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A computational procedure for identifying master regulator candidates: a case study on diabetes progression in Goto-Kakizaki rats
Guanying Piao1,2,
Shigeru Saito3,4,
Yidan Sun5,2,
Zhi-Ping Liu2,6,
Yong Wang6,
Xiao Han5,
Jiarui Wu1,2,
Huarong Zhou2,
Luonan Chen2,3 &
Katsuhisa Horimoto3
We have recently identified a number of active regulatory networks involved in diabetes progression in Goto-Kakizaki (GK) rats by network screening. The networks were quite consistent with the previous knowledge of the regulatory relationships between transcription factors (TFs) and their regulated genes. To study the underlying molecular mechanisms directly related to phenotype changes, such as diseases, we also previously developed a computational procedure for identifying transcriptional master regulators (MRs) in conjunction with network screening and network inference, by effectively perturbing the phenotype states.
In this work, we further improved our previous method for identifying MR candidates, by listing them in a more reliable manner, and applied the method to reveal the MR candidates for diabetes progression in GK rats from the active networks. Specifically, the active TF-gene pairs for different time periods in GK rats were first extracted from the networks by network screening. Another set of active TF-gene pairs was selected by network inference, by considering the gene expression signatures for those periods between GK and Wistar-Kyoto (WKY) rats. The TF-gene pairs extracted by the two methods were then further selected, from the viewpoints of the emergence specificity of TF in GK rats and the regulated-gene coverage of TF in the expression signature. Finally, we narrowed all of the genes down to only 5 TFs (Etv4, Fus, Nr2f1, Sp2, and Tcfap2b) as the candidates of MRs, with 54 regulated genes, by merging the selected TF-gene pairs.
The present method has successfully identified biologically plausible MR candidates, including the TFs related to diabetes in previous reports. Although the experimental verifications of the candidates and the present procedure are beyond the scope of this study, we narrowed down the candidates to 5 TFs, which can be used to perform the verification experiments relatively easily. The numerical results showed that our computational method is an efficient way to detect the key molecules responsible for biological phenomena.
Recent developments in genome-wide computational analyses have successfully identified causal interactions [1], and showed promise in the identification of dysregulated genes in development and tumor progression pathways [2]. For example, a computational analysis procedure was applied to identify the MRs causally linked to the activation of a specific gene set, mesenchymal gene expression signature (MGES), in human malignant glioma [3]. Indeed, 53 TFs were obtained by the ARACNe algorithm and the MGES enrichment test, and among them, the top 6 TFs with the largest fraction of MGES genes were experimentally controlled, as the MR candidates. Finally, 2 of the top 6 TFs, STAT3 and CEBPB, were experimentally verified as MRs of mesenchymal transformation. Unfortunately, the computational method employed in the previous work was unsophisticated and required further improvement. For example, it is unclear why the method selected the top 6 TFs from 53 TFs, rather than 5 or 7 TFs. Although the coverage of the TFs for the MGES genes was carefully considered, there was no rational criterion for the final selection of the MR candidates. Furthermore, ARACNe considers the relationships between three genes for selecting MR candidates. However, there are some well known mathematical techniques that consider multiple relationships and have been applied to infer regulatory networks [4].
We previously reported 39 candidates of active networks for diabetes progression in the Goto-Kakizaki rat (GK), which were identified by network screening, in comparison with the Wistar-Kyoto (WKY) rat [5]. Network screening is a procedure to extract the regulatory networks activated under particular conditions, based on the known regulatory networks [5–7]. The candidates were characterized by the known biological pathways that were consistent with the previous knowledge about diabetes. Unfortunately, the plausibility of the active networks could not be verified experimentally. This was partly because the results were presented in a metaphysical form, and as the biological pathway, instead of the list of concrete target genes. Actually, the active networks were composed of many genes that were not amenable to experimental verification.
To overcome these problems, we recently developed a procedure for identifying MR candidates, by a combination of network screening and network inference [8]. The network screening strongly depends on the previous knowledge of the regulatory networks. To compensate for the limitations of network screening, we introduced a network inference method, which is a version of a path consistency algorithm (PC-A) [9] or a modified PC-A [10, 11] that applies PC-A to biological data with high redundancy. The performance of our procedure was tested for MRs in human malignant glioma, using the same data set in ref. [3], and worked well [8]. In total, 22 TFs and 27 TFs were detected by the network screening and the network inference, respectively, and 3 TFs overlapped between them. Interestingly, 2 of the 3 TFs were STAT3 and CEBPB, which were verified experimentally as the master regulators in the previous report [3].
In this paper, we sought to identify the candidates of master regulators for diabetes progression, using the spontaneous diabetic GK rat model. Based on the networks specific to diabetes progression identified in our previous report [5] and the networks inferred by the modified PC-A, we intended to narrow down the candidate molecules responsible for diabetes further, by identifying the master regulators that play a central role in diabetes progression in GK rats. Furthermore, we improved our previous method [8] to narrow down the candidates in a more reliable manner, by considering the coverage of a TF for its regulated genes in a statistical manner, in addition to the specificity of the TF to the target biological phenomena. As expected from the previous case of the computational identification of MRs in a human brain tumor [8] and the present improvements, we identified a limited set of reliable MR candidates, and thus provided information for further experimental design for candidate verification.
Overview of our computational procedure
In our computational procedure, we identified MR candidates by two approaches, which are schematically shown in Figure 1. One is a knowledge-based approach, which estimates the consistency of the network structures among the known networks with the measured data (named "network screening") [5–7]. The other is a data-driven inference approach, which estimates the conditional independency between the genes by calculating the partial correlation coefficients (named "modified path consistency algorithm") [10, 11]. In both cases, we further selected the MR candidates by considering the enrichment of the gene expression signature in the networks. Finally, we refined the candidates by considering the TF specificity and the regulated-gene coverage. The details are described in the Methods.
Workflow of the MR identification procedure.
MR candidates detected by network screening
In our previous study [5], we used network screening to identify 39 networks for GK and WKY rats in three growth periods: 4w, from 8w to 12w, and from 16w to 20w, among the 1,760 networks in the reference network set. Based on these results, we further selected the MR candidates. From the 39 networks, in total, we extracted 568 binary relationships of TFs and their regulated genes, which were specifically found in the three periods for GK and WKY rats, under the condition that the gene expression shows a difference with a false discovery rate (FDR) of less than 0.05, between the two strains of rats for each period (see the details in the Methods). The numbers of genes specifically found in each period in GK and WKY rats are as follows: 54 genes at the period of 4w in GK; 199 at 8w and 12w in GK; 56 at 16w and 20w in GK; 95 at the period of 4w in WKY; 125 at 8w and 12w in WKY; and 39 at 16w and 20w in WKY. Note that some TF-gene relationships emerged iteratively for different periods in GK and WKY rats.
Among the TF-gene relationships selected above, the TFs were narrowed down in two ways. First, the TF-gene relationships were selected by the specificity, which means that the TFs emerge only in GK, but not in WKY. As a result, we found a total of 21 TFs, as shown in Table 1. Second, the TF-gene relationships were selected by the coverage, which means how many genes the TFs regulate, among the genes in the expression signature. The TFs thus selected were sorted according to the coverage, and then the MR candidates were further selected by a statistical test (see the Methods) for each period in GK and WKY listed in Table 2. As seen in the table, most of the TFs emerged in both GK and WKY, in terms of the coverage selection. We finally found 3 TFs (EGR1, NRF1, and TCFAP2A) among the genes by the initial selection in Table 2.
Table 1 TFs identified by network screening in terms of specificity.
Table 2 TFs identified by network screening in terms of coverage.
MR candidates inferred by the modified path consistency algorithm
We first inferred six networks of all genes on the microarray for each of the three periods in GK and WKY rats, by the modified path consistency algorithm [10, 11], and then the TF-gene relationships were extracted from each network. After the extraction, only the relationships that included the genes with a significant difference between GK and WKY rats were further selected for the 6 sets of relationships.
Using the same procedure as that described in the preceding subsection, the TFs were narrowed down. First, we chose the relationships in terms of the gene-emergence specificity. As a result, 108 TFs were identified as the MR candidates in Table 3. The number of candidates seems to be large, even in comparison with the candidate number, 27 TFs, in the previous case of the brain tumor [3]. While one network was considered to identify the candidates in the previous paper, three networks for the three periods in GK rats were surveyed to select the candidates in the present study. Thus, the number of TFs extracted from one network, 36 TFs on average, is similar to that in the previous study. Second, the TF-gene relationships were selected by the coverage. We chose the TF-gene relationships by a statistical test (see the details in the Methods) for each period in GK and WKY, as shown in Table 4. In contrast to the coverage selection in network screening, only a few TFs emerged in both GK and WKY. Indeed, among the 44 TFs in Table 4, only two TFs (Tbpl1 and Cbfb) emerged in both GK and WKY. Finally, we found 42 TFs as MR candidates.
Table 3 TFs identified by network inference in terms of specificity.
Table 4 TFs identified by network inference in terms of coverage.
MR selection by comparison of the TF sets detected by the two methods
We obtained the final MR candidates by selecting the overlapped TFs detected by the two methods in terms of two criteria (Tables 1, 2, 3, 4), as shown in Table 5. Indeed, 21 TFs detected by network screening in terms of specificity overlapped with only 4 TFs (Etv4, Nr2f1, Sp2, and Tcfap2b) and 2 TFs (Fus and Sp2) by the modified path consistency algorithm by two criteria, respectively. In contrast, 3 TFs detected by network screening in terms of coverage showed no overlapped TFs by the path consistency algorithm by two criteria. This difference might reflect the restriction of the known TF-gene relationships in network screening.
Table 5 Summary of TFs identified by the two methods, in terms of specificity and coverage.
As a result, we merged the MR candidates identified by the two methods, and 5 TFs were finally identified as the candidates of MRs for diabetes progression in GK rats. Note that Sp2 emerged in both the 4 TFs and 2 TFs. The 5 final MR candidates with their regulated genes, in total 54 genes, are listed in Table 6.
Table 6 Candidates of MRs and their regulated genes for diabetes progression in GK rat.
In this study, we have identified the candidates of master regulators based on our previous study [5], by using an improved method for their identification [8]. The MR candidates were extracted from the active networks of many genes characterized by biological pathways, as the feasible gene candidates for experimental verification. From the methodological aspect, the method was improved by considering the coverage of TFs in a statistical manner, in addition to the specificity that was considered in the previous method. Although the experiments are beyond the scope of the present study, we consider experimental verification studies of the present candidates as our future research topic. Our study clearly illustrated a rational way to narrow down the genes of MR candidates, and is fundamentally different from metaphysical presentations, such as biological pathways or large network forms.
Our study intended to identify the MR candidates, which are those genes with large impacts on phenotype changes, in a biological sense [3]. Here, we logically identified MR candidates by the specificity of the TF appearance and the coverage of the regulated genes to the gene expression signature in the networks of GK and WKY rats. Apart from a biological sense, we further investigated the meaning of "master" from the viewpoint of the network structure. To do this, we revealed the hierarchical structures of the 8w-12w and 16w-20w networks by network screening, using a vertex sort algorithm [12], and allocated the present 5 TFs into the hierarchical structures (Figure 2A). As seen in the figures, all 5 TFs were allocated into the highest level. Indeed, Nr2f1 in the 8w-12w network and Tcfap2b in the 16w-20w network were definitely allocated into the highest level of the hierarchical structures. In addition, the remaining TFs were allocated into the levels including the highest and middle levels, but not into the lowest level. Furthermore, we investigated the hierarchical structure by another method, the BFS-level algorithm [13]. As shown in Figure 2B, the positions of the MR candidates are similar to those in Figure 2A. Indeed, previous hierarchical analyses of the regulatory networks by the BSF method in Escherichia coli and Saccharomyces cerevisiae suggested that the MRs were in the middle of the hierarchy [13]. In general, the vertex sort algorithm reports a linear ordering of nodes that contains all feasible solutions, while the BSF-level algorithm reports just a single solution, as shown in Figures 2A and 2B. Subsequently, unlike the BFS-level algorithm, the ordering in the vertex sort algorithm permits nodes to span an entire interval of possible positions with any feasible ordering. Despite this difference in the computational algorithms, the 5 TFs showed the common property as MRs. At any rate, although the verification experiments remain to be performed for the justification of the MRs in a biological sense, the 5 TFs may be regarded as the plausible MR candidates from the viewpoint of network structure.
Hierarchical structures of networks for 8w-12w and 16w-20w by two previous methods. The 5 TFs are indicated at the levels in hierarchical structures obtained by the vertex-sort algorithm (A) [12] and those by the BFS method (B) [13], and the numbers of TFs in each level are indicated in parentheses in (A), and by red circles in (B). In (B), the TFs and the regulated genes are indicated by diamonds and rectangles, respectively.
A preliminary survey revealed that all 5 of the TFs have no reported causal relationship to diabetes. The 5 TFs are sequence-specific DNA-binding proteins, and they function as both transcriptional activators and repressors of large numbers of genes that are closely related to the cell cycle and tumorigenesis. Notably, the relationships of ETS translocation variant 4 (Etv4) and transcription factor AP-2 beta (Tcfap2b) to adipogenesis, which is strongly related to diabetes, have been reported, together with their association with the other pathways [14, 15]. Nuclear Receptor subfamily 2, group F, member 1 (NR2F1) is a member of the steroid hormone receptor family, and has been shown to interact with estrogen receptor alpha (ESR1) [16]. There is a gender difference in the incidence of type 2 diabetes, which is largely due to the role of the sex hormone estrogen. The Sp family proteins, containing the conserved DNA-binding domain, are localized primarily within subnuclear foci associated with the nuclear matrix. Recent unpublished data from our lab have shown that another Sp family member, Sp1, has a major impact on the insulin signaling pathway. The Sp2 transcription factor interacts with E2F1, which mediates both cell proliferation and p53-dependent/independent apoptosis [17]. The recently discovered close relationships between diabetes and tumors in terms of these TFs are quite likely to play a crucial role in the control of diabetes. RNA-binding protein (FUS) is able to bind DNA, RNA and protein [18]. The interactions between the FUS recognition sites and Tcfap2, GCF, and Sp1 were identified recently. Thus, although direct evidence was not found in the previous knowledge, the 5 TFs are expected to be MR candidates, in consideration of the circumstantial evidence of their relationships to diseases, the hierarchical analysis of the 5 TFs, and the successful discovery of new MRs in brain tumor, by the previous version of the procedure. Actually, our current information in terms of important diabetes-related genes includes mostly functional proteins, located at the lowest level of our hierarchical structure, while the MR is deeply hidden and therefore must be revealed by systems biology methods. Thus, in addition to analyses of their regulated genes, some experimental verification of the MR candidates may be desirable to further examine their plausibility as MR candidates for diabetes progression.
In this work, using our new method, we identified the MR candidates for diabetes progression, 5 TFs and their regulated genes, in GK rats. This number of candidates is very small, and thus the results can be used as a basis for biological experiments for verification. Furthermore, the recent availability of the next-gen sequencer may provide another way to confirm the effectiveness of our method, and to test its performance further with other datasets. Indeed, RNA-seq and ChIP-seq are useful for more accurate measurements of gene expression, and yield detailed information about the regulated genes. Thus, the combined use of the two approaches may compensate for the pitfalls inherent in each method, and will provide important clues about the transcriptional networks that regulate transitions into physiological or pathological cellular states.
Network screening
The candidates of the active regulatory networks were detected by network screening [5–7]. Here, we briefly summarize the network screening in the present study, as follows.
First, the regulatory network sets were generated in the same manner as in the previous study [5], as follows. The mouse binary relationships compiled in the TRANSFAC database [19] were used. Based on the correspondence between the mouse and rat gene ids, 3,015 binary relationships of 1,507 genes between 503 TFs and 1,123 regulated genes were achieved. Based on those binary relationships, transcriptional networks were constructed according to the functional gene sets previously defined in the Molecular Signatures Database (MSigDB) [20]. In each gene set, the regulated genes in the binary relationships were searched, and if at least one gene was found in the gene set, then the corresponding binary relationships were regarded as a regulatory network characterized by the gene set. In present study, the reference network comprised 1,760 regulatory networks characterized by biological functions that are composed of 1,195 genes. The numbers of TFs and regulated genes were 335 and 860, respectively.
Then, we calculated the graph consistency probability (GCP) [6], which expressed the consistency of a given network structure with the monitored expression data of the constituent genes in this study. The consistency of a directed acyclic graph (DAG), G(V i , E j ), where V i is a vertex (i = 1, 2, ..., nv) and E j is an edge (j = 1, 2, ..., ne) in the graph, and the joint density function f (X i ), corresponding to V i for the graph G with the measured data, is quantitatively expressed by the logarithm of the likelihood based on the Gaussian graphical model (GN: Gaussian Network), i.e.,
l ( G 0 ) = ln ∏ i = 1 n v f X i | p a X i = - 1 2 ∑ i = 1 n v ∑ j = 1 n i 1 σ i 2 ∑ k = 1 m x i k - ∑ j = 1 n i β i j x k j 2 + ln 2 π σ i 2 ,
where pa{X i } is the set of variables corresponding to the parents of V i in the graph, x ik is the measured value of X i , at the k-th point, and n i is the number of variables corresponding to the parents of V i . Since the likelihood depends on the graph size, we designed a simple procedure to transform the likelihood to the probability for the expression of the graph consistency with the data [6]. First, we generated N r networks under the condition that the networks shared the same numbers of nodes and edges as those of the given networks. Then we defined GCP, as follows,
G C P = N s N r ,
where N s is the number of networks with larger log-likelihoods than the log-likelihood of the tested network. In the present study, N r was set to 2,000, and the GCP significance of the given network was set at 0.05.
Path consistency algorithm
The path consistency (PC) algorithm [9] is an algorithm to infer a causal graph composed of two parts: the undirected graph inference by a partial correlation coefficient and the following directed graph construction by the orientation rule. The present method partially exploits the first part of the PC algorithm for the inference of the network structures. A simple example of the PC algorithm is illustrated in Figure 3.
Example of the path consistency algorithm.
We assume that five variables, X1, X2, X3, X4, X5, have the following five relationships: i) X1∐X2,
ii) X2∐ (X1, X4),
iii) X3∐X4|(X1, X2),
iv) X4∐ (X2, X3)|X1, and
X5∐ (X1, X2)|(X3, X4),
where the symbol, ∐, in the above relationships, means the independence between variables. The PC algorithm reconstructs the above relationships as follows.
1) Prepare a complete graph, C, between the five variables.
2) Test the correlation between two variables by calculating the zeroth-order of the partial correlation coefficient (Pearson's correlation coefficient). From the test, two variable pairs, (X1, X2) and (X2, X4), are excluded (dashed lines in Figure 2), due to the relationships, i) and ii).
3) Test the correlation between three variables by calculating the first-order of the partial correlation coefficient of the variable pairs, given one variable. Then, one variable pair, (X3, X4), is further excluded from the updated graph by 2), due to iii) and iv).
4) Test the correlation between four variables by calculating the second-order of the partial correlation coefficient of the variable pairs, given two variables. Then, two variable pairs, (X1, X5) and (X2, X5), are excluded, due to iv).
5) We could not find any edges adjacent to the three edges in the updated C. Thus, the algorithm naturally stops. As seen in the final graph, the five relationships emerged completely.
In general, the (m-2)-th order of the partial correlation coefficient is calculated between two variables, given (m-2) variables; i.e., r ij, rest , between X i and X j , given the 'rest' of the variables, {X k } for k = 1, 2, ..., m, and k≠i, j, and after calculating the (m-2)-th order of the partial correlation coefficient, the algorithm naturally stops. However, the algorithm does not usually request the (m-2)-th order of the correlation coefficient for the natural stop. This is because after excluding the variables, the adjacent variables are often not found, even in the calculation of the lower orders of partial correlation coefficients.
Modification of the path consistency algorithm for microarray data analysis
In the actual expression profile data, many genes frequently show profiles with similar patterns. This makes the numerical calculation of correlation coefficients difficult, due to the multi-colinearity between the variables. The original PC algorithm accidentally stops, if only one correlation between a pair of variables shows a violation of the numerical calculation. However, in a biological sense, the gene pairs that cause the accidental stop can be interpreted as a case of their high association with each other, in terms of gene expression. Thus, we modified the original PC algorithm to prevent it from accidentally stopping with the highly associated gene pairs, as follows [10, 11]. If the calculation of any order of the partial correlation coefficient between the variables is violated, then the corresponding pair of variables is regarded as being dependent. For example, if the first-order correlation coefficient, r ij, k , cannot be calculated numerically, due to the multi-colinearity between X i and X j , then the edge X i -X j is kept without the statistical test. The other parts remain unchanged in the modified algorithm. Note that the above modification ensures that the algorithm will naturally stop for the data including a high correlation.
As seen in the original algorithm, the output is not unique, depending on the calculation order of pairs [9]. A permutation test for the calculation order is a convenient way to partly resolve this issue. In this study, the estimation without permutation was empirically adopted as the first approximation, based on the successful estimations of the relationships in our previous studies [10, 11]. In addition, one of the most remarkable features of the PC algorithm is that the algorithm removes the pseudo-correlations between the variables (genes) by considering the higher-order partial correlations. If we have the measurement data for a complex network, then we frequently face the more serious issue of the pseudo-correlation, rather than the correlation level. The merit of the PC algorithm may be its ability to identify real relationships between TFs and their regulated genes.
Definition of MR candidates by network screening and network inference
We first referred to two sets of networks obtained by the network screening [5–7] and the network inference [10, 11]. From each network set, the binary relationships between the TFs and their regulated genes were extracted, only if the regulated genes were included in the expression signature, which is the ensemble of genes with significant differences in gene expression, as statistically estimated by the false discovery rate (FDR) test for multiple comparisons (FDR < 0.05) [21]. In the extraction of TFs and their regulated genes, the TF was also cited from the TRANSFAC database [19], but the expression degree of the TF was not considered, due to the small expression changes even under different conditions. Only the regulated genes that were estimated to directly bind TFs were extracted. The numbers of genes in the three gene expression signatures of the three periods (period of 4w, period of 8w and 12w, and period of 16w and 20w) were 1,582, 2,719, and 2,777, respectively.
Then, we defined the MR candidates from the binary relationships by two criteria. One was the specificity of the TF, which was the same criterion as in the previous method [8], and the other was the coverage of the TF, which was newly introduced in the present MR candidate identification. Here, the specificity simply means that the TF emerged only in the GK networks, but not in the WKY networks. To select the TFs in terms of the specificity, we selected the TFs that emerged in the three periods in GK, but not in WKY, as the MR candidates. Note that in the selection of the TFs, we only selected those that were estimated to regulate the genes including the expression signature, to consider the enrichment of the regulated genes in the signature. The coverage means how many genes each TF regulates. To select the TFs in terms of the coverage, we first counted the genes regulated by each TF for each period in GK and WKY, and then also considered the enrichment of their regulated genes in the expression signature, by sorting the numbers of regulated genes for each case. To consider the coverage in a rational way, we used the Smirnov-Grubbs outlier test [22] for the numbers of regulated genes, by setting a threshold (p < 0.05). Thus, the TFs with the larger number of regulated genes that fulfilled the threshold are selected in a statistical manner. Finally, the two sets of MR candidates that were selected in terms of the specificity and the coverage were compared, to define the final MR candidates.
Data analyzed in this study
We analyzed the gene expression data measured in GK and WKY rats [23], which were cited from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/projects/geo/) database (GSE 13271). The data were composed of 31,099 probes that were measured by using Affymetrix Microarray Suite 5.0 (Affymetrix), and were further reduced into 14,506 genes, for 5 samples of male spontaneously diabetic GK rats and WKY controls at each of 5 time points (4, 8, 12, 16, and 20 weeks of age). In this analysis, the 5 periods were classified into three periods: period of 4w, period of 8w and 12w, and period of 16w and 20w.
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This work was supported by a grant, "Joint Seminar 2011 in NSFC-JSPS Scientific Cooperation Program". This work was also partly supported by a project grant, entitled "Development of Analysis Technology for Induced Pluripotent Stem (iPS) Cell" from NEDO of Japan; Major State Basic Research Development Program of China (973 Program) under No. 2011CB504003; NSFC under Nos. 61134013, 81070657, 31100949, 61072149 and 91029301; the Chief Scientist Program of SIBS of CAS under Grant No. 2009CSP002; the Knowledge Innovation Program of SIBS of CAS with Grant Nos. 2011KIP203 and KSCX2-EW-R-01; Shanghai NSF under Grant No. 11ZR1443100; and the SA-SIBS Scholarship Program.
School of Life Sciences, University of Science and Technology of China, Hefei, 230026, China
Guanying Piao & Jiarui Wu
Guanying Piao, Yidan Sun, Zhi-Ping Liu, Jiarui Wu, Huarong Zhou & Luonan Chen
Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, 135-0064, Japan
Shigeru Saito, Luonan Chen & Katsuhisa Horimoto
INFOCOM Corporation, Tokyo, 150-0001, Japan
Shigeru Saito
Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing, 210029, China
Yidan Sun & Xiao Han
National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China
Zhi-Ping Liu & Yong Wang
Guanying Piao
Yidan Sun
Zhi-Ping Liu
Xiao Han
Jiarui Wu
Huarong Zhou
Katsuhisa Horimoto
Correspondence to Jiarui Wu or Huarong Zhou or Luonan Chen or Katsuhisa Horimoto.
HZ, LC and KH conceived the research. SS, GP, YS and ZPL performed the study. JW, YW and XH provided valuable suggestions and improvements. HZ, LC and KH supervised the project. HZ, ZPL, SS and KH drafted a version of the manuscript. All authors wrote and approved of the manuscript.
Guanying Piao, Shigeru Saito contributed equally to this work.
Piao, G., Saito, S., Sun, Y. et al. A computational procedure for identifying master regulator candidates: a case study on diabetes progression in Goto-Kakizaki rats. BMC Syst Biol 6, S2 (2012). https://doi.org/10.1186/1752-0509-6-S1-S2
Network Inference
Variable Pair
Binary Relationship
Diabetes Progression


