment disease as a treatment as well as prophylactic with rigid stabilization.Results and Discussion:Overall clinical improvement was noted in ISD-treated patients, with considerable satisfaction in 77% of patients on average. The patient at first reported an improvement of their radicular pain with a mean reduction of 3.6/10 on visual analog scale. Post-operative walking distance progressively increased during the next 3 months. Whereas, a radiological evaluation at 3 months showed a mean of 42% improvement of the disc height. On the other hand, all patients operated with posterior dynamic stabilization (PDS) at the time of rigid stabilization showed no adjacent segment disease compared to those operated with posterior arthrodesis (P < 0.05).Conclusion:Interspinous spacer after surgical decompression for spinal stenosis by excision of Ligamentum flavum demonstrates excellent short-term and long-term results for improvement in back pain, neurogenic claudication, and patient satisfaction. It provides restoration of disc height, reduction of vertebral slip and it's a necessary tool in the management and the prevention of adjacent segment disease.