text:
Dragonfly 912 Becomes Newest SLSA #132
July 7, 2013 by Dan Johnson Leave a Comment
Note the tall mast extending from the vertical stabilizer; another component can be seen aft of the tailwheel. This is part of the tow bridle system used to safely tow hang gliders.
Unusually large "elephant ear" ailerons are part of design allowing Dragonfly to tow a hang glider at 35 mph.
You might not be in the market for a super slow flying aircraft like Dragonfly that stalls at less than 20 mph. You might not care that Ed Pittman took the lead winning Special LSA approval on behalf of Australian businessman and hang gliding pioneer Bill Moyes and American Dragonfly designer Bobby Bailey. However, as a longtime hang gliding enthusiast, I can attest on behalf of many who enjoy soaring flight in hang gliders that Dragonfly is a critically important aircraft. The unusual aircraft was purpose designed to tow a hang glider aloft so it can be released — commonly at 2,000-2,500 feet and often right in a column of thermal lift — to allow it to achieve soaring flight without the benefit of a mountain from which to launch. One of the most successful aerotug airparks, called Wallaby Ranch, is located a few miles south of Disney World in Florida. Wallaby owns and operates four Dragonfly aircraft and numerous others are in duty elsewhere around the country and globe.
Most everyone in light aviation is now aware that FAA is out conducting audits of LSA manufacturers, with particular attention to new manufacturers or existing manufacturers offering a new model. Last year, FAA issued more guidance — in the form of the catchily-named 8130.2G Chg 1 directive — that defines more about what is a new model or manufacturer. All this was working, albeit at the rather leisurely pace of two audits a month (which would take several years to go through all 90+ manufacturers of LSA), until the federal sequestration came along. With their budget cut, FAA pulled back on all kinds of activities, most notably closing control towers (since altered by congressional action) and charging airshows like Sun 'n Fun and AirVenture to operate towers during their events. With this in mind I asked Ed if Dragonfly powered by the Rotax 912 was considered a new model. Ed replied, "Yes, they treated it as a new model." Ed previously gained approval for a Rotax 582-powered Dragonfly but these two have differently worded Airworthiness Certificates. "Once again I didn't get the 'Special Team' (of several FAA auditors from Washington DC) due to budget constraints within the FAA." Perhaps because of the special duty of this low-speed LSA, Ed concluded, "I don't think they are very worried about the Dragonfly."
"We now offer Dragonfly 582 and Dragonfly 912 in both 80 and 100 horsepower models." He added, "We found a prop that generates 525 pounds of thrust on the 100-hp 912 which should satisfy most towing needs." He noted that this powerful thrust met technical specifications issued by Rotax Aircraft Engines and finished saying, "That's not easy to do with the ASTM requirements and props out there today. These props are made specially for our operation." I know Ed for many years through our mutual hang gliding interest and find him to be a serious, thorough person. The hang gliding community should be celebrating his accomplishment at gaining acceptance by FAA. An SLSA Dragonfly is available ready-to-fly for $67,222 for a 65-hp Rotax 582 model or $81,904 with 100-hp Rotax 912. An ELSA kit version of the latter is $66,964. You may want other accessories or services so check this page for all the details and then call Ed Pittman (530-945-1860 Pacific time) for delivery info.
Filed Under: Dragonfy 912, Pitman Air LLC, Splog Tagged With: 3-Axis 2-Place, Fixed Wing Aircraft

redpajama_set_name: RedPajamaCommonCrawl


text:
St. Matthews, SC
Located 30 miles southeast of Columbus, St. Matthews is the county seat of Calhoun County, South Carolina. Although it's a small town with few big-city attractions, St. Matthews attracts visitors interested in the region's long history. Many archeological sites, antebellum homes and structures in the area are listed on the National Register of Historic Places. The quiet community serves as a good base for exploring recreational actives in nearby Lake Marion and Congaree National Park as well.
Evidence of human occupation has been found in St. Matthews dating back to the Paleoindian Period. The site of modern-day St. Matthews was also a stopping point for Native Americans along the Cherokee Path, a footpath that once crossed the entire length of South Carolina. The town is one of the few places in the state where parts of the path are still visible.
St. Matthews was originally known as Lewisville, a town that was established when the railroad came through in the mid-19th century. The town's charter never received state approval, however, and when the city was officially incorporated in 1876, it was renamed after the colonial St. Matthew's Parish. The Calhoun County Museum and Cultural Center houses many artifacts, art and costumes from the town's early history.
St. Matthews has a land area of 1.93 square miles. Situated on the Atlantic Coastal Plan, the city has an elevation of 287 feet. St. Matthews is intersected by U.S. Route 601 and South Caroline Highway 6.
With a humid subtropical climate, St. Matthews gets an average of 47 inches of rain each year. There are around 222 sunny days each year, and the average daytime high temperature in July is 92 degrees Fahrenheit. The average low daytime temperature in January is around 34 degrees.
The population of St. Matthews has declined in recent years and today is estimated to be less than 2,000. The median household income has increased, however, rising from around $25,000 in 2000 to nearly $30,000 in 2012. Median home values have also improved, increasing from $63,000 in 2000 to more than $100,000 in 2012.
St. Matthews reached its heyday during the antebellum period before the Civil War, and several historic homes and farm buildings from the era are still standing:
Once owned by State Senator Olin Dantzler, the Crutchfield House is a great example of a southern antebellum summer home. Built in 1850, it is the oldest residence in St. Matthews.
The David Houser House was home to one of the region's most successful residents. The estate once stood at 4,800 acres and included a plantation, a mill and the cemetery where Houser is buried.
The only plantation home in St. Matthews still standing, Puritan Farm was built in the early 1800s and became the home of Congressman Lawrence Keitt, a leader in the South Carolina secessionist movement.
Cool Care Air Conditioning Service in St. Matthews
Cool Care Inc. is an award-winning heating and cooling contractor proud to serve residents in St. Matthews and the Greater Columbus area. We are known for our expertise, stellar service and our ability to tailor our products and services to meet the needs of each individual customer.
At Cool Care, our NATE-certified technicians are well equipped to keep you cool and comfortable during the warm-weather months, providing you with expert service, energy-saving systems and timely air conditioning repairs whenever you need them. From the moment we receive your call until we complete the project, delivering the highest level of personal service is our top priority. To learn more about our full range of products, or to schedule air conditioning service, contact Cool Care today.