Bondgenotenlaan. Avenue of the Allies. Bondgenotenlaan. Avenue of the Allies. It's the main road through town so I must've said and heard this name hundreds of times in the four months I lived in Leuven. And probably thousands of times more after I moved back for four more years from 2002-2006. But despite, or maybe because of, it's daily presence in my life, the meaning of the name Bondgenotenlaan – Avenue of the Allies – remained hidden in a background I never thought to fully explore.
I just assumed it had something to do with World War II. Leuven was occupied by the Germans at that time and the university library was turned into a Nazi war-room, which the Allies bombed and later rebuilt using donations from American universities.
weren't those of my grandfather's generation. Rather, these were the men of 1914-18.
So what happened in Leuven during the First World War that I so clearly failed to see during my five years there?
On the first day of the occupation of Leuven "German soldiers behaved in exemplary fashion, bought postcards and souvenirs, paid for all their purchases, and stood in line with the regular customers for haircuts at the barbershop," she writes.
Then, on August 25, as German troops were marching west from Leuven they met the Belgian Army at Mechelen and were forced to return to Leuven.
The Germans said the Belgians had started shooting. The Belgians claimed the Germans were shooting at one another in the dark. Either way, Leuven was about to go off like a box of matches. The burning of the city began later that day. It was the German's way of punishing the Belgians for their disobedience and sending a warning to other would-be enemies that anything less that full cooperation would not be tolerated.
When I read this, I was shocked. Not simply by the heinous and hateful crimes against humanity that took place in Leuven. But also by how little there is today to remind us of what happened.
In other words, the Germans sought to strike at the very soul of a people. Not content to occupy another's land, they set out to erase their culture. This is the only way to understand the decision to burn Leuven's famed library, which housed over 230,000 books, 750 medieval manuscripts, and a thousand incunabula (early printed books dating from the 15th century). It was a purely symbolic move in service of a warped strategy.
On August 30, the day after reports of the madness appeared in the foreign press, the campaign to destroy Leuven ceased. The beautifully ornate Gothic town hall was still standing, and so too was St. Peter's Church. But the damage done to the rest of the city was irreversible.
When I think back to the first time I walked out of the train station there, and that first of many walks down the Bondgenotenlaan – the Avenue of the Allies – I can remember ambling very slowly, in absolute awe of my surroundings. My eyes didn't know where to look first. At the buildings nestled together in long rows of grand façades and bustling shop fronts? At packs of bikers peddling past me carrying on conversations in a language I longed to understand? At the people parked at sidewalk cafés taking it easy with a noontime beer?
Before I knew anything else about Leuven, the spirit of the place had moved me. It lit a fire in my heart and I knew then that, whatever it was, I wanted to be a part of it.


