Nepal in 1950s

Nepal is a small but ethno-linguistically rich Himalayan country that consists of eight of the world’s tallest mountains. Despite being small, Nepal is home to over one hundred languages. Where did these people originate? What are their histories? Unfortunately, due to scanty archeological and historical data, we do not know much about the Nepali linguistic communities.

Understanding population distribution i.e., where people live may tell us important things about origins and histories of a particular population. Basically, dense localization of a population in a particular area may suggest the population’s historical territory. Similarly, population spread may indicate migratory patterns of certain populations. If multiple populations harbor the same area, it is likely that gene flow between such populations may have occurred in the past.

Thus, to learn about the histories of different Nepali language communities, I looked at the census data from 1952-54, which is the first reliable census of Nepal. I obtained the data, formatted it, and cleaned it up a little bit.For this census, Nepal was divided into 9 census regions and 67 census districts (Fig.1). Although data for district level is available, I will focus on the regional data for this article.


Figure 1: Nine census regions in first Nepali census (1952-54 A.D.)

According to the census data, there were 8,473,478 people native to the 28,770 villages and cities in Nepal. Only five cities had more than 5000 inhabitants: Kathmandu (107K), Lalitpur (42K), Bhaktapur (32K), Nepalganj (11K), and Birganj (10K). Interestingly, Thimi, a town between Lalitpur, Kathmandu, and Bhaktapur also had 8.7K people. Migration rate, defined as people not present in their ancestral homes for six months or more, was negligible: 2.6% for the entire country and between 0.06-4.3% for the nine census regions. This makes sense because Nepal was very remote until recently. The first highway was constructed in 1960s before which traveling was probably very difficult, therefore rare. Closed to the western world until 1950, first available reports have also described Nepal as remote and rural and difficult to travel.

The negligible migration rates indicate that most Nepalis lived in their ancestral villages. Therefore, this census data may be useful in understanding the historical population structures within Nepal. Hence, I first looked at population density in each census region (Fig, 2).


Figure 2: Population density in the nine census regions in 1952-54

In the first glance, most populous region in Nepal was Western Hills and the least populous was Western Inner Terai. However, after accounting for geographical area, Kathmandu valley, which consists of three towns: Kathmandu, Bhaktapur, and Lalitpur, was remarkably the most populous region within Nepal consisting of 5% of the entire population. Around 45% Nepalis lived east of Kathmandu valley, Western Hills comprised of 40% of the population, and 61% of the Nepali populations lived in the Hills (Eastern and Western Hills combined). The least populated region in the country was Far-Western Terai, likely because it was covered with dense malaria infested jungles.



Figure 3: Population size of different ethnolinguistic communities within Nepal in 1950s

From the data, major language groups appear to be Nepali, Maithili, Tamang (Lama), Newari, Tharu, Magar, Rai, and Limbu. Although currently over 100 languages are recognized in Nepal, in the 1950 Census reported around 36 language groups (Fig.3), probably in an effort to not contradict Prithvi Narayan Shah’s Divyopadesh  in which he has proclaimed that Nepal is a common ground of 4 varnas and 36 jaats. Many of the smaller language groups in Terai have been lumped into “Pradesh dialects.” Also, several of the High Himalayan languages recognized today are missing. Because the census was conducted by traditional revenue collectors, known as  jimmewals and patwaris, perhaps the Rana government thought that the burden of visiting the remote High Himalaya was not worth the negligible revenues it would extract from its inhabitants. Therefore, it is reasonable to assume that these populations were not included in the first Nepali census of 1952-54.

My ultimate goal was to find clues about population histories of different ethnolinguistic groups within Nepal. Therefore, I used the “mother tongue” data to first see if I can learn anything about where different language communities lived in 1950s.



Figure 4: Ethnolinguistic diversity within Nepal in 1950

Figure 4 shows what proportion of population in each census region is contributed by which language community. For example, about 55% of population in Kathmandu were Newar, 40% were Nepali speakers, and the remaining 5% were Tamang. Although considered natives of Kathmandy valley, appreciable proportions of Newars were present outside of Kathmandu valley in Central Terai (5%) and Eastern Hills (4%). Newars were absent in all Terai regions.

