Science topic

# Recurrence - Science topic

The return of a sign, symptom, or disease after a remission.

Questions related to Recurrence

As I know, there is only one program that can calculate cumulative incidence: XLSTAT. Is there any way to calculate in SPSS with %95 confidence intervals, to compare two treatments?

I have two treatment groups. I recorded the day of relapse and day of "death or other competing events".

Hi,,

I'm planning to run cut&run for H3K27me3,EZH2 and JARID2 profiling in matched paired (primary and recurrent) glioblastoma samples. I'm looking for a positive control to validate the antibodies for EZH2 and JARID2 for cut&run using qPCR, any recommendation or suggestions based on your experience?

Thanks,

Muna

I have a problem with finding references for high-order generating functions. For example in finding explicit formula of this recurrence relation: https://mathoverflow.net/questions/266478/linear-two-dimensional-recurrence-relation

Actually, in my research, there is a three-dimensional recurrence relation. Does anybody have some books about high order generating function in general?

I really appreciate any help you can provide.

- To estimate suitable petrophysical properties, would it will be useful to use CNN or GRU algorithms alone?
- Or, will this estimate will be appropriate when the two methods are combined?
- Convolutional_Neural_Network: In deep learning, a CNN is a class of artificial neural networks, most commonly applied to analyze visual imagery. They are also known as shift invariant or space invariant artificial neural networks (SIANN), based on the shared-weight architecture of the convolution kernels or filters that slide along input features and provide translation equivariant responses known as feature maps. Counter-intuitively, most CNN's are only equivariant, as opposed to invariant, to interpretation.
- Gated_Recurrent_Units: GRU is a gating mechanism in recurrent neural networks, introduced in 2014 by Kyunghyun Cho et al. The GRU is like a long short-term memory with a forget gate, but has fewer parameters than LSTM, as it lacks an output gate. GRUs have been shown to exhibit better performance on certain smaller and less frequent datasets.

Dear collegues.

I would like to ask,if anybody works with neural networks,to check my loop for the test sample.

I've 4 sequences (with a goal to predict prov,monthly data,22 data in each sequence) and I would like to construct the forecast for each next month with using training sample size 5 months.

It means, I need to shift each time by one month with 5 elements:

train<-1:5, train<-2:6, train<-3:7...,train<-17:21. So I need to get 17 columns as a output result.

The loop is:

shift <- 4

number_forecasts <- 1

d <- nrow(maxmindf)

k <- number_forecasts

for (i in 1:(d - shift + 1))

{

The code:

require(quantmod)

require(nnet)

require(caret)

prov=c(25,22,47,70,59,49,29,40,49,2,6,50,84,33,25,67,89,3,4,7,8,2)

temp=c(22,23,23,23,25,29,20,27,22,23,23,23,25,29,20,27,20,30,35,50,52,20)

soil=c(676,589,536,499,429,368,370,387,400,423,676,589,536,499,429,368,370,387,400,423,600,605)

rain=c(7,8,2,8,6,5,4,9,7,8,2,8,6,5,4,9,5,6,9,2,3,4)

df=data.frame(prov,temp,soil,rain)

mydata<-df

attach(mydata)

mi<-mydata

scaleddata<-scale(mi$prov)

normalize <- function(x) {

return ((x - min(x)) / (max(x) - min(x)))

}

maxmindf <- as.data.frame(lapply(mydata, normalize))

go<-maxmindf

forecasts <- NULL

forecasts$prov <- 1:22

forecasts$predictions <- NA

forecasts <- data.frame(forecasts)

# Training and Test Data

trainset <- maxmindf()

testset <- maxmindf()

#Neural Network

library(neuralnet)

nn <- neuralnet(prov~temp+soil+rain, data=trainset, hidden=c(3,2), linear.output=FALSE, threshold=0.01)

nn$result.matrix

plot(nn)

#Test the resulting output

#Test the resulting output

temp_test <- subset(testset, select = c("temp","soil", "rain"))

head(temp_test)

nn.results <- compute(nn, temp_test)

results <- data.frame(actual = testset$prov, prediction = nn.results$net.result)

}

minval<-min(x)

maxval<-max(x)

minvec <- sapply(mydata,min)

maxvec <- sapply(mydata,max)

denormalize <- function(x,minval,maxval) {

x*(maxval-minval) + minval

}

as.data.frame(Map(denormalize,results,minvec,maxvec))

Could you tell me please,what can i add in trainset and testset (with using loop) and how to display all predictions using a loop so that the results are displayed with a shift by one with a test sample of 5?