text:
"""
    Compatible with Python 2 and Python 3
"""

import csv
import logging
import os
import re
from math import log

from dateutil.parser import parse as parse_date
from nltk import FreqDist
from nltk import PorterStemmer
from nltk import tokenize
from nltk import word_tokenize
from pydblite.pydblite import Base

class Discretizer:
    logging.basicConfig(level=logging.DEBUG)
    logger = logging.getLogger(__name__)
    linesep = '\n'

    def __init__(self, db_name, db_files):
        self.db_name = db_name
        self.db_files = db_files
        self.db = dict()

    def log(self, msg, level=logging.DEBUG):
        self.logger.log(level, msg)

    def load_db(self, check=True, fix=False, save_to_file=False):
        self.log('Opening {0} database(s)'.format(len(self.db_files)), logging.INFO)
        for db_name, db_file in self.db_files.items():
            _db = Base(db_file, save_to_file=save_to_file)
            _db.open()
            self.log('Database {0} opened, records #: {1}'.format(db_name, len(_db)), logging.DEBUG)
            self.db.update({db_name: _db})
            _db.create_index('uid')
            _db.create_index('type')
        if check is True:
            self.check_db(fix)

    """
    * fix answers_count with actual # of answers exported
    * if an answer has tag != N/A, the tags must be applied to the question in the same thread
    * if a question is marked as resolved True, then one of the answers in the thread must have been marked as solution;
    and viceversa;
    * check if Q or A text is ''
    * turn question uid from int to unicode string
    """

    def check_db(self, fix=False):
        self.log('Checking consistency for databases.', logging.INFO)
        for name, _db in self.db.items():
            for question in _db._type['question']:
                expected_answers_count = int(question['answers'])
                actual_answers_count = 0
                for i in range(1, expected_answers_count + 1):
                    try:
                        _db._uid[str(question['uid']) + '.' + str(i)][0]
                        actual_answers_count += 1
                    except IndexError:
                        break
                if actual_answers_count < expected_answers_count:
                    self.log('Fixing answers count mismatch in thread id {0}, expected {1}, found {2}'.
                             format(question['uid'], expected_answers_count, actual_answers_count))
                    _db.update(question, answers=actual_answers_count)

            for record in (_db('text') == ''):
                self.log('Warning on record {0} from db {1}: empty text!'.format(record['uid'], name),
                         logging.WARNING)

            for record in (_db('type') == 'answer') & (_db('tags') != 'N/A'):
                self.log('Warning on record {0} from db {1}: tags in answer!'.format(record['uid'], name),
                         logging.WARNING)
                question_uid = record['uid'].split('.')[0]
                question = _db._uid[question_uid][0]
                question_tags = question['tags'] + '.' + record['tags']
                _db.update(question, tags=question_tags)

            if fix is True:
                _db.commit()

    def load_threads(self):
        self.log('Loading threads from {0} db(s)'.format(len(self.db_files)), logging.INFO)
        overall_threads = list()
        for name, _db in self.db.items():
            db_threads = list()
            questions = _db._type['question']  # use db index
            self.log('Loaded {0} questions (threads) from db {1}, attaching answers...'.format(len(questions), name),
                     logging.DEBUG)
            for question in questions:
                answers = self._get_answers(question['uid'], int(question['answers']), _db)
                db_threads.append({'question': question, 'question_uid': question['uid'],
                                   'date_time': question['date_time'], 'answers_count': question['answers'],
                                   'resolved': question['resolve'], 'tags': question['tags'], 'answers': answers})

            overall_threads.extend(db_threads)
        self.log('Overall threads loaded: {0} from {1} database(s)'.format(len(overall_threads), len(self.db_files)))
        return overall_threads

    def _get_answers(self, question_id, answers_count, _db):
        self.log('Getting {0} answers for thread id {1}'.format(answers_count, question_id), logging.DEBUG)
        answers = list()
        if answers_count > 0:
            for i in range(1, answers_count + 1):
                answer_id = '{0}.{1}'.format(question_id, i)
                for answer in (_db._uid[answer_id]):  # use index
                    answers.append(answer)
            if answers_count != len(answers):
                self.log('Warning in thread id {0}: loaded {1} answers, expected {2}. Please, run a check db with '
                         'fix=True'.format(question_id, len(answers), answers_count),
                         logging.WARNING)
        return answers

    def compute_features(self, threads, stemmed_vocabulary, distrib_matrix):
        self.log('Computing features. Please, wait. This will take some serious time...', logging.INFO)
        for thread in threads:
            self.log('Computing features for thread id {0}'.format(thread['question_uid']), logging.INFO)
            try:
                base_date = parse_date(thread['date_time'])
            except ValueError:
                base_date = parse_date('1970-01-01')
            except AttributeError:
                base_date = thread['date_time']
            answers = thread['answers']
            tag_list = thread['tags'].split('.')
            if '' in tag_list:
                tag_list.remove('')
            for answer in answers:
                # compute thread tags
                answer_tags = answer['tags'].split()
                if 'N/A' in answer_tags:
                    answer_tags.remove('N/A')
                tag_list.extend(answer_tags)
                thread['tags'] = sorted(set(tag_list))

                # compute len in chars and words
                alen = len(answer['text'])
                answer['len'] = alen
                wordcount = Discretizer._count_words(answer['text'])
                answer['wordcount'] = wordcount
                if wordcount == 0:
                    answer['avg_chars_per_word'] = 0
                else:
                    answer['avg_chars_per_word'] = "{0:.2f}".format(alen / float(wordcount))  # float with 2 decimals
                try:
                    sentences = tokenize.sent_tokenize(answer['text'].decode('utf-8', 'replace').encode('ascii', 'replace'),
                                                       language='english')
                except (AttributeError, TypeError) as e:
                    sentences = tokenize.sent_tokenize(str(answer['text']), language='english')
                sentence_count = len(sentences)
                answer['sentences'] = sentence_count
                if sentence_count == 0:
                    words_per_sentence = 0
                else:
                    words_per_sentence = "{0:.2f}".format(wordcount / float(sentence_count))
                answer['avg_words_per_sentence'] = words_per_sentence
                longest_sentence = 0
                for s in sentences:
                    l = Discretizer._count_words(s)
                    if l > longest_sentence:
                        longest_sentence = l
                answer['longest_sentence'] = longest_sentence
                try:
                    creation_date = parse_date(answer['date_time'])
                except AttributeError:
                    creation_date = answer['date_time']
                time_difference = abs((creation_date - base_date).total_seconds())
                answer['time_difference'] = time_difference

                # TODO upvotes score

                # check for urls and code snippets
                match = re.search(r'http(s)?://', str(answer['text']), re.MULTILINE)
                if match:
                    answer['has_links'] = True
                else:
                    answer['has_links'] = False

                answer['has_code_snippet'] = self._has_codesnippet(str(answer['text']))
                try:
                    LL = Discretizer._log_likelihood(answer['text'].decode('utf-8', 'replace').encode('ascii', 'replace'),
                                             stemmed_vocabulary, distrib_matrix)
                except (AttributeError, TypeError) as e:
                    LL = Discretizer._log_likelihood(str(answer['text']), stemmed_vocabulary, distrib_matrix)
                answer['loglikelihood'] = LL
                answer['loglikelihood_descending'] = LL
                answer['loglikelihood_ascending'] = LL
                try:
                     aspw = Discretizer._ASPW(answer['text'].decode('utf-8', 'replace').encode('ascii', 'replace'))
                except (AttributeError, TypeError) as e:
                     aspw = Discretizer._ASPW(str(answer['text']))
                fk = Discretizer._FK(answer['avg_words_per_sentence'], aspw)
                answer['F-K'] = fk
                answer['F-K_descending'] = fk
                answer['F-K_ascending'] = fk