The census clearly shows that Terai was populated by various non-Nepali speakers. Even in 1950s, it is clear that Nepali speakers were widespread in Nepali Hills and Inner Terai, but were also virtually absent (<5%) from all of the Terai (Fig.4). Given the low migration rates, it is likely that the populations that lived in certain parts of Terai in 1950 were native to that region. For example, the majority of populations in West-Inner Terai (57%) and Far-Western Terai (60%) were Tharu, a tribe that is indigenous to dense, malaria-infested, impenetrable jungles, also known as chaar-kose jaadi that decorated Terai until very recently. Indeed,  Danagaura Tharu (Banke, Bardiya, Dang, Surkhet), Kathariya Tharu (Kailali), and Rana Tharu (Kailali and Kanchanpur) are indigenous to FW Terai. Tharu presence is also strong in  Mid-Western Terai (20%) and Central Inner Terai (12%). Indeed, Chitawania Tharu are known to be indigenous to Chitwan, Bara, Persa in Center Inner Terai. The presence of Tharu is appreciable as well in East Inner Terai (6% of the population in Sindhuli and Udayapur), perhaps due to large populations of Kochila Tharu in this region. They are virtually absent in Kathmandu valley and in the Hills but interestingly, also in the Eastern Terai, which was mostly populated by Maithili speakers, perhaps because this region was once the capital of an ancient Maithili kingdom of Videha.

Tamang and Magar communities were widespread in Eastern as well as Central Nepal. Surprisingly, 33% of Nepalis in Central Inner Terai (Chitawan, Chisapani Garhi, and Nawalpur) were Tamang, although Tamangs were also present in Eastern hills and perhaps even in the high-altitude regions in the East. After Nepali and Tamang speakers, Rai (13%) and Limbu (8%) were the most populous groups in the Eastern Hills whereas  Magar were the third most populous in East-Inner Terai (12%).

Although this data indicates that Eastern Nepal was more diverse than Western Nepal, it is biased against the smaller language communities. For example, almost all of the 14,261 Chepang lived in the Central Inner Terai but they only comprised 6% of the population. Many other language communities have much smaller population sizes (Fig.3). Hence, to know the whereabouts of smaller language communities, I asked what proportions of speakers lived in each census region. In other words, I asked how each language group was distributed across different census regions (Fig.5).


Fig 5: Distribution of language families within Nepal in 1950

This figure clearly shows that many smaller language communities are localized to a particular region, especially in the Hills and Terai of the East. About 60% of Nepali speakers were present in Western Hills, indicating that Nepali speakers were originally residents of Western Hills and later spread rapidly to comprise the majority of populations in many other census regions (Fig 3). Although this is consistent with previous reports of rapid Khas migrations within Nepal, it is important to realize that this migration must have happened steadily over several generations because migration rate throughout the country was very low.

Eastern Hills appear to be very diverse along with Eastern Terai.  Many smaller language communities such as Jirel, Thami, and Sunuwar appear to be residents of Eastern Hills. Although Maithili is the dominant population in Eastern Inner Terai, Jhangar, Dhimal, Bhojpuri, Rajbanshi, and Satar also appear to be restricted to this region. It would be interesting to see when different populations arrived in this region of Nepal and whether any gene flow among these populations have occurred.

Also interesting is the Majwari population, which is present discontinuously in Eastern Terai and  Mid-Western Terai. Who are the Majwari peoples? How and why they moved within Nepal remains to be understood. Similarly, Sherpa seem to have two distinct populations: a strong presence in Eastern Hills and a moderate one in Western Hills. Danuwar also appear to have spread from Eastern to Central Nepal.

This data has shown that smaller language communities in Nepal have historically localized to particular regions whereas larger populations have moved around. However, there are certain populations that present in Eastern and Western Nepal but not in the middle. When did these populations migrate into separate regions? Given migration was negligible in 1950s, did these populations migrated in ancient times? Did they originate from the same ancestral population? How long ago they split? These are some interesting questions that need further work.



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Map of Europe: 1000 AD to present day

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A practical guide for craft beer lovers with expanding waistline.