I am very grateful for your answers

Dear colleagues, I've tried to construct some recurrent neural network with using learning sample size 25 and I would like to get 178 columns in output as a result (there are 25 columns and 178 linesin the learning sample),but I can use predict ony for a single item :

pred<-predict(fit,inputs[-train[106,]]),so I need to change the numbers in train to get a column with forecast.

sslog<-as.ts(read.csv("k.csv"))

mi<-sslog

shift <- 25

S <- c()

for (i in 1:(length(mi)-shift+1))

{

s <- mi[i:(i+shift-1)]

S <- rbind(S,s)

}

train<-S

y<-as.data.frame(S, row.names=FALSE)

x1<-Lag(y,k=1)

x2<-Lag(y,k=2)

x3<-Lag(y,k=3)

x4<-Lag(y,k=4)

x5<-Lag(y,k=5)

x6<-Lag(y,k=6)

x7<-Lag(y,k=7)

x8<-Lag(y,k=8)

x9<-Lag(y,k=9)

x10<-Lag(y,k=10)

x11<-Lag(y,k=11)

x12<-Lag(y,k=12)

slog<-cbind(y,x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12)

slog<-slog[-(1:12),]

inputs<-slog[,2:13]

outputs<-slog[,1]

fit<-elman(inputs[train[106,]],

outputs[train[106,]],

size=c(3,2),

learnFuncParams=c(0.2),

maxit=40)

#plotIterativeError(fit)

y<-as.vector(outputs[-train[106,]])

#plot(y,type="l")

pred<-predict(fit,inputs[-train[106,]])

a<-pred

print (a)

df <- data.frame(a)

Could you tell me please,how is possible to construct data frame and to get the 178 in output as a result,not only single column?

Thanks a lot for your help

Dear collegues,

Could you tell me please, if anybody may to provide,please, a working code for the recurrent neural network for the real data (with using training set) in R?

For example, keras and rnn.

Thanks a lot for your help

Hello everybody

According to what mentioned in the attached snapshot from the appendix of this article

My question is, if we already have the transition probability matrix P, how could we calculate numerically v^=α0(I−P)−1, as the limit of the recurrence v(t+1)=v(t)P+α0?

Is it really necessary to open the external oblique aponeurosis in performing open inguinal herniotomy ? or performing inguinal herniotomy via the external ring is equally effective ? and does that ( opening the inguinal canal ) really increase that risk of Ilioinguinal nerve injury ? is there any increased risk of recurrence if done via the external oblique ? feedback regarding institution experience is highly appreciated

Hi, could I get some suggestions about how to determine (1) the depth of water that infiltrates into the soil profile; (2) whether surface runoff will occur, and if so, how much.

Assume that for each scenario (a-b), the antecedent moisture content is at field capacity.

·

*Root zone depth = 1 m*·

*Ksat= 15 mm/hr*· %

*wilting point = 0.15*·

*% field capacity = 0.25*·

*% sat = 0.35*a) A rainfall event with an average 1-year recurrence interval and a duration of 60 minutes of 1.11 in

b) A rainfall event with an average 1-year recurrence interval and a duration of 24 hours of 2.51 in

Thanks.

The wave of pandemic Corona is still on.

Many get infected, Some died and a lot more got cured.

Now the question is -- what is the chance of recurrence after recovery? Is there any possibility of re-inception ??

How can I treat patient with post treated HCV mixed cryoglobulinemia relapse after sof/dakla after SVR, 6 months... Presented with peripheral neuropathy and can't stand or walk with PCR HCV RNA negative with positive cryoglob. With high tire?

there are many side effects of chemo and radio therapy for cancer therapy, moreover, one of the main obstacles is cancer recurrence !!! I would like to know, does genomic engineering approach for cancer therapy gives permanent results or there is still a risk of cancer recurrence

Please justify your opinion:

whether fusion is necessary for recurrent lumbar disc prolapse.