            # compute ranks
            answers = Discretizer._sort_rank(answers, 'upvotes', reverse=True)
            answers = Discretizer._sort_rank(answers, 'sentences', reverse=True)
            answers = Discretizer._sort_rank(answers, 'len', reverse=True)
            answers = Discretizer._sort_rank(answers, 'views', reverse=True)
            answers = Discretizer._sort_rank(answers, 'wordcount', reverse=True)
            answers = Discretizer._sort_rank(answers, 'avg_chars_per_word', reverse=True)
            answers = Discretizer._sort_rank(answers, 'avg_words_per_sentence', reverse=True)
            answers = Discretizer._sort_rank(answers, 'longest_sentence', reverse=True)
            answers = Discretizer._sort_rank(answers, 'time_difference', reverse=False)
            answers = Discretizer._sort_rank(answers, 'loglikelihood_descending', reverse=True)
            answers = Discretizer._sort_rank(answers, 'loglikelihood_ascending', reverse=False)
            answers = Discretizer._sort_rank(answers, 'F-K_descending', reverse=True)
            answers = Discretizer._sort_rank(answers, 'F-K_ascending', reverse=False)
            thread['answers'] = answers

        self.log('Done computing features for {0} threads'.format(len(threads)), logging.INFO)
        return threads

    @staticmethod
    def _ASPW(text):
        aspw = 0
        for word in text.split():
            s = Discretizer._count_syllables(word)
            aspw += s
        return aspw

    @staticmethod
    def _count_syllables(word):
        vowels = ['a', 'e', 'i', 'o', 'u', 'y']
        currentWord = list(word)
        numVowels = 0
        lastWasVowel = False
        for wc in currentWord:
            foundVowel = False
            for v in vowels:
                # don't count diphthongs
                if (v == wc) and lastWasVowel is True:
                    foundVowel = True
                    lastWasVowel = True
                    break
                elif (v == wc) and lastWasVowel is False:
                    numVowels += 1
                    foundVowel = True
                    lastWasVowel = True
                    break

            # If full cycle and no vowel found, set lastWasVowel to false;
            if not foundVowel:
                lastWasVowel = False

        # Remove es, it's _usually? silent
        if (len(word) > 2) and (word[len(word)-2:] == "es"):
            numVowels -= 1
        # remove silent e
        elif (len(word) > 1) and (word[len(word)-1:] == "e"):
            numVowels -= 1
        return numVowels

    @staticmethod
    def _FK(awps, asps):
        fk = (0.39 * float(awps)) + (11.8 * float(asps)) - 15.59
        return fk

    @staticmethod
    def _log_likelihood(answer_text, stemmed_vocabulary, distrib_matrix):
        LL = 0
        if answer_text is not '':
            tokens = word_tokenize(str(answer_text), language='english')
            porter_stemmer = PorterStemmer()
            unique_wordcount = len(stemmed_vocabulary)
            """
            per ogni w unica print_function words
                Cw = conta w in answer_text
                PwM = self.distrib_matrix[stemmer(w)]
                unique_wordcount = len(tokenize(answer_text)
            """
            for w in tokens:
                _w = w.strip().lower()
                Cw = 0
                for _ in answer_text.split():
                    if _w == _.strip().lower():
                        Cw += 1

                try:
                    w_stem = porter_stemmer.stem(_w.decode('utf-8', 'replace').encode('ascii', 'replace'))
                except AttributeError:
                    w_stem = porter_stemmer.stem(_w)
                try:
                    PwM = distrib_matrix[w_stem]
                except KeyError:  # key error means frequency is equal to cutoff point 1
                    PwM = 1
                LL += (Cw * log(float(PwM)))

            try:
                LL = "{0:.2f}".format(LL / float(unique_wordcount))
            except ZeroDivisionError:
                LL = 0

        return LL

    @staticmethod
    def _count_words(text):
        wordcount = 0
        for word in text.split():
            wordcount += 1
        return wordcount

    @staticmethod
    def _sort_rank(answers, key, reverse=True):
        new_list = sorted(answers, key=lambda x: float(x[key]), reverse=reverse)
        ranks = dict()
        for i in range(0, len(answers)):
            ranks[new_list[i]['uid']] = i + 1

        # fix rank ties
        for i in range(0, len(answers)-1):
            if new_list[i][key] == new_list[i+1][key]:
                ranks[new_list[i+1]['uid']] = ranks[new_list[i]['uid']]

        for k, v in ranks.items():
            for a in answers:
                if a['uid'] == k:
                    a['{0}_rank'.format(key)] = v
        return answers

    def _has_codesnippet(self, text):
        code = False
        if re.search(r'({|}| package |\.jar| class | namespace |exception |<<| end | def |<\?php| soap | <xml| wsdl |\.cs|\.java|\.php|\.rb|lambda)',
                     text, re.MULTILINE | re.IGNORECASE):
                code = True
        return code

    def build_vocabulary(self, stems):
        vocabulary_filename = '{0}_vocabulary.txt'.format(self.db_name)
        if os.path.isfile(vocabulary_filename):  # load vocabulary from file
            words = list()
            self.log('Loading existing community vocabulary from {0}'.format(vocabulary_filename), logging.INFO)
            with open(vocabulary_filename, 'rt') as f:
                for word in f:
                    words.append(word.strip())
                f.close()
            vocabulary = sorted(set(words))
        else:  # create vocabulary and save file
            self.log('Creating new vocabulary into {0}. Please wait, this may take some time.'.
                     format(vocabulary_filename), logging.INFO)
            vocabulary = sorted(set(stems))
            with open(vocabulary_filename, 'wt') as f:
                for lemma in vocabulary:
                    f.write('{0}{1}'.format(lemma, self.linesep))
                f.close()
        return vocabulary

    def build_corpus(self):
        corpus_filename = '{0}_corpus.txt'.format(self.db_name)
        corpus = list()
        if os.path.isfile(corpus_filename):  # load corpus from file
            self.log('Loading existing corpus from {0}'.format(corpus_filename), logging.INFO)
            with open(corpus_filename, 'rt') as f:
                for word in f:
                    corpus.append(word.strip())
                f.close()
        else:
            self.log('Creating corpus from {0} database(s). Please wait, this may take some time.'.format(
                len(self.db_files)), logging.INFO)
            with open(corpus_filename, 'wt') as f:
                for name, _db in self.db.items():
                    self.log('Updating corpus from db {0}.'.format(name), logging.DEBUG)
                    for record in _db:
                        try:
                            tokens = word_tokenize(record['text'].decode('utf-8', 'replace').encode('ascii', 'replace'),
                                                   language='english')
                        except (AttributeError, TypeError) as e:
                            tokens = word_tokenize(str(record['text']), language='english')
                        for t in tokens:
                            corpus.append(t)
                            f.write('{0}{1}'.format(t, self.linesep))
                f.close()
        return corpus