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text:
Q: Things to watch out for with OpenCL and GPU with permutations/hashing? I'm a total newcomer to OpenCL trying to find out the pros and cons of OpenCL and hashes.
Say, for example, I have a trivial hash function:
public static uint GetHash(string str)
{
  uint s = 21; // seed
  foreach (char ch in str)
      s = (s + (uint)ch) * 10;
  return s;
}

(I know this is a horrible hash, but it's just an example)
Now lets say I wish to calculate all permutations of characters a-zA-Z0-9_ out to a length of 50, so for example:
a
b
...
_
aa
ab
...
__

Obviously this is a huge number (63^50) of hashes I need to calculate, so I decide to use OpenCL and GPU computing.
My question is: are there any pitfalls that OpenCL/GPU computing brings? I've read the following:

*

*Transferring data across the PCIe bus is sloooooooowwwwwwwwwwwww

*Accessing global memory on the GPU is sloooooooooooowwwwww

*All "threads" in a warp must execute the same instructions

This makes me question the effectiveness of GPU computing in this case, because it seems to me that I'll need to use one of these approaches:

*

*Have each thread calculate its own permutation (violates #3 because each thread would have a different number of increments to do)

*Have each thread preform one increment that affects all other threads (violates #2)

*Calculate permutations on the CPU and dispatch them to the GPU (violates #1, plus then I'm basically just using the GPU to calculate a hash...)