If you are like me, with a passion for good beer but bothered by increasing waistline that only seems to increase with increasing age, it is difficult to keep drinking beer. I have tried switching to beer alternatives, single malt for example. But whiskey is not really a beer substitute. I tried switching to low calorie light beers but they taste like beer flavored soda, not good. So, I set out to find great tasting beer with relatively low calories and here is what I found.

As  The Beer Wench has pointed out, “all you really need to know is that sugar content and calories in beer directly correlates to its alcohol content.” However, in my limited search experience, I found limited data to validate this claim. To test whether this is really the case, I downloaded alcohol, calories, and carb data for the Top 250 Beers rated by beer drinkers and compiled by



Of the two hundred beers, 135 had information on total calories and 87 had information on carbohydrates content per 20 oz. volume. I found that there is a highly significant correlation between calories and carbohydrates (Spearman’s rho=0.74, P<2.592e-16), which may seem obvious. Interestingly, I realized that the non-alcoholic beers have high carbs even though they have lower total calories (blue dots in top left figure). I also compared the calories and carbs to alcohol by volume (%ABV). I found that ABV is also significantly correlated to calories as well as carbs (Spearman’s rho=0.86 and 0.51, P<2.2e-16 and 3.853e-07, respectively). Sierra Nevada’s Bigfoot was a clear outlier in both comparisons. Also with Sam Adams’ Triple Bock, has with very high ABV and therefore, very high calories and carbs (top right figure). If you do not want your waistline to increase exponentially, you may want to stay away from both these beers. So, The Beer Wench (@thebeerwench) was right: all you need to know is the ABV. The data suggests you should avoid higher ABV for lower calories. 

These results created a moral dilemma: should one sacrifice taste for calories? More importantly, does this mean no craft beer? That would really be terrible! Fortunately, there are many great tasting craft beers with low calories but finding the right one is very challenging. I really did not have time to analyze data on all craft beers, hence I chose to work with BeerAdvocate’s Top 250 Beers. Each of these beers is rated by 150-12,000 people. A “Weighted Rating (WR)” score is generated for each beer “using a Bayesian estimate that pulls data from millions of member ratings (not hand-picked) and normalizes scores based on the number of ratings for each beer.” If that is complicated, don’t worry. The point is, I had 250 of the best beers and my job was to pick the “cream of the crop.”

Beer_data_Top250Beers.Styles   Beer_data_Top250Beers.AleCategories

I was curious to see what styles of beer are most popular among Americans. I found that ales were the more popular than lagers. People liked American ales the most followed by Belgian/French, English, German, and Scottish ales in that order. Surprisingly, lager does not seem to be please the palettes of this group of beer afficionados! Among the ales IPA and Stouts were highly rated, which is awesome because I love both. I was surprised to see that several of the American Wild Ales (AWA) were also rated high. I have tried very few of them. A few porters were also highly rated.

Beer_data_Top250Beers.ABVvsVotesI decided to look at the distribution of ABV for all the 250 beers in the dataset. I was very surprised to find that the median ABV was 9.0! This raised a strong possibility that the survey may be highly skewed towards high-alcohol beers. To test this, I compared number of votes casted per beer to its alcohol content. I found that beers with moderate ABV (~7.5%) received the most votes. This means many more people tried beer with moderate ABV than beer with high ABV but those who tried high ABV beers also rated them highly.


Anyway, it does not look like the data is biased so I decided to split the Top 250 Beers by their styles and focused on IPA, AWA, stouts, and porters. In the subsequent figures, purple indicates higher scores and yellow indicates lower scores. Ideally, you would want to find beer with yellow color for “%Alcohol” column and with blue color for “Rating” column. For example, Maple Bacon Coffee seems to be the best Porter for the calorie counters (6.3% ABV with 4.4 WR). Whereas the calorie-concerned may go with slightly higher rated Everett (7.5% ABV with 4.49 WR). Although, Twilight of the Idols is not that bad (7.5% ABV, 4.29 WR), you may want to avoid Collaboration Series: Rue D’ Floyd (14.4% ABV). Similarly, among the Stouts, Founder’s Breakfast and Péché Mortel (Imperial Stout Au Cafe) have the least calories ( (8.3% and 9.5% ABV and 4.51 and 4.38 WR respectively). I am thrilled that one of my most favorite beer, Bell’s Two Hearted Ale (7% ABV and 4.27 WR), is among the highly rated low-calorie IPA 🙂

I am really excited that each of these lists have several beers that are highly rated but have relatively lower calories. I am certainly going to try them in months to come and I hope that this list serves you well in finding your favorite beer as well.