    def build_stems(self, corpus):
        stems_filename = '{0}_stems.txt'.format(self.db_name)
        if os.path.isfile(stems_filename):  # load stems from file
            stems = list()
            self.log('Loading existing stems from {0}'.format(stems_filename), logging.INFO)
            with open(stems_filename, 'rt') as f:
                for stem in f:
                    stems.append(stem.strip())
                f.close()
        else:
            self.log('Creating stems from corpus into {0}. Please wait, this may take some time.'.format(
                stems_filename), logging.INFO)
            porter_stemmer = PorterStemmer()
            try:
                stems = [porter_stemmer.stem(token.lower().decode('utf-8', 'replace').encode('ascii', 'replace'))
                         for token in corpus]
            except (AttributeError, TypeError) as e:
                stems = [porter_stemmer.stem(token.lower())
                         for token in corpus]
            with open(stems_filename, 'wt') as f:
                for stem in stems:
                    f.write('{0}{1}'.format(stem, self.linesep))
                f.close()
        return stems

    def build_distribution_matrix(self, stems):
        distrib_matrix_filename = '{0}_distrib_matrix.txt'.format(self.db_name)
        if os.path.isfile(distrib_matrix_filename):  # load matrix from file
            self.log('Loading existing distribution matrix from {0}'.format(distrib_matrix_filename), logging.INFO)
            distrib_matrix = dict()
            with open(distrib_matrix_filename, 'rt') as f:
                csvrreader = csv.DictReader(f, delimiter=' ', lineterminator=self.linesep)
                for row in csvrreader:
                    distrib_matrix.update({row['w']: row['P(w|M)']})
                f.close()
        else:  # create matrix and save file
            self.log('Creating new distribution matrix into {0}. Please wait, this may take some time'.
                     format(distrib_matrix_filename), logging.INFO)
            distrib_matrix = FreqDist(stems)

            with open(distrib_matrix_filename, 'wt') as f:
                writer = csv.DictWriter(f, fieldnames=['w', 'P(w|M)'], delimiter=' ', lineterminator=self.linesep)
                writer.writeheader()
                for k in distrib_matrix.keys():
                    writer.writerow({'w': k, 'P(w|M)': distrib_matrix[k]})
                f.close()

        distrib_matrix = Discretizer.reduce_distribution_matrix(distrib_matrix, cutoff=1)
        return distrib_matrix

    @staticmethod
    def reduce_distribution_matrix(matrix, cutoff=1):
        reduced = {key: value for key, value in matrix.items() if int(value) > cutoff}
        return reduced

    def save_csv(self, threads):
        fout = '{0}_features.csv'.format(self.db_name)
        self.log('Saving features into {0}'.format(fout), logging.INFO)
        csvf = open(fout, 'wt')
        fields = ('resolved', 'question_uid', 'answers_count', 'answer_uid',
                  'date_time', 'time_difference', 'time_difference_rank', 'solution', 'len', 'len_rank', 'wordcount',
                  'wordcount_rank', 'avg_chars_per_word', 'avg_chars_per_word_rank', 'sentences', 'sentences_rank',
                  'avg_words_per_sentence', 'avg_words_per_sentence_rank', 'longest_sentence', 'longest_sentence_rank',
                  'views', 'views_rank', 'loglikelihood', 'loglikelihood_ascending_rank',
                  'loglikelihood_descending_rank', 'F-K', 'F-K_ascending_rank', 'F-K_descending_rank', 'upvotes',
                  'upvotes_rank', 'has_links', 'has_code_snippet', 'has_tags')
        writer = csv.DictWriter(csvf, dialect=csv.excel, fieldnames=fields, delimiter=';', lineterminator=self.linesep)
        writer.writeheader()
        # empty_line = dict.fromkeys(fields)
        for t in threads:
            row = dict()
            row.fromkeys(fields)
            answers = t['answers']
            # question with no answers are excluded
            i = 0
            for a in answers:
                i += 1
                if i == 1:
                    row['resolved'] = t['resolved']
                    row['question_uid'] = t['question_uid']
                    if len(t['tags']) > 0:
                        row['has_tags'] = True
                    else:
                        row['has_tags'] = False
                else:
                    row['resolved'] = ''
                    row['question_uid'] = ''
                row['answers_count'] = t['answers_count']
                row['answer_uid'] = a['uid']
                row['time_difference'] = a['time_difference']
                row['time_difference_rank'] = a['time_difference_rank']
                if a['resolve'] == 'solution':
                    row['solution'] = True
                else:
                    row['solution'] = False
                row['len'] = a['len']
                row['len_rank'] = a['len_rank']
                row['wordcount'] = a['wordcount']
                row['wordcount_rank'] = a['wordcount_rank']
                row['avg_chars_per_word'] = a['avg_chars_per_word']
                row['avg_chars_per_word_rank'] = a['avg_chars_per_word_rank']
                row['sentences'] = a['sentences']
                row['sentences_rank'] = a['sentences_rank']
                row['avg_words_per_sentence'] = a['avg_words_per_sentence']
                row['avg_words_per_sentence_rank'] = a['avg_words_per_sentence_rank']
                row['longest_sentence'] = a['longest_sentence']
                row['longest_sentence_rank'] = a['longest_sentence_rank']
                row['views'] = a['views']
                row['views_rank'] = a['views_rank']
                row['loglikelihood'] = a['loglikelihood']
                row['loglikelihood_descending_rank'] = a['loglikelihood_descending_rank']
                row['loglikelihood_ascending_rank'] = a['loglikelihood_ascending_rank']
                row['F-K'] = a['F-K']
                row['F-K_descending_rank'] = a['F-K_descending_rank']
                row['F-K_ascending_rank'] = a['F-K_ascending_rank']
                row['upvotes'] = a['upvotes']
                row['upvotes_rank'] = a['upvotes_rank']
                row['has_links'] = a['has_links']
                row['has_code_snippet'] = a['has_code_snippet']
                row['date_time'] = a['date_time']
                writer.writerow(row)
            #writer.writerow(empty_line)
        csvf.close()