Are those conclusions accurate? If not, why, and is there anything else to watch out for?

A: Slow is a relative term.  But generally, you want to avoid transferring huge amounts of data to and from the GPU, or to put it another way, you have to make the cost of the data transfer 'worth it' by doing a decent amount of calculations on the GPU before you transfer the result back off.
So, looking at your problem as you current have stated it (as I understand), you want to:

*

*Generate each possible string on the host (CPU)

*Transfer the original strings to the GPU

*Calculate the hashes of these strings in parallel on the GPU

*Transfer the calculated hashes back to the host (CPU)

This will run poorly, because the calculation of the hash is computationally fairly trivial and the majority of time will be spent performing data transfer.
Definitely you want to generate the string permutations on the GPU - this will avoid the cost of (2).  Splitting these up into work items should not be too hard.  If you have a base string, e.g. 'aaaa', and have, say, 4 dimensions for each suffixed character, then calculate the hash in each thread (depending on the hash function, you could also make huge savings if the hash of the prefix 'aaaa' can be precalculated once and reused) and put that in the output.
But I suspect this approach would still bottleneck at transferring the generated hashes back to the host.  If there is something you need to do with the hashes afterwards, such as check for equality against a known hash, you can do this on the GPU as well, avoiding all those costly data transfers because all you would need to write back is the single matching (or maybe a few matches) string/result hash to global memory and not 63^50.

redpajama_set_name: RedPajamaStackExchange


text:
International Data Flows: EU and UK data flows: The Future of the Post-Brexit Agreement
As detailed by The Law Society in the UK, "The outward flow of data from the UK to the EU/EEA remains unaffected since the UK government has determined that it considers all EU 27 and EEA member states to be adequate for the purposes of data protection."
The UK Data Protection Index is produced by Data Protection World Forum and The DPO Centre. Each quarter the Index provides a glimpse into the changing attitudes and sentiments of Data Protection Officers across the UK.
Trust: How to Use Data While Maintaining Consumer Trust
Companies are more and more reliant upon technology and data, but this comes at a time where consumers believe their information is less secure than ever before.
How easy is it to phish your business?
As cybersecurity and cyberthreats become more prevalent in our personal and working lives, businesses have invested in solutions like antivirus software and endpoint protection to try and secure their employees, data and intellectual property.
Artificial Intelligence/Machine Learning: Regulate the Usage, Not the Technology
Many arguments that surround the regulation of AI discuss how this will stifle technology and innovation. What is the regulations centred more around the usage of AI than of the technological advancement?
Global Data Protection and Privacy Law Developments: POPIA; The First Three Months
South Africa's Protection of Personal Information Act (POPIA) came into enforcement from 1st July 2021.
Data Breaches: The Brand Battle for CMOs After Your Data is Breached
Fresh cyber attacks and data breaches across Volkswagen, Audi, McDonalds and Electronic Arts highlight the growing cybersecurity and data threat. So what can marketing leaders do about preventing and reacting to these crises?
Spotting the signs of insider risk – and stopping a security incident before it happens
When it comes to cybersecurity and the risks that go alongside it, we know that people aren't perfect – they get hacked, they make mistakes, and they also break the rules.
The Role of Privacy in ESG
With more focus on ethical data use, more companies are assessing their approach to environment, social and governance (ESG) criteria. Investors are looking beyond financial indicators to assess long-term value.
Covid-19 Vaccines, Data Protection and the Great HR Debate
The roll out of the Covid-19 vaccine has employers thinking - will they obtain, and how might they manage data on employee's covid-19 vaccination status? And if they are collecting this, how will this affect the company's thinking on a return to the office strategy?
Operationalising Data Retention to Reduce Data Risks
It is estimated that up to 70% of an organisation's unstructured data is redundant, obsolete and trivial, which creates enormous risk to potential cyber threats, as well as exposure to regulations such as the GDPR for non-compliance in handling and deleting data accordingly.
Why Your Cloud Migration Needs De-Identification
Cloud data storage provides organizations with affordable, easily managed options for keeping and maintaining expanding data stores as their business grows, increasing not only productivity but also resiliency, service continuity, and business agility
Phishing The Growing Threat to your Business
The remote working revolution has led to an increased threat from phishing. It is thought that around three-quarters of all companies have suffered some sort of phishing campaign in the past year.
Ethics and Consent: How Ethical AI Can Change The World
There is a fork in the road ahead - missue of AI and data can continue, or change can be demanded and a more ethical approach to AI and ML can be our future.
Global Data Protection and Privacy Law Developments: How Ready is China and the World for their new Data Security Law?
China's Data Security Law contains provisions that cover the usage, collection, and protection of data in the PRC.
Information Commissioners Office: Design Guidance for The Children's Code
This fireside chat between Robert Bateman and the ICO explores the work they're doing on UX design guidelines and good practice for ISS, looking for ideas on how to conform with the Age Appropriate Design Code.
Relationship between Innovation and Equity: Remote Work and the Digital Revolution
The global pandemic changed everything, from our health and well-being to ways in which we communicate. It led to millions remote working amid huge swathes of digital transformation projects that needed to be accelerated to support this radical change in business environment.
Artificial Intelligence/Machine Learning: How Can AI lead to a New Revolution in Cybersecurity
Artificial Intelligence and Machine Learning have radically affected the ways in which we work; within cybersecurity this is fascinating, as it will affect the ways in which cybercriminals operate as much as how security teams can evolve.
Covid-19 Vaccine Take Up, Tracking and Passes: What Does the New Normal Truly Look like?
The implementation of the Covid-19 global vaccine campaign was never going to be simple and straight-forward. What of those who cannot have the vaccine or refuse?
Ransomware is not out of control, it is everything from cryptocurrencies to users
This panel will explore a controversial topic: what is more out of control at the moment, ransomware attacks or our susceptibility due to outside forces such as cryptocurrencies and the very users/staff of our companies?

redpajama_set_name: RedPajamaCommonCrawl


Feels good to by right, sometimes!
On August 26, 2016 we published this post entitled, "5 Reasons we won't have a Recession in the next 12 months." One year later the reasoning behind this forecast has been proved correct! Markets have reached new highs and most economic indicators are showing continued strength. But of course, now we must look ahead to attempt to appropriately position investments for current conditions. It seems fitting to look to the same analysts whose projections were correct over the past year. This piece provides a look at factors used to gauge the possibility of a recession in the near future.
As I always remind clients, the only true investments have a long-term view. It makes sense to analyze current fundamentals to make small tweaks in portfolios, but the investment principals that have proved successful in the past do not require major revisions based on the current news.
(Our blog post from 8/26/2016 titled "5 Reasons we won't have a Recession in the next 12 months.") . . . Or at least, 5 reasons there seems to be a somewhat strong argument to be made that we might not have a recession in the next year based on what LPL Financial calls the Recession Watch Dashboard. This tool uses 5 indicators that, when considered collectively, have had a strong history of forecasting economic downturns.
You can follow this link to see the full report (RecessionWatch), but I'll provide a brief summary of the main points. Based on the Five Forecasters listed below, LPL states in the report, "Our Recession Watch Dashboard is showing an overall low risk of recession starting within the next year." If you take a look around Bend, OR you will likely come to the same conclusion! LPL believes these forecasters provide a comprehensive view of the odds of a recession starting within the next year. If they are correct, as they have often been in the past, continuing to maintain some exposure to growth oriented securities might make a lot of sense right now.
The opinions voiced in this material are for general information only and are not intended to provide or be construed as providing specific investment advice or recommendations for your clients. Any economic forecasts set forth in the presentation may not develop as predicted and there can be no guarantee that strategies promoted will be successful. All indexes are un-managed and cannot be invested into directly.
NYSE Composite Index measures the performance of all stocks listed on the New York Stock Exchange. The NYSE Composite Index includes more than 1,900 stocks, of which over 1,500 are U.S. companies.