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‘फ’ बाट फलावाङका फुत्त बहादुर फुयाँल (लोककथा)

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फलावाङका फुत्तबहादुर फुयाँलको फुर्ती नै अर्कै। फुलेको फराकिलो छाती, फररर परेको फलाटिनको फिर्फिरे कमीज, त्यसमाथि फराँसिला मिजास भएका फुर्तिला फुत्तबहादुर, अनी उनकी फ्यावुलोस वाइफ फूलमाया!

फुत्तबहादुरको फुर्ती को बारेमा त फेरीटेल नै छ: एकपल्ट गाउँमा फिटीक्कै पानी नपर्दा फुत्तबहादुर फजित भई फलावाङबाट फुत्त निस्केर फाँटै फाँट फटाफट हिंड्दै फर्पिङ्हुँदै फार्बिसगन्ज सम्म पुगे रे। फार्बिस्गन्जमा कताबाट एउटा फिरन्ते फकिर फेला परे रे। फकिर ले फुत्तलाई आफ्नो फन्दामा फँसाउन खोज्दा उल्टै फटाहा फकडालाईनै दस फन्को फनफनी घुमाएर पाता कसी दिए रे। फिटिफिटी परेका फटाहा फक्कडले फट मानी अफुसँग भएको वडेमानको फटिक दिन्छु भनेर फुत्तलाई फकाउन खोजेछन। फितला फकुल्लो हुन र फुत्त बहादुर? त्यत्तिकैमा फक्लक्क फुत्किनेवाला थिएनन् ति फटाहा फकिर! पीडाले फक्र्याक-फुक्रुक परेका फकिरले फटिकको हारको साथै विना पानीकै फकाफक फल्ने फक्फकाउँदो फर्सीको वियाँ दिन्छु भनेपछी मात्रै फुत्तले आफ्नो रिसानी फर्छाएका रे।

फिरन्ते फकिरले दिएको वडेमानको फटिक अनी फलाइलो फर्सीको वियाँ बोकेर फलावाङ फर्किदै गर्दा फेटावाल सिख फरिकसिंंहसँग उन्को भेट भयो रे। नीज फरिक सिंंह परेछन रे फलाटिनका ब्यापारी! फुत्तले फटाहा फकिरको कथा सुनाउँदा फरिकसिंंहले फजुल फगल्टा फकफक भनेर फुत्तलाई फट्कारेछन। आफुलाई फन्टुस फतौरो भन्दै फरिकर्सिंह फाँकिएपछी फन्कीएका फुत्तले पनि फिरन्ते फकिरले दिएको विना पानीकै फकाफक फल्ने फक्फकाउँदो फर्सीको एउटा वियाँ निकलेर फ्यात्त फ्यांकिदिए रे। फर्सिको वोट फस्टाइहाल्यो! फरिकसिंहले फलुवा फर्सिको विउको फर्माइस गरे, फुत्तले फलाटिनको। फुत्तले फर्सिको एउटा वियाँ दिएर फरिकसिंहसँग जीवनभरी फलाटिन लिने फर्स्योट गरे रे। त्यस दिन फुत्त बहादुर फुयाँलले आफ्नो फलालो फोहोरी फत्तु फाली फररर फर्फराउने फलटीनको नयाँ कमीज फेरेका रे। अनी त्यस दिन देखी फुत्तले फलाटिनको फिर्फिरे कमीज बहेक अरु केही फेरेकै छैनन रे।