redpajama_set_name: RedPajamaGithub


awkward silence, and a question and answer kind of session. The connection was there. We flowed like we have known each other for ages. Within me, I knew that whenever I decide to pop the question, the answer is going to come out in positive.
We talked school politics, state politics, religion, culture and every other thing that was left to be talked about. Her view were so articulate. She seemed to know a lot about everything. I was impressed by her views and I also made sure to leave an impression with her.
I hailed a cab as we got outside the café. About to hop into the waiting car, an "excuse me sir" caught me in my track. I turned to see a waiter walking towards me. I did a quick mental check. I know I paid my bills because I still have the receipt. We didn't leave our phones behind or anything.
"Sorry sir, someone said I should give this to you" she said handing over a piece of paper with #700 to me.
From the way she talked, I know she didn't want Cindy to hear what she was saying.
"What for?" I asked collecting the paper together with the money from her.
"I don't know, she just said I should give it to you" she said and went back inside the café.
I took a quick glance at the note and saw a phone number with a 'call me' written under it. Below the call me was another line that read 'tell her you forgot your change if she asks'. I tried to scan the café but I couldn't get a clear view.
"Oga if you no dey go again, tell your wife to come down make I comot from here" the cab man shouted at me. I folded the paper together with the money and inserted it into my pocket and hopped into the waiting cab.
"Oga abeg no vex" I apologized to the driver to which he nodded and eased the car into motion.
"You go drop my wife for Okeke hostel and the drop me for hilltop gate." As I said wife, Cindy raised her head for the first time from her phone and smacked my shoulder smiling revealing a beautiful set of dimples.
"Ok your money na 5H" he said throwing away his gaze through the window.
"You self, person wey God don bless give you this kind babe wetin come be 5H na" he said turning to look at me. I took a quick look at Cindy and she was smiling. Looking at the driver, we made eye contact and he dimmed his eyes.
"No wahala sha. Even if you no carry money, I for carry una free because of this your girl" he said smiling at Cindy.
"Ok o, thanks man" I said and made a wink at him through the rear view mirror. Cindy was so engrossed in whatever she was doing with her phone to notice the winks going on. The driver continued with his yarns doing the 'chyking' for me. Cindy couldn't help but kept smiling as the driver didn't seem tired of praising her beauty.
My mind drifted away to the note as the driver kept talking. I had the urge to bring the note out and check if I can be able to recognize the number, but I decided against it. There will be enough time to do that.
Five minutes later saw us in front of Cindy's hostel. I alighted and held the door for her to step out. She came down still flashing that beautiful smile.
"Thanks for coming out with me" I said as we walked a bit down her hostel.
She turned and gave me a big bear hug. Not like the one she gave me when I came to pick her earlier on. This one came with a meaning, yes it did. You know that kinda hug were a girl presses herself so hard on you that you feel she is about to rip your heart out? Yes that the kind of hug she gave me.
"I enjoyed myself " she whispered into my ear. That sent a tingling sign down my spine to the man below who responded immediately. With the way she was pressed to me, I know she must have felt my semi attention. As she disentangled herself from me, my hand went down straight inside my pocket to hide the tent that was already forming down below.
I stood watching her sheepishly as she walked straight to her hostel. I watched as she swayed her backside as if she has no waist bone. As my sight was focused on her back, so many thought were running through my mind. Cindy is the kind of girl that attracts so much attention to herself. Not that she does that intentionally but she is just too endowed.
When she got to her hostel entrance, she turned and saw me staring at her. She smiled and blew me a kiss in the air before walking into the hostel. That action of hers got many guys and babes around looking towards my direction. It was then I realized that I wasn't the only person looking at her.
"Oga your phone dey ring" the driver said bringing my mind back. It was then that I realized that I was even with a cab.
"Ah! My oga sorry o, no vex" I apologized collecting the phone from him. It was Cindy calling. I picked leaning on the car.
"If you don't leave my hostel now, I will call the security for you" she said giggling from her end of the phone.
"Provided I will still see you when they arrive, no problem" I said.
"Mr lover boy, na so I don shark your head reach" she said laughing.
"Oya e don do. Start going and lemme know when you get home" she said.
I went around and hopped into the front seat of the cab. I apologized to the driver for keeping him waiting but he replied "not to worry" as he also enjoyed the show. As he eased the car into motion, I brought out the note and the money. I gave the money to the driver and folded the note back into my pocket. He was all smiles when I gave the money and he kept showering me with praises. When we got to gate, I alighted and collected his number promising to call him anytime I need a cab service.


text:
Textile Design (Top-up) BA (Full-time)
Chat live with students from London Met
All available course dates
Courses in London
London (English)
This is a top-up version of our Textiles BA (Hons) degree. A top-up degree is the final year (Level 6) of an undergraduate degree course and is for those who have a foundation degree, Higher National Diploma or equivalent qualification, or those wishing to study the final year of their degree in London.
On the Textile Design BA (Top-up) you'll learn technical skills through exploring a variety of subject areas including textile design for interiors and fashion and accessories. There will be opportunities to produce collections of textiles, surface techniques and garments and to showcase in a professional setting.
You'll have opportunities to enter local and international competitions, to exhibit your work and to visit industry and trade shows in London, Paris and Florence.
Do you want to know what it's like to study at London Metropolitan University? Visit the link below to student ambassadors and get answers to all of your burning questions about academic and student life.
Find a student ambassador
In addition to the University's standard entry requirements, you should have one of the following:
240 credits from a relevant Higher National Diploma (HND), Foundation Degree (FdA/FdSc) or equivalent international qualification in a relevant subject
240 credits from years 1 and 2 of an undergraduate degree (BA/BSc) in a relevant subject at a different institution
a portfolio interview
We encourage applications from international/EU students with equivalent qualifications. We also accept mature students with diverse backgrounds and experiences.
For more information about admission requirements, please visit the university website.
3D Project Design & Development
Critical & Contextual Studies 3: Dissertation (3D)
Major Project Realisation: Textile Design
Modules and module details are subject to change over time.
Several scholarship options are available. Please visit the university website for more information.
How much you pay in tuition fees depends on which country you come from and whether you are a full-time or part-time student. Please visit the course page on university website for fee information particular to that course.
Upon completion of the degree you could progress on to a master's course.
Upon completion of the degree you could enter textile, fashion or interior design roles including designer-maker, industry designer, buyer, technologist, stylist and design journalist.
Our graduates have gone on to work at companies including Timberland, Harrods, the Fashion Model Directory and River Island.
Want to know more about this program, Textile Design (Top-up) BA (Full-time)? Fill out the following form and include any questions you have. This information will be sent directly to the school, and a representative will respond to your enquiry.
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Based in England's historic capital city, London Metropolitan University has a rich history of education with its roots dating back to 1848. Taking its current form following a merger of two well-renowned universities in 2002, it offers a wide range...
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Show phone number Phone no: +44(0)20 7133 4200
http://www.londonmet.ac.uk
Want to know more about Textile Design (Top-up) BA (Full-time)? Fill out the following form and we'll pass your details on to a representative from the school, who will respond to your enquiry.
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Bachelor in Textile, Design
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Into the Legend stands closer to earlier Rhapsody's works such as Dawn of Victory 1999 or debut album Legendary Tales 1997. Most of the songs has this dream-like atmosphere and there are many tracks which are indeed long just like a closing one. Those longer songs has quite complex song- writing and, indeed, most of the record stands as a very complex piece of work. Once again Alex has proved himself on keyboards and orchestrations while Fabio has done some amazing stuff on vocals. If you like fantasy and symphonic stuff, then their newer effort is a right solution. Call it however you like but brand new Rhapsody of Fire sounds, in the same time, very powerful and symphonic. Some of the songs are more direct like the title track but also there are several tracks with more complex themes so in a way one could find some links between a new one and Symphony of the Enchanted Land Part I 1999.


text:
Q: Resetting state in ngxs When I add some new data to my state, the new data does not appear in my log or DevTool Ui.
Is there a mechanism to reset the state so that the data will appear. It seems that the old data from some cache is still being shown.
Thanks

A: In v3.1 there is a reset function on the store that allows you to reset state see the docs here

A: I prefer to use this reset plugin; https://github.com/ng-turkey/ngxs-reset-plugin
It's an ngxs plugin, easy to implement.