Measure Title: RELATING TO NATURAL DISASTERS.
1/24/2019 H Introduced and Pass First Reading.
2/4/2019 H Bill scheduled to be heard by PVM/WLH/HSG/HSH on Friday, 02-08-19 9:00AM in House conference room 329.
2/8/2019 H The committees on PVM recommend that the measure be PASSED, WITH AMENDMENTS. The votes were as follows: 6 Ayes: Representative(s) Takayama, Gates, Kong, Nishimoto, Ohno, McDermott; Ayes with reservations: none; Noes: none; and 1 Excused: Representative(s) D. Kobayashi.
2/8/2019 H The committees on WLH recommend that the measure be PASSED, WITH AMENDMENTS. The votes were as follows: 5 Ayes: Representative(s) Yamane, Todd, Lowen, Tarnas, Wildberger; Ayes with reservations: none; Noes: none; and 2 Excused: Representative(s) Har, Thielen.
2/8/2019 H The committees on HSG recommend that the measure be PASSED, WITH AMENDMENTS. The votes were as follows: 8 Ayes: Representative(s) Brower, Aquino, Cullen, Hashem, Hashimoto, Woodson, McDermott; Ayes with reservations: Representative(s) Matayoshi; Noes: none; and Excused: none.
2/8/2019 H The committees on HSH recommend that the measure be PASSED, WITH AMENDMENTS. The votes were as follows: 6 Ayes: Representative(s) San Buenaventura, Belatti, B. Kobayashi, Mizuno, Say, Tokioka; Ayes with reservations: none; Noes: none; and 2 Excused: Representative(s) Nakamura, Ward.
2/11/2019 H Reported from PVM/WLH/HSG/HSH (Stand. Com. Rep. No. 245) as amended in HD 1, recommending passage on Second Reading and referral to FIN.
2/11/2019 H Passed Second Reading as amended in HD 1 and referred to the committee(s) on FIN with none voting aye with reservations; none voting no (0) and Representative(s) Nakamura excused (1).
2/16/2019 H Bill scheduled to be heard by FIN on Thursday, 02-21-19 12:30PM in House conference room 308.
2/21/2019 H The committees on FIN recommend that the measure be PASSED, UNAMENDED. The votes were as follows: 14 Ayes: Representative(s) Luke, Cullen, Eli, Gates, Hashimoto, Holt, Kitagawa, B. Kobayashi, Matayoshi, Nakamura, Nishimoto, Wildberger, Yamashita, McDermott; Ayes with reservations: none; 0 Noes: none; and 1 Excused: Representative(s) Todd.
2/28/2019 H Reported from FIN (Stand. Com. Rep. No. 904), recommending passage on Third Reading.
2/28/2019 H Passed Third Reading with none voting aye with reservations; none voting no (0) and Representative(s) DeCoite excused (1). Transmitted to Senate.
3/1/2019 S Received from House (Hse. Com. No. 106).
3/1/2019 S Passed First Reading.
3/5/2019 S Referred to PSM, WAM.
3/8/2019 S The committee(s) on PSM has scheduled a public hearing on 03-14-19 1:15PM in conference room 229.
3/14/2019 S The committee(s) on PSM recommend(s) that the measure be PASSED, UNAMENDED. The votes in PSM were as follows: 4 Aye(s): Senator(s) Nishihara, Wakai, Baker, Harimoto; Aye(s) with reservations: none ; 0 No(es): none; and 1 Excused: Senator(s) Fevella.
3/22/2019 S Reported from PSM (Stand. Com. Rep. No. 1379) with recommendation of passage on Second Reading and referral to WAM.
3/22/2019 S Report adopted; Passed Second Reading and referred to WAM.
3/22/2019 S The committee(s) on WAM will hold a public decision making on 03-25-19 11:00AM in conference room 211.
3/25/2019 S The committee(s) on WAM recommend(s) that the measure be PASSED, UNAMENDED. The votes in WAM were as follows: 9 Aye(s): Senator(s) Dela Cruz, Keith-Agaran, English, Harimoto, Inouye, K. Kahele, Moriwaki, Shimabukuro, Taniguchi; Aye(s) with reservations: none ; 0 No(es): none; and 4 Excused: Senator(s) Kanuha, Kidani, Riviere, Fevella.
3/28/2019 S Reported from WAM (Stand. Com. Rep. No. 1651) with recommendation of passage on Third Reading.
3/28/2019 S One Day Notice 03-29-19.
3/29/2019 S Report adopted; Passed Third Reading. Ayes, 23; Aye(s) with reservations: none . Noes, 0 (none). Excused, 2 (Senator(s) Fevella, Kim). Transmitted to House.
3/29/2019 H Returned from Senate (Sen. Com. No. 541).
3/29/2019 H Transmitted to Governor.
4/16/2019 H Act 009, on 04/16/2019 (Gov. Msg. No. 1110).
4/16/2019 S Act 009, 04/16/2019 (Gov. Msg. No. 1110).


Bio Pac is a family-run cleaning products company with wonderful customers who use our biodegradable detergents and soaps because they work great, use refillable containers, and are formulated for the chemically sensitive. We focus on providing environmentally safe cleaning products found in natural food stores nationwide.
Our family is passionate about the environment, local communities, and personal health. Our biodegradable cleaning products are super concentrated, contain no animal ingredients and are never tested on animals. Bio Pac, Inc. donates a percentage of our profits to groups involved in wilderness and watershed preservation.
We are having distribution problems in some areas. If your store no longer carries Bio Pac. it is because one of our distributors, UNFI, has dropped out product in some of their warehouses. All we can recommend is you ask the store to bring the product back in. With enough demand, UNFI will carry the product in all their warehouses so the store can order it. We are looking into alternative distribution so check back here for updates.


"The Flying City" was the name of the 1928 diploma project of Georgii Krutikov, a student at the VkhUTEMAS architecture school in the Soviet Union.
In his project, Krutikov envisioned atomic-powered aircraft which carried urban residents from industrial work stations to beehive living colonies floating in space.
The post 1928 Futurism: 'Flying City' Architectural Project appeared first on Soviet Visuals.


Hum Gene Ther Clin Dev. 2018 Sep;29(3):148-155. doi: 10.1089/humc.2018.081.
Long-Term Follow-Up of a Phase I/II Study of ProSavin, a Lentiviral Vector Gene Therapy for Parkinson's Disease.
Palfi S1,2, Gurruchaga JM1,2, Lepetit H1,2, Howard K3, Ralph GS3, Mason S4, Gouello G1,2, Domenech P1,2, Buttery PC4, Hantraye P5, Tuckwell NJ3, Barker RA4, Mitrophanous KA3.
1 AP-HP, Groupe Hospitalier Henri-Mondor , DHU PePsy, Neurochirurgie, Psychiatrie Créteil, France .
2 Université Paris 12 , Faculté de Médecine, IMRB INSERM U 955 Team 14 Créteil, France .
3 Oxford BioMedica Ltd. , Oxford, United Kingdom .
4 John van Geest Centre for Brain Repair, Department of Clinical Neuroscience, Addenbrooke's Hospital , Cambridge, United Kingdom .
5 CEA, DSV FBM, MIRCen and CNRS URA2210, Fontenay-aux-Roses , France .
Parkinson's disease is typically treated with oral dopamine replacement therapies. However, long-term use is complicated by motor fluctuations from intermittent stimulation of dopamine receptors and off-target effects. ProSavin, a lentiviral vector based gene therapy that delivers local and continuous dopamine, was previously shown to be well tolerated in a Phase I/II first-in-human study, with significant improvements in motor behavior from baseline at 1 year. Here, patients with Parkinson's disease from the open-label trial were followed up in the long term to assess the safety and efficacy of ProSavin after bilateral injection into the putamen. Fifteen patients who were previously treated with ProSavin have been followed for up to 5 years, with some having been seen for 8 years. Eight patients received deep brain stimulation at different time points, and their subsequent assessments continued to assess safety. Ninety-six drug-related adverse events were reported (87 mild, 6 moderate, 3 severe) of which more than half occurred in the first year. The most common drug-related events were dyskinesias (33 events, 11 patients) and on-off phenomena (22 events, 11 patients). A significant improvement in the defined "off" Unified Parkinson's Disease Rating Scale part III motor scores, compared to baseline, was seen at 2 years (mean score 29 · 2 vs. 38 · 4, n = 14, p < 0.05) and at 4 years in 8/15 patients. ProSavin continued to be safe and well tolerated in patients with Parkinson's disease. Moderate improvements in motor behavior over baseline continued to be reported in the majority of patients who could still be evaluated up to 5 years of follow-up.
Trial profile. Box 1 represents cohort 1: n = 3 patients included at dose level 1 (low dose, 1.9 × 107 transducing units [TU]; 8 years of follow-up), which involved four needle tracks of five ProSavin deposits per track in each motor putamen. Box 2 represents cohort 2: n = 3 patients at dose level 2 (mid dose, 4.0 × 107 TU; 7 years of follow-up), which involved five needle tracks of five ProSavin deposits in each track placed within the motor putamen. Box 3 represents cohort 2b: n = 3 patients at dose level 2 (mid dose, 4.0 × 107 TU; 6 years of follow-up), with the new delivery method leading to three needle tracks with one deposit per track in each motor putamen. Box 4 represents cohort 3: n = 6 patients at dose level 3 (high dose, 1 × 108 TU; 5 years of follow-up), with the new delivery method of three needle tracks, one deposit per track, in each motor putamen. A modified delivery method of administration was introduced for cohorts 2b and 3 to increase the rate of delivery from 1 to 3 μL/min and a reduction of diameter of the cannula from 25 to 28 gauge.
Hum Gene Ther Clin Dev. 2018 Sep 1;29(3):148-155.


text:
Birmingham BASS Festival returns for its eighth year
A city music festival celebrating black artists is now in its eighth year. Michael Wood talks to the man who has given the event soul.
Ammo Talwar
Eight years ago, Ammo Talwar, CEO of arts development agency Punch Records, had a vision.
His work with young people in Birmingham was bringing him into contact with a lot of talented black artists, and he could see a lot of great arts venues in the city, but he realised that the two just didn't join up.
He explains: "A lot of people were coming up to us and saying, 'We don't feel connected with the large venues in the city'.
"Most of the arts tended to be white and middle-class – and that's not the DNA of the city. We thought we had to do something because we had the infrastructure and a little bit of influence. So we decided that we would create an event that would represent young black people."
That event became the BASS (Birmingham Arts and Street Sounds) Festival, which returns to the city for the eighth time next week – and this year it has added soul.
The annual celebration of theatre, dance, spoken word and music is expected to attract a total audience of about 12,000 at the 20 events being held over 20 days, all linked by this year's "soul" theme.
It'll even have a pop-up radio station - BASS 87.7FM - broadcasting across the city throughout the event.
But it wasn't always that big – or that organised.
The first couple of years were "pretty chaotic", Ammo admits. "We were really unsure what we were doing. "At first, we didn't think it would be a yearly thing. We thought, 'We'll try something and see if it'll work'."
Eight years on, though, the BASS Festival is established as part of the city's cultural calendar.
It's a commissioning festival, explains Ammo, who was made an MBE in 2008 for his work with music and young people. In November and December, a call goes out for people to come up with ideas for events, the applications then come in in January and in February the successful acts are commissioned.
"We normally get about 35 to 100 applications, which we whittle down to about 15," says Ammo.
"Imagine giving people £1,000 and saying, 'We'll get you into The Rep'. We can do that," he adds.
"It's kind of breaking down barriers," he explains. "We are a city of makers, but sometimes people are making works, but haven't the venue to put them in."
* The BASS Festival runs from June 11 until June 30 at various venues. For more details visit: www.punch-records.co.uk .
Bass Festival highlights
* This year's highlights include:
Soul Acoustic: Seven up-and-coming artists, including MOBO-nominated Terri Walker and Labrinth's sister ShezAr, are currently on a national tour and stop off at the Glee Club on June 11 to launch the festival. Ammo describes them as "seven acts that are about to blow". (7pm, £8).
Monique: The Gospel artist launches her new album at The Institute on June 22 (7pm, £7).
Soul II Soul Train: Aston Performing Arts Academy's homage to 70s American TV show Soul Train at Crescent Theatre on June 28. "Think people on roller skates with afros", says Ammo (7.30pm, £7, £5 concs, £16 family).
Bilal: The Philadelphia-born soul man has worked with Dr Dre, Common, Jay-Z and Beyonce, among others, and will headline the festival at the Hare And Hounds on June 30. "He is coming over to do a one-off show for us," adds Ammo (8pm, £15 adv).