फिरन्ते फकिरले दिएको वडेमानको फटिक, फलाइलो फर्सीको वियाँ, अनी फरिक सिंह ब्यापारीको फलाटिन बोकेर फलावाङ फर्कदै गर्दा फर्पिङंमा फुत्तले एउटा राम्रो फुलबारी देखे रे। फार्बिस्गन्ज देखी फर्पिङसम्मको लामो सफरले फतक्क गलेका फुत्तले त्यही राम्रो फुलबारिमा फजिरसम्म आराम गर्ने निधो गरेछन। फूलबारीमा फुलेका फुलहरु र फुलहरु विच उफ्रिरहेका फट्यङ्रा टिपिरहेको फिस्टे फल्कोनेटको अबलोकन गर्दै बस्दा उनको नजर फुलबारीको कुनामा फलेकमाथि फरिया फिजएर फुत्ततिरै फर्केर फल फकार्दै गरेकी फूलमायामाथी पर्न गयो रे। फुलमायाको फिलिङगी रूपले फुत्तको मनमा फोस्फोरोस हाल्या फसेलझैं फीलिङ फस्टिएछ। लभ-आट-फर्स्ट-साइट।

त्यस्ती राम्री फुलमायालाई फुत्किन नदिने फुत्तले निधो गरे रे तर उनिसँग कुरा गर्ने आँट आएन रे फुत्तको। फुत्तलाई परेछ फसाद! फुलमायाको सुन्दर्तामा मन्त्रमुग्ध भएर फुत्त चैं त्यही फुलबारीको फन्को लगाउन थाले रे। फाईनल्ली शाहसको फाँको हालेर फुत्तले फूलमायालाई एउटा फूल दिएछन। फुलमायाको फुर्फुरिने वानी त थिएन तरपनी फुलेको फराकिलो छातीलाई फररर फहराउने फलाटिनको फिर्फिरे कमीजले ढाकेका फराँसिला फुत्तबहादुर जस्ता फुर्तिला, फ्याशनेवल, र फ्रेन्डली नवजवानलाई देखेर फूलमाया पनि दंग परिछिन्। फुलमायाको फतफताउने वानी पनि थिएन, तरपनी फुत्तले फटाहा फक्कडसँग लिएको फटिकको फ्यान्सी हार बनाइदिन्छु भनेपछी त फुलमाया फुरुक्कै भाईहालिन रे! आफन्तको नाममा एउटै मात्रै फूफू भएको कुरा फुलमायाले फुत्तलाई बताइन रे अनी त्यही फकर्ताउली फास्फुसे फूफूसँग भेटेर फागुनमा फुत्तले आफ्नो बिहे फूलमायासँग फट्ट गरे रे।

फिरन्ते फकिरको फलाइलो फर्सिको बिउ अनी फरिक सिंह ब्यापारीको फलाटिन बोकेर वडेमानको फटिकको फ्यान्सी हार लगाई फलाटिनकै फरियामा बेरिएकी फिलिङगी फुलमाया सँगै प्रफुल्लितहुँदै फुत्तबहादुर फुयाँल फलावाङ फर्के। फलावाङ फर्केर फुत्तले फेदिको फांट पुरै फाँडेर आफ्नो घर बसाएछका छन। फुत्तको नयाँ घर उसलाई सार्है फापेको छ। फिरन्ते फकिरको फर्सी फलाइलो भा’को छ। फरिक सिंह ब्यापारीले पनि फलाटिन सालैपिच्छे पठाउदै गरेकाछन्। फूलमायाको माया पनि फुत्तले टन्नै पाएकाछन्। फुत्त बहादुरको फुर्ती नै अर्कै भएको छ। फुत्त र फुलमायालाई अब केही फिक्री छैन तरपनी उनीहरुको स्वभाब फेरिएको छैन। फालाफाल भये पनि फारो गर्ने बानी छ फुलमायाको, फुकाफाल भएकी छैनन्। फुत्तबहादुर पनि फाल्तु फाइफुट्टी लाउँदैनन्। फुत्त बहादुरको फर्सीको फयल अहिले फिन्ल्यान्ड देखी फ्लोरिडासम्म फैलिएको छ। दुनियाँ भरिका मान्छेहरु फुत्तसँग फकेबूक फ्रेन्डस भएका छन। आफ्नो बिहेको वार्षिकोत्सव मनाउन प्रतेक फागुनमा फुर्सद निकलेर फुत्त र फुलमाया फर्पिङको त्यही राम्रो फुल्बारिमा फोगिन र फुकुन्डालाई फर्सिको खीर र फलफूल खुवौंछन; फलाटिनको पछेउरा ओढाउँछन्। एक साल त ति फुकुन्डाहरु मध्ये ति फटाहा फक्कडसँग पनि थियो रे।

भोली भोली भन्दै भुँडी पल्टाउने भैरब अर्याल बाट प्रेरित र निस्ट २००० ब्याच सेक्सन-सिका सम्पूर्ण साथीहरुमा समर्पित||

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Quantitative approach to running a marathon for beginners

Everything that people say about running a marathon is wrong. So, DREAM BIG.