We have seen the quarantine is the best remedy for covid. However we can't stay at home all the time. Labour hours, working at home is not adapted now. Can we find a way to approach a solution, better without a quarantine, to find an equilibra between our lives and our health? This summer has been hantavirus that might have faded away, and it could be the first time the bubonic plaque has reached China from Mongolia, where there has been cases in USA, California(and before covid) How does covid really affect the new diseases and how will it affect to us now?

Throughout my research related to mixed-race identity development in Japanese context, most participants report differences in how their self-ascription differs from that of their parents. I would like to know if this is a recurrent phenomena in other contexts as well.

Thank you very much for your reply,

Kind Regards,

Alexandra Shaitan.

I have a model of depression which I am attempting to convert into a functional simulation in the form of a recurrent neural network or genetic algorithm, whichever would suit it better. (The model is attached)

Some of my questions on how this may work include:

- How ought one optimise the initial parameters of the system?
- How best to deal with positive feedback-loop induced instability?
- How to go about choosing between activation functions

Any suggestions on how to go about coding an initial loop and then expanding it would be very helpful. Also, any suggestions on where to code this, I was thinking Jupyter.

I would like to identify the predictors of seizure recurrence after a first seizure. Should I use a Cox regression model yielding hazard ratios or should I use a log-binomial regression yielding risk ratios?

From what I understand, I shouldn't use logistic regression because it yields odds ratios, which often overestimate risk ratios.

Stress is a fact among the researchers' community, wherever you are and whatever you are doing. It can be cyclical, randomly recurrent, ephemeral, or chronic.

Is there any practical guide [good laboratory practices] to prevent burnout?

I have some binary values, lets say 0.5 and -0.5 (remember not 0 and 1), I want to use RNN to predict these values. Is it possible using RNN?

What is the role of Retroperitoneal lymphnode dissection for a synchronous metastatic RCC, status post Cytoreductive nephrectomy with unaddressed enlarged retroperitoneal nodes during surgery?

Is there a evidence to suggest staged RPLND after a gap of 6 months or shud Oral TKI is preferred?

Patient has a recurrent scalp lesion involving the occipital region with an intracranial extension, however resectable

We know from the literature (Andrich and Mundy, Barbagli and mamy others authors) that recurrence rate after buccal mucosa graft urethroplasty (BMGU) done for urethral stricture increase every 5 years from the operation, reaching 30-40% or even more 15 years after the operation. It seems reasonable to try to prevent those complications actively instead of using "watch and see" passive method of postoperative observation and perform next BMGU if recurrence of urethral stricture appear. Don`t you think that our proposition of calibration of urethra with antiscar gel used as a preventive method for stricture recurrence may be some solution of that problem? We don`t waste time during scar remodelling which starts early in postoperative time, followed by scar contraction, the main cause of urethral stricture recurrency.

In a DCLD patient who is on diuretics, the recommendation in a patient with ascites and AKI is to stop diuretics and start albumin. But when the diuretics should be restarted remains a dilemma, because these patients are commonly prone to recurrent AKI.

Hello, I am a master's student studying in Yonsei Univeristy, Korea.

I am trying to estimate the state of satellite, using Neural Network.

Below is a simple flow of my study.

1. Train (t0 ~ t1)

Train neural network using known observation & true state data

2. Validation (t1 ~ t2)

Using observation data starting from t1, validate the network

3. Test (t3 ~ t4)

With new observation data, estimate the true ECI coordinate at different time.

[For all steps]

Input : observation data ( RADAR SEZ coordinate data or Orbital Element data )

Output : true data ( ECI coordinate data)

I know that the validation is already done while training,

but the validation part is for checking whether the network is well-trained.

I used "narxnet" from the deep learning toolbox, and it worked well until the validation part.

However, in order to use the network made with "narxnet" for the test part,

I had to retrain using data from just before.

(to estimate t3~t4, need tx ~ t3 data trained network)

So all my work have failed, and I am going to restart on doing this.

Here is what I want to ask.

- I found that most of codes in MATLAB related to neural network is for image training. Is it better to use other program for this type of work? (e.g. Python, Tensorflow...)
- I found that is it better to use recurrent neural network, and time series input. Is MATLAB "train" code available for this?
- I cannot find much information on the documentations. I would like to know if there is good example I can refer to.

Thank you very much for reading my questions.

Jee Hoon, Kim.

Using available data ,the median time from onset to clinical recovery for mild case approximately 2 weeks and 3 _6 weeks for patients with sever or critical disease. Are patients who recovered from COVID_19 immune from disease or may have viral relapse or re infection?