Luis Tumialán, MD, is a neurosurgeon at Barrow Neurological Institute at Dignity Health St. Joseph's Hospital and Medical Center in Phoenix. Dr. Tumialán is board certified by the American Board of Neurological Surgery.
Dr. Tumialán's expertise includes minimally invasive spine surgery and cervical and lumbar arthoplasty.
Dr. Tumialán received his medical degree from Georgetown University School of Medicine in Washington, D.C. He completed his residency at Emory University School of Medicine in Atlanta and served on active duty with the United States Navy as a neurosurgeon.


Recent weather conditions for Bedford showed that it was light intensity drizzle, with a high of 16.67 degrees and a low of 7.22 degrees. Wind was at 8.7km from the SSW, with gusts of 12.3km. The sun will rise at 04:22 EST and set at 18:04 EST.
Esquire Motel - Listed under Bedford Motels, located approximately 0.67km away.
An ideal stop on your journey.
Travelers & Esquire Motel - Listed under Bedford Motels, located approximately 0.67km away.
Hotel located just minutes from downtown Halifax.
Howard Johnson - Listed under Bedford Motels, located approximately 1.22km away.
Listed under Bedford Vacation Rentals, located approximately 0.97km away.
Listed under Bedford Bed and Breakfasts, located approximately 1.21km away.
Listed under Bedford Bed and Breakfasts, located approximately 1.18km away.
Listed under Bedford Motels, located approximately 0.38km away.


During our photoshoot for our UNEXPECTED 2019 Collection drop - where we shot in an embroidery shop I worked with years ago in the heart of the Garment Center to celebrate 18 years in business, we walked by and saw Upside Pizza right next door. Noam (Co-Founder of Upside Pizza) warmly invited us in for slices, and I had the opportunity to learn more about this new cool establishment and Noam's amazing entrepreneurial spirit while photographer Sophie Elgort continued to shoot the scene. I love unexpected meetings that turn into stories.
Learn more about Noam below [I might ask him about Chicago Style pizza... it's up for debate].
Noam Grossman stepped onto the New York food and hospitality scene as Operations Manager of B.GOOD, where he helped open the brand's first New York store in Brooklyn Heights and oversaw its subsequent expansion across the tri-state region. He eventually grew into a business development role at B.GOOD, with a focus on driving sales at underperforming locations. With an engaged and on-the-ground approach, Grossman applied his natural attention to detail and developed a passion for fostering an inspiring work culture for his teams at B.GOOD. Under Grossman's direction, less-frequented B.GOOD stores across New Jersey and Connecticut grew exponentially in performance and sales. Grossman later joined Dig Inn on the Strategic Operations team, working closely with one of the co-founders to bridge the gap between business strategy at the company's headquarters and day-to-day operations in the field, building invaluable community relationships to ensure success and goal attainment. He then transitioned to the Offsite Team, utilizing his keen eye and drive for efficiency to focus on programming including delivery, catering, business and product development, and more. After leaving Dig Inn, Grossman created Upside Pizza with the goal of providing New Yorkers and visitors alike with an unparalleled but authentic slice experience, utilizing the highest quality ingredients in a nostalgic yet contemporary space.
Congratulations on the new spot! How does it feel to be in the hustle & bustle of the Garment District?
"The Garment District brings people from all walks of life, and Upside Pizza is a spot that caters to all different demographics. We created Upside with the desire to not only provide people with great pizza, but also pay homage to the communal element of a traditional pizza parlor, and the Garment District community has been very welcoming and receptive of Upside. The neighborhood is also somewhat of a dollar-slice haven, so we're excited to continue celebrating the area's traditional New York slice culture, while at the same time bring something different and of higher quality."
What [or who] inspires you?
"I'm inspired by the days I get to spend in the kitchen with my team, perfecting our pies and continuously working toward building a better slice."
"And I'm deeply inspired by the late Tony Bourdain. He was such a genuine human, who always had a willingness to take risks and never follow a rigid plan. He brought the world closer together through so much more than food alone. Another inspiration of mine is chef Massimo Bottura of the three-Michelin star, Osteria Francescana. I really value his commitment to feeding the homeless and hungry, while simultaneously working to reduce food waste. He owns and operates one of the best restaurants in the world, and he uses that prestige to make positive social and environmental impacts."
What causes do you advocate for?
"We've been open a little over a month and are excited to continue to support local farms, small, family-owned purveyors, and distributors who we admire for their sustainability and values. We're also gearing up to work with some great organizations like Edible Schoolyard, with a mission to build and share national edible education curriculum(s) for kids in pre-kindergarten through high school."
If you could have a pizza date with anyone [dead or alive] who would it be?
"Has to be Dave Chappelle. He's not only one of the funniest people on earth, but he's also extremely smart and well versed, and always stays true to himself. I'd also be down for John Mayer to join us. The two of them have such a great relationship through music and comedy, and they're both very intentional people. They're never trying to be anything other than themselves, no matter what situation arises. I really respect that."
Controversial question [our boss lady is from Chicago] – thoughts on Chicago Style Pizza?
"Controversial answer -- no comment."
"But in reality, while Upside's pizza is quintessential New York, we still have a ton of respect for all kinds of pizza, including Chicago-style, and are always finding inspiration from others within the industry."
You knew this was coming.. what is your favorite kind of pizza?
"A classic New York slice -- thin and crispy, flavorful crust that can hold its own against the flavors and textures of the various cheeses and sauce. There's nothing better. I'm also a huge fan of our Sicilian slices and their texture, but for me, a classic New York slice will always reign supreme."
What does your average day look like running a business?
"Well, I definitely now know the meaning of "24 hours straight." I'm pretty much working round-the-clock running operations and handling business necessities behind the scenes, as well as jumping in to help my crew wherever I can. I like to spend a good amount of time in the kitchen prepping and working with our chef, developing new recipes, training staff, etc. I'm always making sure things are running consistently."
"Since we are still so new, I also spend a good deal of the day working hard to develop the Upside brand itself. We've got some exciting projects in the works -- like an upcoming clothing collab we're releasing with Ovadia & Sons -- so it's important for us to have a super solid foundation."
"And finally, if there's any time leftover, I try to head home for some sleep (but when that doesn't happen, I've become a pro at turning pizza boxes in a makeshift bed)."
What is your advice for other aspiring foodie entrepreneurs?
"If you're thinking of opening a restaurant, make sure you fully understand what you are getting yourself into. It's not something that's done on a whim. It's very real, very hard work, and there's no room for slacking off. Often times people have this idealistic view on what owning and operating a restaurant is like. Believe me, there is a big difference between the dream and the reality, so make sure it's something you desperately want before diving in. Also never underestimate the importance of community. As an entrepreneur, it's easy to get caught up in your own specific vision, but don't lose sight of why you are creating your business in the first place. Always remember that while the restaurant might be yours in ownership, it is not for you -- it's for the people."
Ava Laborde is wearing the BOY MEETS GIRL® x Unexpected 2019 Raw Edge Recycled Hoodie & BOY MEETS GIRL® UNEXPECTED 2019 Tropical Dress at the Upside Pizza on 39th Street & 8th Avenue.
Make sure to follow Upside Pizza on Instagram, @upsidepizza. Check out more information on their website - www.upsidepizza.com.
Interview by Stacy Igel, Photography by Sophie Elgort.


This is a class action case on behalf of construction labor contractors in California and Nevada for violations of labor, wage and hour laws. Plaintiff alleges that Trillium Staffing uses a pre-paid cash card to pay wages, which unlawfully discounts employees' wages because fees are charged to withdraw wages earned or use the card.
If you worked as a construction laborer through Trillium Staffing anytime between October 2013 and the present, please contact Thierman Buck, LLP immediately to discuss your rights.


Absolutely beautiful dress. So many compliments. Nicely made. Very comfortable.
Speedy shipping and great dress! Quality was not bad... It looks expensive. Go by the size chart.
Very beautiful dress I absolutely love it!
Ordered dress in red for my daughter. It fit great true to size lots of detail looks better in person. Very satisfied with my purchase would definitely buy again.
Got my dress today I ordered it and got here exactly the day they said it would. The details on the dress is very lovely can't wait to wear to my school hoco. The Size fit as expected the length is perfect will recommend it to anyone.