I am not a runner and before 2013 I had never competed in any long distance races (except for that one 10K that I literally walked) but with a little bit of training I still ran the 2013 Bank of America Marathon and completed it in 5:02:22 (officially in 5:22:43, more on that later). Although I did not win the race, I was able to beat about eight-thousand fellow competitors (the 32,000 that beat me are irrelevant). The chart above reflects my performance during the marathon but does not tell the entire story of how I got there. Here is the story of my journey to become a marathoner.

1. Deciding to run a marathon: I have wanted to run a marathon for a long time but did not have the courage to do it. I could barely run a few steps and a flight of stairs left me panting for what seemed to be an eternity. On the Thanksgiving Day of 2012, I told my friends, of my desire to run a marathon, which they likened to a joke. I took that as the spark to ignite the fire in me and registered for the Bank of America Marathon, without knowing that it is one of the biggest marathons in the world.

2. Finding a cause (Fundraising): Registering for the marathon was easy but there was a strong probability that I would not complete it because it was probable that I would not train properly. In the past I had started numerous exercise regiments but never completed a single one. I needed something solid to motivate me to train hard. Therefore, I started a fundraising campaign with a modest goal to raise $1,200 to help Himanchal Education Foundation install wireless internet in three rural Nepali villages. I used social media (facebook and twitter) to announce it to as many people as I could. Now my family, my extended family and their extended family, all my friends, and my colleagues knew what I was up to. I had to do whatever it took to complete the marathon. Failure was not an option.

3. Training: I registered for the Marathon in February but the arctic cold in Chicago did not permit outdoor running until April. I occasionally ran in the gym but did not enjoy it at all. On April 20, 2013, Day I of training, I geared up: basketball shorts, cotton T-shirt, ankle length white socks, and 6 year old shoes (hardly used). I felt like a stallion just freed from years of captivity and I ran like one. After about a minute, I was done. It felt like my rib cage would not be able to resist the pressure of my diaphragm and my heart would burst out any minute! I was done for the day. That day I realized that marathon training is much more daunting undertaking than I had hoped for. I contemplated accepting this fact and postponing it for another year. But I had already announced to the world that I was running a marathon. More importantly, I could not disappoint my friends at Himanchal. I had to find a way.

That evening I visited about a dozen running websites that scared me even more.  Most of them suggested I start with 10Ks, then in a year try half-marathon, then may be in two years I could contemplate running the full marathon. I had six months. I then found a smartphone app called Runkeeper which has training programs for beginners as well as advanced runners. I selected a program for sub-four hour marathon, without realizing how hard it would be, a classic beginners problem. Hey, at that time 4 hours seemed a loooonnnnnggggg time. Clearly, I did not realize that 26 miles is a looooonnnnnnnnnggggggggg distance! Anyway, I was supposed to run 4 miles on the first day but even at a tortoise’s pace (13:09 mpm (minutes per mile)) I could only complete 2.22 miles.

4. Quantitative approach (counting steps): On the Day II of training, I quantified my performance using a very simple rule: for every 100 steps I ran, I walked 100 steps. At that time I did not know that walk breaks improves speed!!! Remarkably, using this approach I was able to complete the entire 4 miles the very next day. Then after, I followed the Runkeeper program such that I completed 4-8 miles three days a week and longer 8-10 miles in the weekends for the next two months.  I gradually increased my pace during the shorter runs, for example, the second week I ran 500 steps punctuated by 100 steps. Eventually I reached 2500 running steps with 250 walking steps for shorter runs. I tried running as much of the longer distances at my weekday pace but if I could not, I adjusted my pace accordingly making sure I could cover the longer distance for that weekend. Remarkably, my pace improved to ~11:09 mpm! Within two weeks I ran 10.09 miles and after a month I ran my first unofficial half marathon (13.13 miles at 11:28 mpm).