Clinical, recurrence,relapse,re infection

Does anyone know publications that addressed the following question?: Do lifetime suicidal behaviors impact on addiction treatment adherence or relapses?

There have been a number of studies relating vitamin D deficiency to cancer and relapse in different types of cancers, for instance Hodgkin's lymphoma. Yet it does not have any repercussion for medical practice. I believe a large study is needed comparing vit D level in newly diagnosed patients to normal population, and next the progress and relapse of these patients should be monitored. This could turn out to be an important prophylaxes tool.

The role of vit D in Covid-19 patients has recently been studied at last. (Dr Campbell called for such studies in march 2020 based on observed differences in the number of Covid-19 patients with different amount of pigment in their skin while living at the same geographical location) and amazing results have been found. This simple, virtually costless intervention might decrease the number of new cancers especially blood related ones. After all vit D impacts immune system. Current research shows that the adequate value of vit D for proper functioning of the immune system is 40 not 30 ng/ml

It will be interesting to find out, how increased supplementation these day will influence the number of new cancers, though one will need to take into account diagnostic delays of recent months. Would anyone be interested in running such a study? Wouldn't be wonderful if vit D supplementation in new required doses could limit the number of oncology patients if only a little bit? Once vit. D supplementation in children has significantly lowered rickets.

I'm carrying out a retrospective cohort clinical study,

Some patients have visited the hospital twice because of recurrence, with few months in between, but with different symptoms, complications, and cyst size in each time. Even the primary outcome is different in each visit.

What should I do?

Should I consider only the latest visit?

Or treat them like 2 different patients?

I would like to know whether it is possible to model competing events while including the type of observation period as a covariate? For example, if I wanted to model competing events in two different tasks, one that lasted 3 mins and the other 5 mins. These are two different observation periods, but can events from both be included in the same analysis?

Urinary Tract Infection is more likely to occur in young women especially those who are sexually active or pregnant, which puts them at a higher risk for the infection. It can be a single-episode of Urinary Tract Infection or a recurrent UTI. The incidences of

*Enterococcus faecalis*and*Escherichia coli*shows to be significantly higher in patients with infection than those who had single-episode urinary tract infection.*E. faecalis*is known to be the most common and make structural changes. Adherent*E. coli*is also more likely to have an important role in the etiology of young women who have recurrent UTI. Both of these bacteria are known to cause mild to serious diseases. So the question is, what clinical signs and symptoms will distinguish recurrent UTI from a single-episode UTI? In terms of quality of life versus quantity of life?

Dear All,

can anyone assist in assessment of VEGF-D concentration in a 15-yr old girl with recurrent pneumothorax (Poznań, Poland)? We need to rule out LAM as a differential diagnosis.

Best regards,

M. Mikoś

Can anybody guide me regarding minimum required events (recurrence) for a successful recurrence free survival analysis in oral SCC? I'm expecting 30-35 events in my cohort of 108 patients at 3 years. Will it be good enough?

I am comparing different machine learning techniques for learning dynamical systems (e.g. a system of ordinary differential equations), and so far I've used Long-Short-Term Memory Networks (LSTM) and other variations of Recurrent Neural Networks, Dynamic Bayesian Networks, and Symbolic Regression.

However, I know only a part of this fascinating domain, so I wanted to ask the community: Can you suggest other state-of-the-art machine learning techniques for learning dynamical systems? Black-box or white-box, it's not important; I am more focused on getting good data fitting for my application.

Thanks in advance for any suggestion :-)

I want to do region based classification of speech using dilect analysis. So whether can I use Recurrent neural network for it?

Many patients of OCD relapse after cessation of rTMS. Maintenance rTMS may be useful in these patients.

Patients recovered from COVID-19 and discharged from hospital after fulfilling the criteria of discharging (WHO), so any chance of COVID-19 relapse in a recovered patient is there or not?

I'm looking for historical wind speed data in Vietnam for coastal areas. Data can be 10 or 2-min. averaged. The data will be used for extreme wind speed and recurrence period analysis that is why I need data for as long period of time as possible.

A ten years old female child with recurrent melena. Her upper endoscopy revealed an isolated lesion in the gastric fundus that could be IGV-1 without esophageal varices nor PHG.

What is your experience?