UGro is a high quality Coconut substrate that is peat free, sustainable and ecofriendly. UGro has the consistency of traditional moss peat once it has been rehydrated. In bonsai we recommend adding a percentage to inorganic materials such as Moler or Akadama in order to aid water retention and to promote microbial activity within the root zone. UGro is naturally rich in Trichoderma Harizanum, a micro-organism that fights root rot and stimulates the growth of plants.
This UGro Small brick will make up to 11 litres of product. Place the brick in a bucket with about three litres of water, once it starts to break open pull it appart amd mix roughly. Leave over night and by the morning you will have a fully hydrated clean product ready to use. A superbly clean high quality well graded product without any mess or fuss.
Coir maintains excellent air porosity even when saturated and gives better crops with faster developing roots and more flowers and fruit per plant when used correctly.
Coir has better water retention qualities than peat and other growing media. This has obvious advantages in dry climates or at times when plants cannot be watered frequently.
Coir peat absorbs moisture immediately, even from a dry state, (unlike sphagnum peat which tends to shrink when dry and form a water- repellent crust which causes water run-off from the top surface and water loss between the peat and the inside edge of the flower pot). Thus plants growing in coir tend to recover better and more quickly from dry conditions.
The ease of re-wetting and the quick drainage characteristics of coir mean that coir needs to be irrigated less frequently and for shorter periods. This leads to reduced leaching losses of nutrients and lower water use.
The inherent qualities of coir and the optimum water/air availability are ideal for quick rooting and propagation.
In its unprocessed state, coir is a waste product in its country of origin. Its use therefore does not involve the destruction of peat bogs and natural wetland wildlife habitat. It is a renewable resource with no hazardous disposal problems (unlike some alternatives such as rock wool). Having carefully researched the question, we are quite satisfied that the environmental input including the fossil fuel consumption associated with the transport of coir from Asia is significantly less than the environmental cost involved in the production and transport of peat moss and rock-wool. Coir is transported in a compressed compact state on scheduled vessels.
The lignin content of around 45% ensures that the excellent water/air ratio is maintained over a longer period of time than is the case with many other substrates. Thus, for example, good performance is maintained over the commercial life of a plant which may be more than 5 years.
Because Coir originates above ground it does not contain any soil diseases. In fact several studies have indicated that coir substrate brings increased resistance to pythium and other root diseases.


text:
Shakhtar vs Schalke: tickets go on sale on January 18
Dear fans, On January 18, Arena Lviv will start selling tickets for the Shakhtar vs Schalke 04 game. We want to remind you that this match will be held as part of the Europa League Round of 32 in Lviv, at 22:05 on February 18.
Ticket sales will be carried out in several stages. Traditionally, the fans who regularly attend matches of Shakhtar in the Ukrainian League and the Champions League will have priority to purchase them. We bring you the prices and the sales stages.
• Stage 1 (18-24/01/2016). Ticket sales for registered fans. The first stage is divided into four periods:
- 18/01 – tickets can be purchased by the holders of the Arena Lviv fan cards and by the fans who attended the domestic league matches this season. Simultaneously, the official website of Shakhtar will start the online sales for those football fans who have purchased tickets online for the Pitmen's games in the Ukrainian League in the current season;
- 19-20/01 – tickets can be purchased by those fans who attended the domestic league games in the 2014/15 season. Online sale of tickets available to the fans who purchase tickets online for the Ukrainian League matches in the 2014/15 season;
- 21-22/01 – tickets can be purchased by the fans who attended the Orange-and-Blacks' Champions League games this season. Online sale of tickets to the fans who purchased tickets online for Shakhtar's European competition games this season;
- 23-24/01 – sale of tickets to the fans who attended the Champions League games in the 2014/15 season. Online ticket sales to the football fans who bought tickets online for the Pitmen's Champions League games in the 2014/15 season.
Please note! Each registered fans will receive a text message with a special code. To purchase a ticket, they will need to produce their ID and the SMS-code at the Arena Lviv ticket office. The users of the online service will have access to the website in the corresponding period of sales.
• Stage 2 (25/01-07/02/2016). General sales of tickets at the Arena Lviv ticket office, on the official site of FC Shakhtar and partner sites (kassa.in.ua, internet-bilet.ua, ukrticket.com.ua and kassir24.com.ua).
In the second stage, the tickets will be available at retail outlets in Lviv:
- network of Interpress kiosks;
- network of Vysokyi Zamok kiosks;
- network of OT-OT kiosks;
- network of ZHZHUK gadget outlets.
If vacant seats remain in the stadium after the first two stages, they will launch Stage 3. Please note that ticket prices at this stage will be higher than those at the previous two stages. We will announce the possible Stage 3 later.
One fan will be able to buy a maximum of four tickets!
Holders of the Donbass Arena season tickets for the last 6 seasons can purchase one ticket of any category at 30% off. To do so, a fan is required to send the series and the number of their season ticket (if they cannot send the series and the number of their season ticket, is will be sufficient to email their full name, the season in which they had a season ticket, and their mobile phone number) to zayavka@shakhtar.com or contact the call centre at (062) 388 88 83. The season ticket holders of the Club 1936, Business Club and Diamond Club can use a dedicated phone line (067) 620 14 59 or (050) 420 20 17. We will book tickets for them. They can pick the passes at the Arena Lviv ticket office daily from 10:00 until 20:00 and on the match day from 10:00 until 17:00. Make sure to bring an ID.
Prices for the Shakhtar vs Schalke tickets:
Standard: UAH 70, 100, 120, 150, 200 and 250;
Club 1936: UAH 700;
Business Club: UAH 1500 and 2000.
Ticket office of the Arena Lviv stadium is open from 10:00 to 20:00 without breaks and days-off. Please note: on holidays and weekends the ticket office opening hours remains unchanged!
You also have the opportunity to purchase a corporate box for the Shakhtar vs Schalke game. You can book a place in a box or the entire box by following this link and get more information about VIP-tickets for the corporate boxes by calling at (067) 620 40 11.
For more information, please contact the information centre at the Arena Lviv at (067) 622 38 88.


The National Science Foundation in the science and technology and other research and development sector is offering a public funding opportunity titled "Methodology, Measurement, and Statistics" and is now available to receive applicants.
Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 47.075.
Applicants must submit their applications by Aug 29, 2019.
Review the funding details for the opportunity (19 575) and check/verify your eligibility.


text:
Steinkühler ist der Familienname folgender Personen:
 Franz Steinkühler (* 1937), deutscher Gewerkschafter und ehemaliger Vorsitzender der IG Metall
 Horst Steinkühler (* 1936), deutscher Politiker (SPD)
 Kai Maria Steinkühler (1967–2021), deutscher Filmemacher, Drehbuchautor, Autor und Schauspieler
 Manfred Steinkühler (1929–2018), deutscher Diplomat

 Martina Steinkühler (* 1961), deutsche Theologin und Autorin
 Paul Steinkühler (1873–1959), deutscher Handwerkskammerpräsident
 Theodor Steinkühler (1894–1921), deutscher Kunstmaler

redpajama_set_name: RedPajamaWikipedia


text:
Takamoto ist der Familienname folgender Personen:

 Iwao Takamoto (1925–2007), US-amerikanischer Trickfilmzeichner
 Norifumi Takamoto (* 1967), japanischer Fußballspieler