The difference with my approach was that by counting steps, I was able to monitor my improvement. Also it prevented me from quitting at random spaces: if I got tired in the middle of 500, 1000, or 2500 stretch of running, I knew I just needed to complete that stretch and I got to walk for a while. So the challenge was not to run many miles but very segments of the distance. Running a marathon was a mental problem for me and I tricked my brain!

If I was able to run 500 steps on Monday, that was my threshold for the week. If I got tired before 500 steps, I knew I could continue running, it was just my mind playing tricks on me. So I continued running until I completed my stretch. In a few days running 500 steps became easy but I did not increase it immediately. I ran faster. I focused on increasing my speed during the shorter runs and focused on the distance (sometimes at the expense of speed) on the longer runs. Compared to the first day, I made significant improvement on the second day. Compared to the first week, I made progress on the second week and so on. The improved pace and the longer distance I completed encouraged me and motivated me to keep training. I kept updating my facebook status. My improvement impressed my friends and they started donating for my cause. Over the summer my wife and I raised $1700, far more than my goal of $1200! Eventually, I ran my first marathon, the Bank of America Marathon, on October 13, 2013.

5. Lessons learned: Towards the end of my training, a friend of mine loaned me a Book on marathon running for beginners. After reading the book, I realized that marathon running is not about competition. It is not about finishing it fast. But it is about having fun while conquering the un-achievable. So on the day of the marathon, I decided to have fun. I took time to high-five all the kids on the sidewalk. I waived at all the seniors cheering from their balconies and I even crossed the street to high-five all those wearing Green Bay Packers jerseys. I had a blast the whole time. A few days after I completed the BofA Marathon, I looked back and was so proud of myself. I started not being able to run more than a few hundred steps and here I was, a marathoner. That was probably the most incredible achievement of my life. I realized that I can achieve anything if I put my mind to it. Nothing is impossible.


After the marathon, I felt tremendous boost in my confidence. Before the marathon, I was overweight. Although I shed some of the extra fat (but gained muscles such that net weight loss was almost zero), I still was slightly overweight. Still, I had enough confidence to tuck my shirt and even some of my friends said I looked better in my new fashion style 🙂 The new look and boost in confidence rejuvenated me. I was not the overweight unfit slob waiting for a heart attack anymore. I was a freaking marathoner. Take that!

Through the fundraiser, I learned four important lessons for life: 1) A single person can make a significant impact in this world. As I mentioned earlier, we raised $1700, which was enough to install wireless internet in four villages in Nepal. Many villages in Nepal are rural, remote, and devoid of infrastructures we take for granted. They are almost completely isolated from the world, as they have no roads, no hospitals, and even to this day children die of diarrhea. The ability to connect to the world via internet can mean the world to the children of these villages. 2) Small things can make big difference.  I used to think that to make a significant difference in the world, one has to be an icon, like Bill Gates or Nelson Mandela. The fundraiser made me realize that is not true because the funds we raised can save lives in the rural villages of Nepal. For example, Mr. Mahabir Pun of Himanchal is running a telemedicine program in rural villages of Nepal. Through this program, doctors in nearby cities can regularly chat with the villagers via the internet and prescribe simple homemade cures for diseases such as diarrhea. It was amazing to think that I was helping save lives! 3) People are good. It was incredible that we raised most of the $1700 within two weeks. Even before my family could donate, many of my friends, started donating. Most of them were not even Nepalis and many of these good people were cash deprived graduate students or average income Americans. This reinstated the value of charity in me. I too have started giving. 4) My wife is awesome! Marathon training was very hard for me and many times when my body was aching I needed encouragement and comfort. My wife was always there for me throughout this process. Without her, I would not have been able to complete this daunting task. Thank you Nanu.

There are many other lessons for life that you can learn from training for and running a marathon. For some of the life lessons you can learn from marathon running, visit this blog.

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Evolutionary marvels: Biodiversity in animals

Evolutionary marvels: Biodiversity in animals

The Guardian has a dozen #amazing pictures of remarkable animals that inhabit land and the deep seas. “A very worthwhile diversion,” says the New York Times’ Jennifer Kingson.

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09.19. 2013 · 9:45 am

GFP stained Drosophila larva

Please also view Dosophila embryogenesis video

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Filed under Evolution, My Life My Thoughts