**Error using trainNetwork (line 154)**

Invalid training data. For a recurrent layer with output mode 'last', responses must be a categorical column vector.

*Error in Trails (line 71)*

*net = trainNetwork(XTrain,YTrain,layers,options);*

**Caused by:** Error using nnet.internal.cnn.util.NetworkDataValidator/assertOutputModeCorrespondsToDataForClassification (line 382)

Invalid training data. For a recurrent layer with output mode 'last', responses must be a categorical column vector.

I will be thankful to u if ur solution resolves this problem.

Curettage and bone cementation is a commonly done procedure in the GCT of bone. The recurrence rates after this surgery are significant. We are trying to find the causes of recurrence and what all could be done to avoid or decrease its incidence.

I want to optimize the Recurrent Neural Networks weights using the Genetics Algorithm.

How does one cure a long-term headache (more than 2 months), which seems to be secondary to recurrent depression in man?

The headache is located in the following regions of the head: left and right orbitofrontal cortices, lower left temporal cortex, lower left parietal cortex and lower left occipital cortex. The pain switches sometimes from the frontal areas to the back areas of the brain.

Could it be something unrelated to depression?

What are the causal underlying mechanisms of such pain?

Our knowledge on Chaos theory is practically zero. Can anyone help us figuring out and explaining pattern of the chaos (please check out the figures only)

Preprint Chaos Theory Approximation

We have not found any research paper or textbook referring to this recurrence. Can you help us to explain these problems in terms of chaos theory?

Recently HPV vaccine is being used in the management of Recurrent Respiratory Papillomatosis. It is expected to deter the recurrence of the disease. I have so far used it in five patients in the last two years. So far the outcome is not very encouraging. I want to know about the experience of the researchers about the efficacy of HPV vaccine in the management of Recurrent Respiratory Papillomatosis.

Dear everybody!

I do a hobby project as creating a character-level seq2seq2 LSTM.

In my task, I give a text as an input (max 40 characters) and the LSTM generates an output that rhymes with the input.

I created very large rhyming rows databases.

At the beginnings I trained my model with the next parameters:

batch_size = 200
epochs = 250
latent_dim = 300
num_samples = 10000

with these parameters my model converged to 0.4 after 75 epoch, but i waited all the 250 epoch and tested that model.

The result wan't so bad, but I wanted more.

After that I tried very large batch sizes, with more than 200k training data (almost all possible parameres) and every result leads to overfitting, that means my model threw the same sentence to every input. BUT(!) after I tried the 250 epoch model, I used checkpoint saving and tested only the best model after it didn't converge more. It stops at 0.29 acc usually.

I know the character level lstm in this task has its own limitations, but it would be really 10k training data?

Is it possible the convergence doesn't matter in this case and the model needs only more epochs?

Is the database too big and has a lot of stopwords and I need to do word-frequency-based filtering on the training data?

I know that the word-level method could be more effective, but I'm afraid of I misunderstood something and I don't want to waste more time to wait results from training until I don't know what I'm doing wrong.

What should I do?

Thank you all.

Hello

I am searching for the latest trends in the long term memory neural networks for sequence learning. If you know any model (recurrent or not) good to learn from a large sequence thank you for sharing it with me.

Cordially

Salah Eddine Ghamri

In the context of time series analysis, there are several multi-step ahead prediction (MSAP) strategies such as the recursive and direct strategies (the two fundamentally distinct and opposed mechanisms). The recursive strategy is the most popular one amongst practitioners. Considering that initial random weights cause inconsistency at the output of RNNs (unless it's been dealt with properly), how to quantify uncertainty over the forecast horizon. I need bands within which the forecasts oscillate.

I apologize for asking again the same question, but il really don't have a satisfactory response. In different article, I find more and more (focused on eye movement in reading) that interaction is expressed with "t" value and "b" value. I just ask myself how it is possible. I have try to find a response by without success, even asking directly the concerned authors. I think that my question is not really relevant. But for me, it is.

I known that different solution exist (as

*anova*funtion or*chi2*) but i would like to know whether it is possible with "*t*" value.Thank your in advance for any answer that could remove the doubts?