text:
Kumdo
Kumdo is a modern martial art of fencing, the Korean equivalent of Japanese kendo. It is also romanized as komdo, gumdo, or geomdo. The name means "the way of the sword," and is a cognate with the Japanese term.
The use of swordsmanship on the battlefield in Korea dates as early as the Three Kingdoms period, where sword techniques using a two-handed sword are illustrated in a book named Bonguk Geombeop, believed to have been authored during the Silla dynasty.
According to the Army Account of Military Arts and Science (Hanzi: ???; Pinyin: Wu Bèi Zhì), a Ming dynasty strategy book written in 1629 by Mao Yuanyi, Korean fencing (????; Cháoxian shìfa) was a martial art that had reached Korea through Chinese martial artists. Much of this text was based on earlier works by Ming general Qi Jiguang, who successfully adapted and emulated the use of the Japanese katana by developing the wodao, to respond to the prevalent threat of the Japanese wokou or pirates. Joseon Saebeop, one of the few surviving techniques of historical Korean swordplay, is believed to be based on this work.
Later in Korea, warriors were regarded as inferior to scholars during parts of the Goryeo Dynasty (908-1392) and much of the Joseon Dynasty, due to the heavy influence of neo-Confucianism, which greatly valued scholastic achievement and refinement over martial prowess. Yangban, Joseon-era noblemen who were typically the only males eligible for government positions through the Chinese-based examination systems, generally preferred to apply for the civil service as opposed to the military as the civil service was considered more prestigious and a better guarantor of wealth and honor compared to comparable positions in the military's officer corps, which were also generally restricted to yangban and chungin. In addition, the royal court, mindful that the Joseon dynasty founder, Yi Seonggye, was a general who overthrew the last Goryeo king, looked warily at its successful and popular military leaders and were reluctant to support a large military. Influenced by Confucian thought, the royal court generally deferred to imperial China out of respect in regards to their foreign, cultural, and defense policies, relying on the Ming and Qing dynasties for military aid and necessary foreign intervention.
This is in contrast to their Japanese counterparts, who valued martial prowess and leadership because of centuries of continuous warfare between warlords or daimyo who fought over territory and hegemony, despite acknowledging a figurehead emperor and noble court based in Kyoto. Military life during this period allowed Japanese peasants a means of social mobility they otherwise would not have, as they could aspire to be elevated to samurai class and status before the Edo period. Toyotomi Hideyoshi, born a peasant, was even able to become the ruler of Japan.
The Imjin War, the last large-scale pre-modern conflict between Japanese and Korean forces, is known more for the use of emerging weapons such as the Japanese use of the arquebus and the Korean use of naval technologies such as the turtle ship and panokseon that were advanced for its time and context, as well as the use of gunpowder-based artillery, than for the use of traditional weapons such as swords and spears.
While swordsmanship continued to be practiced, it was eclipsed in popularity by archery and the use of cavalry, was generally not as systematized as Japanese sword schools, and was seldom practiced beyond members of the military and their associates. Consequently, the popularity of certain martial arts waned without many successors to carry on its traditions. Today, there are only two remaining documents that refer to ancient Korean martial arts.[1]
The Muye Dobo Tongji, compiled during the reign of King Jeongjo in the 1790s, cataloged various sword arts and applications known to Koreans during that time, as well as hand-to-hand techniques and the use of other weapons. This work was based on earlier Ming and Joseon texts including Qi Jiguang's Ji Xiao Xin Shu, the Muyejebo, and the Muyesinbo and incorporates known Chinese and Japanese martial arts and weapon techniques. While noting the efficacy of the Japanese katana and its applications, the manual noted that Chinese influences on Korean swordsmanship and other martial arts were more prevalent.
These ancient arts are not popularly considered to be ancestors of kumdo, though some kumdo scholars, including those at the Korea Kumdo Association, believe ancient Korean fencing as outlined in a Silla dynasty book known as Bonguk Geombeop (????; Korean Sword Method) was the basis of all modern two-handed sword techniques. This belief is not commonly held outside Korea.
Other scholars regard it as being a Korean version of Japanese Kendo, with almost all kata, techniques, rules and regulations identical between the two.
Kendo, then still known as gekiken, was introduced to Korea from Japan in 1896 as a form of police and military training. After Japan outlawed all Korean martial arts, they introduced Japanese martial arts such as judo and kendo to schools. Its popularity in Korea spread quickly as part of Korea's first national physical education system. Up until end of the occupation in 1945, kumdo developed in parallel with kendo.
After the occupation ended, kumdo restructured itself, and the Korea Kumdo Association was formed in 1947. When the Korean National Sports Festival was reinstituted in South Korea in 1956, Kumdo was included as an official event.
Consequently, the history of kumdo in Korea can be seen in the following timeline, split in 2 periods; prior to Japanese invasion and after WWII. Joseon refers to Korea during the Yi Dynasty:
2010 Korea 7 Dan Kumdo(Kendo) Championship Final - Jung-gook Kim vs Kyung-ok Park
검도, kumdo, kendo, 대한검도회, 대한검도회중앙연수원, 회장기제10회전국7단검도선수권대회, 7단대회, 김정국, 박경옥, 김정국검도관, 검풍검도관
The 10th Korea 7 Dan Kumdo(Kendo) Championship Final -
Jung-gook Kim (bl...
[Highlights] Men's Team FINAL - Korea Kendo(Kumdo) Championship 2019
剣道, 검도, Kendo, 대한검도, 일본검도, 검도대회, 剣道大会, Ippons, 一本集, 검도시합, Kendo Ippons, 全日本剣道, 剣道 一本集, Let's kendo, Kendo World, Lets Kendo, Let's Kendo, Kumdo, 검도선수, 검도영상, 韓国剣道, コムド, Korean Kendo, Korean Kumdo, 대통령기 검도, 대통령기검도, 대통령기 검도대회, 검도 득점
41st Korean President's flag Kendo(Kumdo) Championship
Introduction to Kumdo
kumdo, kendo, sword, martial arts, Korean, intro, introduction, karate, kata
Master Lee Sang Hwan and his students introduce the Korean martial art of Kumdo....
Combat Hopak
Chain whip
Tomahawk (axe)
Goshin Jujitsu
Pulwar
Zipota
Kwan Tak Hing


text:
Journey to Edinburgh Fringe 2018 – stage 1
By Jan van der Black 3rd April 2018 3rd April 2018 Uncategorised
Dulce et Decorum Est: The Unknown Soldiers
How does a Fringe show come into being? This isn't a question I get asked directly, but I think that if I answer it I'll be coming close to answering several questions that I do get asked over and over – questions such as "Where do you get your ideas from?" and "Why did you write about that?" and several other common questions.
I rather think that if you asked a hundred of us the same questions, you'd get a hundred different answers really, but I also think that there's a common ground that we all cover, stages of development.
Our individual process might be very different, but we're all taking the same journey. Just as, when we come to Fringe time, we'll all be in Edinburgh but how we got there will vary tremendously. Like with most things in this business, we learn very quickly what works for us and we use that as a sort of template for creating what we hope will be something that an audience will want to see. So, how did I come up with "Dulce et Decorum Est: The Unknown Soldiers"?
The impetus…
For me, every show starts with one isolated thought. Almost anything can trigger it. Reading a book, watching TV or a movie. A dream. A conversation. Something will spark a thought that makes me think "I want to write that". Usually, the thought that's triggered is very simple to state. I may think of a line of dialogue which would be a great line for the first line of the show (that one was "I wasn't cut out to be a murderer." from The Box). It might be a situation, like a serial killer in his cell the night before his execution (10 Rillington Place).
Or it might, as in this case, be "I wonder who those people are?".
In December 2017 my friend and Director, Penny Gkritzapi and myself met for dinner. We talked of lots of things, as usual, but one of the topics was the 2018 Edinburgh Fringe. Penny showed me a photograph – the one at the head of this post – which she had come across in a Facebook post. I think most of you will agree that it evokes a number of sensations in the viewer, not least of which is "I wonder who those people are?". So, there was the impetus, and there was my trigger. "I want to write about those people", I thought.
I'll tell you more about that in the next post. Until then…
Dulce et Decorum Est: The Unknown Soldiers plays at the Space Triplex from the 6th to the 11th of August 2018.
Tickets on sale at the Edinburgh Fringe Box Office
« 10 Rillington Place at Edinburgh Fringe 2017
Journey to Edinburgh Fringe 2018 – Stage 2 »


text:
Q: Percent limit with remainder distribution on PHP There is a list of percentages. The sum of the numbers is 100.
$percent = [20.88, 14.93, 14.14, 13.29, 5.06, 4.43, 4.24, 4.22, 2.57, 2.51, 2.38, 2.18, 1.94, 1.80, 1.34, 1.21, 0.81, 0.63, 0.50, 0.48, 0.30, 0.16];

I need to limit the maximum number to a specific value, and distribute the remainder over the rest of the numbers. If possible, keeping the proportions of the remaining percentages.
Tried the following solution:
$limit = 8;

// Calculating the remainder of numbers exceeding $limit.
$rest = array_reduce($percent, function ($a, $b) use ($limit) {
    return $limit < $b ? $a += ($b - $limit) : $a;
});

// Number of numbers not exceeding $limit.
$small = array_reduce($percent, function ($a, $b) use ($limit) {
    return $limit > $b ? ++$a : $a;
});

// Percent calc with limit up to $limit and addition of the remainder ($rest / $small).
array_walk($percent, function(&$value) use ($limit, $rest, $small) {
    $value = $limit < $value ? min($value, $limit) : $value + ($rest / $small);
});

print_r($percent);
print(array_sum($percent)) . "\n";

This code works correctly:
Array
(
    [0] => 8
    [1] => 8
    [2] => 8
    [3] => 8
    [4] => 6.7955555555556
    [5] => 6.1655555555556
    [6] => 5.9755555555556
    [7] => 5.9555555555556
    [8] => 4.3055555555556
    [9] => 4.2455555555556
    [10] => 4.1155555555556
    [11] => 3.9155555555556
    [12] => 3.6755555555556
    [13] => 3.5355555555556
    [14] => 3.0755555555556
    [15] => 2.9455555555556
    [16] => 2.5455555555556
    [17] => 2.3655555555556
    [18] => 2.2355555555556
    [19] => 2.2155555555556
    [20] => 2.0355555555556
    [21] => 1.8955555555556
)
100

But if I change the variable $limit to the value 6, the limit is exceeded due to the addition of the remainder:
Array
(
    [0] => 6
    [1] => 6
    [2] => 6
    [3] => 6
    [4] => 7.24
    [5] => 6.61
    [6] => 6.42
    [7] => 6.4
    [8] => 4.75
    [9] => 4.69
    [10] => 4.56
    [11] => 4.36
    [12] => 4.12
    [13] => 3.98
    [14] => 3.52
    [15] => 3.39
    [16] => 2.99
    [17] => 2.81
    [18] => 2.68
    [19] => 2.66
    [20] => 2.48
    [21] => 2.34
)
100

I can't find an algorithm.

A: You can try an iterative approch.

*

*limit the maximum value

*while the sum is not 100:

*

*compute the missing value for each item under the limit

*add this value to item under the limit, without exceeding this limit

Code: (demo)
$percent = [20.88, 14.93, 14.14, 13.29, 5.06, 4.43, 4.24, 4.22, 2.57, 2.51, 2.38, 2.18, 1.94, 1.80, 1.34, 1.21, 0.81, 0.63, 0.50, 0.48, 0.30, 0.16];

$limit = 6;

// check if a solution is possible
if ($limit * count($percent) < 100) die("Not possible");

// 1. limit the maximum value
$limited = array_map(fn($value) => min($value, $limit), $percent);
// 2. while the sum is not 100
while (($remain = 100 - array_sum($limited)) > 0)
{
    // get the "non-full" values
    $filtered = array_filter($limited, fn($v) => $v < $limit);
    // get the value to add for each items
    $evenly   = $remain / count($filtered);
    // add the value (maximum as  possible)
    $limited  = array_map(fn($value) => min($value + $evenly, $limit), $limited);
}

print_r($limited);
print_r(array_sum($limited));

Output:

Array
(
    [0] => 6
    [1] => 6
    [2] => 6
    [3] => 6
    [4] => 6
    [5] => 6
    [6] => 6
    [7] => 6
    [8] => 4.9407142857143
    [9] => 4.8807142857143
    [10] => 4.7507142857143
    [11] => 4.5507142857143
    [12] => 4.3107142857143
    [13] => 4.1707142857143
    [14] => 3.7107142857143
    [15] => 3.5807142857143
    [16] => 3.1807142857143
    [17] => 3.0007142857143
    [18] => 2.8707142857143
    [19] => 2.8507142857143
    [20] => 2.6707142857143
    [21] => 2.5307142857143
)
100

See this demo for PHP version prior to 7.4.