A: You can simply add an action to your app.state.ts file as follows

The Action to reset the state

@Action(ResetAppState)
resetState(ctx: StateContext<AppStateModel>): Observable<AppStateModel> {
   return of(ctx.getState()).pipe(
      map(currentState => {
         ctx.patchState({/* enter initial/reset values here */});
         return currentState;
      })
   );
}

You must also add the action into the app.action.ts file as
export class ResetAppState {
  static readonly type = '[AppState] Reset App State';
}

Now you can dispatch the action in your service or component easily to reset the NGXS state as follows:
constructor(private store: Store) {}

yourMethod(): void {
    this.store.dispatch(new ResetAppState());
}

A: For state reset I try to use "meta-reducer" concept via plugin (https://ngxs.gitbook.io/ngxs/advanced/meta-reducers), but I have trouble with re-initialize state to default value for each slice.

redpajama_set_name: RedPajamaStackExchange


Cat lovers enjoyed a lovely morning in the sunshine to help raise funds for Bluebell Ridge on Tuesday 2 May.
Bluebell Ridge saw a great turnout for their first coffee morning at the centre, which raised over £200 for the cat rehoming centre in Hastings.
The public had the chance to enjoy home-made cakes, walk along the bluebells and visit the cats that are looking for their furrever homes.
Due to the interest and success of the coffee morning, the centre plans on holding another one in a few months' time – with a date to be announced soon.


High quality, tailored and casual menswear.
Jos. A. Bank carries an extensive selection of beautifully made tailored and casual clothing for men, as well as classically styled footwear and accessories. Their experienced tailors keep a close eye on every detail, and adhere to the highest standards of fabric, fit and construction.


text:
import React from 'react'
import { shallow } from 'enzyme'

import Component from './index'

test('should just pass', () => {
  expect(<Component value={0} />).toMatchSnapshot()
})

test('should return `Yeah!` if value is 17', () => {
  const actual = shallow(<Component value={17} />)

  expect(actual).toMatchSnapshot()
})

test('should return `Naah!` if value is not 17', () => {
  const actual = shallow(<Component value={42} />)

  expect(actual).toMatchSnapshot()
})


The term 'half-bath' is not used with respect to the size but the usage and the options of things that can be done inside the room. A half bath usually has a sink or a basin and a toilet. It lacks the shower or a space to take a bath. However, sometimes there are half baths which are big in size but do not have the option of a shower. Variations are also called powder rooms, men's bathroom, etc.
When thinking of a space for building the half-bath try to think of some unused or ignored place so that you don't intrude on important and necessary space. It can be beneath the staircase or the basement or maybe a large unnecessary storage closet. However, it would be best to choose a place which is close to the water and sewage pipe connectivity lest you want to completely remodel your house. Since half-baths are already small in size, use space saving, sleek and smart things such as a single vanity which has storage space beneath for your towels and napkins. Baskets can also be kept and if possible, you can keep the bin under the vanity too which makes the place appear tidier as well.
The main intention of starting the half-bath was probably to increase the value of houses on sale. There is always an element of attraction associated with novelty – be it necessary or not. However, half baths can be built with care and intelligence and can be a sign of your care towards home making. It can be a great space for doing other things which you do not have room for in your house otherwise. For example, it can be used for doing the laundry. If you have a slightly bigger space, you can utilize a portion of the room to create a laundry section.
In most houses, half-baths are for guests and hence their functionality and good looks should go hand in hand. Everything from the lighting to the positioning of things should be correct so as to maximize utility and minimize confusion. Recessed lighting does a great work at half baths owing to their no hankering for space and top light effects. Lighter colors as always go for the walls and the floor. You can also try wallpapers of pastel shades instead of plain colors. Remember that half-baths are more about being user-friendly and hence you do not need to put in too many things, especially since it is not meant to be a space for taking baths. Keep whatever is necessary and never keep what isn't. A small shelf with a mirror is a perfect choice for half-baths. The shelf will be good to hold brushes, pastes, soaps, face washes, liquid soaps, hand washes, a few basic medicines, tissues and the like. What you can do is choose the vanity, the shelf, the mirror with care so that they look a little out of the ordinary and speak for themselves.