Hi everyone, I am currently working with gene expression analysis. I have downloaded a dataset GSE17537 from GEO database. In this dataset, it shows 19 and 36 patients with cancer recurrence and without recurrence respectively. ( no treatment at all)

how can I find the differentially expressed genes? What basic tool can I use? I find many use Limma but it is too difficult for me!! And how can I calculate the fold change of each gene from this dataset since I don’t know the reference gene ?

thanks for all HELPING hands!!

what are the causes of recurrent abortion in women?

I want to train two deep neural networks on two different data sets. The aim is same in both ( predicting cancer relapse) but data sets contain different type of information. I am looking for the best way to combine these two networks to be able to predict the outcome more accurate.

Hello,

i would like to performe time to event Data as time varying covariate in competing risk Analysis in Stata?

I have the variables

- Overall Survival in Months (OSM)

- Cumulative Incidence of Nonrelapse Mortality (NRM 0=alive, 1=nonrelapse death, 2= competing event Relapse).

- Time to Infection in Months (TI)

- Infection (0 no infection, 1infection detected)

I am very new in data analysing and coudn´t find a satisfying answer in the Internet.

Thank you very much and have a pleasant day!

Sincerely yours,

Alex

Why we use Recurrent Neural Networks for the design if Intrusion Detection System?

What is the difference between the fuzzy neural network and Recurrent Neural Network

No, it is not merely hypnozoite activation or recrudescence as conventionally understood. This is a rhetorical question, because the answer is here:

I am going to conduct a meta-analysis about risk factors for recurrence of “A cancer” after curative resection. When I search literatures, I found that there are some qualifications for certain researches, like qualification on cancer characteristisc such as etiology, histological differentiation, tumor size, etc.

For example, one research study risk factors for recurrence of “xx-related A cancer” after curative resection, other study that for “stage II A cancer”, and someone for “large size A cancer”.

I wonder if these qualified studies can be included? I think they may increase bias of meta-analysis, but if I exclude all studies with any qualification, few available studies will left. Is there any solution to this dilemma? Thanks!!!

7-year-old boy with standard B-ALL with late marrow and bone relapse (27 months after finishing treatment).

After second induction he had MRD < 0,01% in marrow and bone evaluation with 0,03% of blasts (79% of viability).

After second cycle 0,01% blasts in bone.

He only has related haploidentical donor.

Which is the best approach: Chemo/radiotherapy or SCT?

Recurrent chalazia are seen to harbor adenocarcinoma clinically and on histopathology examination 1.

1.

**Ref: Shah SIA et al: Concise Ophthalmology Text & Atals. 5th ed. Param B (Pvt.) Ltd. 2018: 27-31**Few patients have recurrent ingrown toe nail problem leading to paronychia.

Despite lifestyle management, oral/topical antibiotics, anti-inflammatories and local hygiene, the problem seems to recur.

What makes matters worse is that despite toe nail removal the problem persists when the nail regrows in a similar fashion.

What are the ways to deal with it for a more permanent solution?

I wanna know about other genetic test different than Oncotype and Mammaprint, that have similar function in evaluating oncogenes and risk score, but as generic test

With recurrent major depressive disorders there are some guide line about chronic therapy with antidelressants. The question seems to me less clear in the case of recurrent anxious disorder.

Which is the single most important prognostic factor that most significantly influences the risk of breast cancer recurrence?

there are different kinds of neural networks. MLP, RBF, LSTM, recurrent, ...

I have to approximate a dynamical system with neural network, which type of NN is more suitable for this task?

What might have caused the devastating flood in Kerala?

Is it natural or man made or a mix of both?

What lesson should we human learn from this to help future non-recurrence of events of this magnitude?

I am studying synchronization of a network of identical Hindmarsh-Rose neurons.

Please anyone tell me how to define recurrence functions of 3*10 equations in Mat-lab.

please follow the attach file.

source of the file

B.K.Bera, D.Ghosh and M.Lakshmanan , PhysRevE.93.012205

Breast cancer recurrence prognostic factors

The number of malware continues to increase dynamically and are very complex and sophisticated. Distributed Malware contributes to loss or privacy invasion, having negative impact on confidentiality, integrity and availability of private data.

Trying to find the scoring method for this measure, but neither the original paper nor other studies mention the exact scoring.

Does the adaptive recurrence have the same role in life and pharmaceutical sciences as the trigonometric functions in technical sciences ?

I want to know any research on recurrence interval of landslide damming on Indus through Himalayas of Pakistan.

Regards

Ijaz