text:
Saklatvala and the Indian workers
Submitted by AWL on 30 September, 2020 - 8:05 Author: Sacha Ismail
25 of the accused in the Meerut conspiracy case
This is part five of a series. For the other articles, see here.
Buy our pamphlet on Saklatvala here.
"Mr Saklatvala… has great influence in India. Irrespective of his Communist views, the Indian people are proud of him… They, a subject race… are naturally proud of the courage with which Saklatvala, one of themselves, denounces the British domination of India in unmeasured terms in the very House of Commons itself. He is a rebel by proxy for them all… When he speaks to them, therefore, they listen, and he speaks to them frequently."
- "India's lost faith in Labour", Socialist Review, 1928
Saklatvala campaigned for reforms in British India, short of independence and socialism. In particular he focused, through organisations including the Workers' Welfare League of India, on demands for workers' rights. He also advocated the complete overthrow of British rule in India and the British Empire.
During his time as an MP, Saklatavla continually and insistently expressed this wider position. In 1927, when Parliament discussed the creation of an all-British "commission" on the future of India, he protested in the Commons:
"May I ask the House just to review the historical position from 1910 to 1914? There was the Kaiser in Europe. He also felt the same thing [as the Tories argued about India], that... there was such a welter and chaos that one strong man was required to rule the whole of Europe. He failed. You succeeded. That is the only difference, but the claim of the Kaiser and the British Kaisers is equally preposterous from the ethical standpoint and the point of view of national rights."
His speech repeatedly assailed the idea that British rule was somehow intended to bolster the rights of minorities or any working people in India:
"Who are the majority of the Indian people? Never mind the Hindus and Mohammedans, because religious differences exist in all nations of the world. The majority of the people of India are peasants and agriculturalists. The majority of the people in the large cities are industrial workers. What rights have you given to them? … What is the purpose of this country's rule in India? To keep talking of minorities and to trample on the rights and progress of the majority."
"It is not your fault", added Saklatvala. "The Romans did the same thing once when they were ruling your country. My ancestors, the Persians, did the same thing when they were ruling the Jews, the Assyrians and the Turks."
In 1923, during his first year in Parliament, he had intervened in a debate about the role of Britain's Viceroy by denouncing "the right of this country to send a Viceroy at all". Although he perhaps shifted towards a more aggressively anti-colonial stance during the 1920s, he had held the same basic position for decades.
India's rising tide
Saklatvala's rise to prominence coincided with a rising tide of India's national liberation movement – not coincidentally, since the Russian revolution and its ripples set the context for many rising anti-colonial struggles as well as the working-class upsurge in Europe.
Also important was the upheaval of the war, in which Allied leaders proclaimed a principle of self-determination but did not apply it to colonies of the victorious powers. So was British repression: in 1919 the government suspended the rights of defendants in sedition trials and the army murdered many hundreds of civilians in Amritsar. This in the midst of a "Spanish flu" pandemic in which maybe 18 million Indians died. In 1919 the Indian National Congress moved away from cooperation with the British authorities and launched a struggle for complete independence.
In Britain too campaigning around India began to tilt in a more radical, strongly pro-independence direction. Saklatvala, a major figure among both Indian nationalists and British labour movement activists, was a force in bringing the shift about.
India saw a growth of specifically working-class and socialist struggles. As the 1931 Royal Commission on Labour in India expressed it, from the early '20s there was a "realisation of the potentialities of the strike" and "industrial strife became almost general". Groups of socialist workers, labour organisers and intellectuals organised and intervened in this ferment. The Communist Party of India was founded as a solid organisation in 1925.
In 1927 Saklatvala toured India for three months, pledging – as he put it in an appeal to the Daily Herald for solidarity messages – "a great effort from the Indian end to pull the two working-class brotherhoods [Indian and British] together". He got an overwhelming reception, speaking to thousands wherever he went. The authorities of nine cities formally welcomed him, despite the undemocratic nature of local government in India and opposition from British officials.
Saklatvala used his "megaphone" to encourage working-class and peasant organisation, and to urge young nationalists to help workers assert themselves, including by taking jobs in industry. Behind the scenes he helped build and organise the CPI in the areas he visited.
While he was in India he engaged in polemics with Mohandas Gandhi, in written exchanges and on one occasion in person. He criticised Gandhi's limited and in many ways backward-looking perspective, counterposing the organisation of workers and peasants to struggle for their rights against capitalism:
"The acuteness with which the class war operates upon the wage-earners of India is more than in most of the advanced European countries... The class war in India is murderous... to throw dust in the eyes of the world that class war is not operating in India is inhuman and monstrous... Class war is there and will continue to be there until... Communism abolishes it. But in the meantime, not to struggle against its evil effects day to day is a doctrine which cannot appeal to any genuine humanitarianism..."
He demanded an end to the "moral plague" of cult-like devotion which surrounded the nationalist leader, including his use of the honorific "Mahatma" ("Great Soul" - venerable or holy man). Gandhi's replies praised Saklatvala but, unsurprisingly, firmly disagreed.
How the British government viewed all this can be judged by the fact that, on Saklatvala's return to the UK, it announced his passport would no longer be valid for travel to India. This ban remained in place for the rest of his life, including under the 1929-31 Labour government.
Six months after Saklatvala arrived back, the government appointed its commission on India. Chaired by right-wing Liberal MP John Simon, it was made up entirely of white British politicians – including two Labour MPs, one of them Clement Attlee. The Labour leadership backed the commission; Indian nationalists called for the party to withdraw its support and representatives.
When the commissioners arrived in India in 1928, they met a very different reception to Saklatvala's, with mass protests and strikes ("Simon, go back"). After police attacked demonstrators to clear the way for the commission in Lahore, nationalist leader Lala Lajpat Rai died of his injuries. Saklatvala helped organise the fight against the commission, in the name of full independence, in Britain.
Anti-imperialist organising
The CI's work in the colonies was organised primarily by a network led by Manabendra Nath Roy; he and Saklatvala had important differences, including on how Communists should relate to India's bourgeois nationalists, and Saklatvala was increasingly distrustful of and hostile to Roy. As a result he was often excluded (or self-excluded) from the International's colonial work.
He did nonetheless play a significant part, due to his position in the British CP and as an MP. The British party was responsible for work in India until the CPI was firmly established in 1925. Saklatvala undertook various roles, from establishing CI connections while travelling as an MP; to liaising with and helping set up unions in India; to interviewing Indian students in Britain who could help build the CP when they returned home. Even after the establishment of the CPI, his status made him an important international liaison, as his 1927 tour demonstrated.
He played a high-profile role in the League Against Imperialism – a network of activists in many countries and colonies founded on the initiative of the CI in 1927, named as an attack on the League of Nations, which had perpetuated colonialism by handing territories over to European control as "mandates". Through the LAI he supported anti-colonial struggles in other parts of the world, for instance in Nigeria.
The LAI was an early venture by Willi Münzenberg, a Stalinist who – after leading the international campaign for Sacco and Vanzetti – managed to put together a number of Popular Front-type show events even in the midst of the "ultra-left" Third Period. Trotsky described the LAI as a "masquerade", and one of the leading groups featured in the first LAI congress was Chiang Kai-shek's Guomindang, which only two months later would massacre the Communist-led workers in Shanghai. By the time the organisation folded in 1937, the Stalinists were minimising their opposition to the imperialism of the Western "democracies" in search of military alliances against Nazi Germany.
In 1927 the Communist Parties were as yet far from completely Stalinised, and for Saklatvala and many others in the British labour movement, the LAI meant militant opposition to colonialism.
Communism on trial
In 1928-9 over 31,000,000 worker-days were lost to strikes in India, and the depression further energised workers' and peasants' struggles. The growth of working-class militancy and Communist activism alarmed the British authorities, who intensified their repression. In 1929 this came to a head with the Meerut conspiracy case, named after the small town near Delhi where the trial took place. 32 left-wing labour organisers, 29 Indian (of diverse religious and ethnic origins) and three British, were charged with attempting to "deprive the King Emperor of his Sovereignty of British India" and "incitement of antagonism between Capital and Labour".
Naturally many of the accused were Communists. The charges referred extensively to Communists and the International. Britain's Viceroy wrote of his hopes of dealing a "severe blow to the Indian Communist movement".
As word of the arrests spread, there were big protests, including strikes in Bombay's textile industry. It was the beginning of a major struggle.
The international campaign was led by organisations in which Saklatvala was prominent, including the League Against Imperialism and the Workers' Welfare League of India. Before and after losing his parliamentary seat in 1929, he spoke and campaigned prolifically for the liberation of the prisoners, who were guilty of "no more heinous a crime than openly and legally organising workers and peasants in India" (London May Day, 1929).
After four years in the India's brutal prison system – in 1930 holding something like 23,000 political prisoners – sixteen were sentenced to transportation to a penal colony for between five years and life, and eleven to "rigorous imprisonment" for three to four years.
The Meerut trials took place mainly under a Labour government. The arrests occurred just before the 1929 general election in which Ramsay MacDonald returned to office; it was his Secretary of State for the Colonies, Fabian leader Sidney Webb, who allowed the process to go forward. Left-wingers such as George Lansbury, while critical of what was happening in India, remained in the MacDonald government while this scandal was taking place and as a result were relatively muted.
There was, nonetheless, serious unrest in the British labour movement about it, including in the Labour Party.
Later in 1933, in the midst of great agitation and protest, with a realisation that the affair was actually strengthening Communism in India, eight of the convicts were released and the remaining sentences greatly reduced – but no thanks to the Labour leadership.
The analysis Saklatvala made in the House of Commons in 1928 had been shamefully confirmed:
"The workers in Great Britain should realise that God has not created man to be ruled dictatorially and autocratically by another man. Through self-determination and mutual consent we should elect somebody to rule who is not a socialist boss, but a helper and adviser. If that is our essential belief, how can the people of this country believe that God has created the British Labour Party to rule the Indians and the Chinese? 'We are ruling you; we are sending Commissions to your countries because you are less experienced and we are more experienced, and we want to be kind to you and tell you how you should live your lives.' That is exactly what the capitalist masters and bosses are saying to the workers in this country. They say to them, 'We are more experienced in directing industry than you are, and we keep an Army, a Navy, and an Air Force to protect you...' Socialism believes that that sort of incapacity is not inherent in human nature. How can the Labour Party say that they are preaching socialism and collecting the majority of voices in favour of socialism when they are pursuing such a policy as I have described?"
• Part six here
• Part four, also about Saklatvala, India and colonialism, here
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In a statement issued on Monday morning by SANS Park, a pride of lions had devoured the remains leaving only a human skull and a pair of pants.
Brigadier Leonard Hlathihe said in a statement that he received information that some men had gone poaching in the KNP on 1 April 2019, when suddenly an elephant attacked and killed one of them.
"His accomplices claimed to have carried his body to the road so that passers-by could find it in the morning. They then vanished from the park," he said.
Subsequent to that, police launched a joint intelligence-driven operation in search of the dead poacher's accomplices, resulting in the arrest of three men, aged between 26 and 35. During the operation, two .375 hunting rifles and ammunition were seized.
The suspects had briefly appeared in the Komatipoort Magistrate's Court on Friday on charges of possession of firearms and ammunition without a licence, conspiracy to poach, and trespassing.
"According to the family of the deceased, they were called by his accomplices who notified them that their relative had been killed by an elephant while they were in the KNP to poach rhino on Tuesday evening. The family then called Skukuza Regional Ranger, Don English who, after assuring the family that he would do everything possible to recover the remains and bring them closure, arranged a search party. Rangers on foot, accompanied by members of the KNP Airwing flew over the area that was described by the family but due to failing light, could not locate the body.
Managing Executive of the KNP Glenn Phillips commended those who were part of the search party for helping the family find closure and extended his condolences to the relatives of the deceased.


text:
Q: Protocol message contained an invalid tag 0 My goal is to create a realtime service alert feed and send it over to a server that I made in Java with an HTTP post request. The first step I did was to create a copy of the example alert feed posted here and it seems I was successfully able to do that as I was able to print it out the message. https://developers.google.com/transit/gtfs-realtime/examples/alerts
The next step that I did is to create an HTTP connection and send the feed over with the POST request. This is what I have in my client code and example here is the feed name.
String url = "https://localhost:8080";
URL obj = new URL(url);
HttpsURLConnection con = (HttpsURLConnection) obj.openConnection();
//add reuqest header
con.setRequestMethod("POST");
con.setRequestProperty("User-Agent", "Mozilla/5.0");
con.setRequestProperty("Accept-Language", "en-US,en;q=0.5");
con.setRequestProperty("Content-Type", "application/x-protobuf");
con.setDoOutput(true);
DataOutputStream wr = new DataOutputStream(con.getOutputStream());
example.build().writeDelimitedTo(wr);
wr.flush();
wr.close();

My server code is simply this so far.
ServerSocket server = new ServerSocket(8080);
System.out.println("Listening for connection on port 8080 ....");
while (true) {
    try (Socket socket = server.accept()) {
      FeedMessage feed = FeedMessage.parseDelimitedFrom(socket.getInputStream());
      Date today = new Date();
      String httpResponse = "HTTP/1.1 200 OK\r\n\r\n" + today;
      socket.getOutputStream().write(httpResponse.getBytes("UTF-8"));
      }
}

The question here is that I get the Protocol message contained an invalid tag 0 on the server side. I would like some help on trying to resolve this issue. Maybe I am not parsing it correctly.
Update #2
I have tried to parse the HTTP headers to get to the payload like comments have said. But my code hangs and the output to print the headers on the terminal looks serialized.
    DataInputStream isr = new DataInputStream(socket.getInputStream());
    Reader reader = new InputStreamReader(isr);
    BufferedReader reader2 = new BufferedReader(reader);
    String line = reader2.readLine();
    System.out.println("get lines");
    while (!line.isEmpty()) {
         System.out.println(line);
         line = reader2.readLine();
     }

A: You are dealing with raw sockets at the server, but the payload is encoded in an http request body. You are going to need to parse the http request through to the payload, and when you have just the body : send that to protobuf. Right now, you're sending the http headers to protobuf, which doesn't make sense. That could mean parsing through to \r\n\r\n, but it would help if you could make use of the content-length header, and even better if you can use a pre-built http library.


text:
Banque de Tunisie et des Emirats (BTE) is a bank in Tunisia. It is listed in the Bourse de Tunis.

Overview
Banque de Tunisie et des Emirats was founded in 1982 as a result of an agreement between Tunisia and the United Arab Emirates. It is headquartered in Tunis, Tunisia. It is partly owned by the Abu Dhabi Investment Authority.

External links

References

1982 establishments in Tunisia
Banks established in 1982
Banks of Tunisia
Companies listed on the Bourse de Tunis

redpajama_set_name: RedPajamaWikipedia


text:
German Flatts es un pueblo ubicado en el condado de Herkimer en el estado estadounidense de Nueva York. En el año 2000 tenía una población de 13.629 habitantes y una densidad poblacional de 156.0 personas por km².

Geografía
German Flatts se encuentra ubicado en las coordenadas .

Demografía
Según la Oficina del Censo en 2000 los ingresos medios por hogar en la localidad eran de $32,772, y los ingresos medios por familia eran $39,380. Los hombres tenían unos ingresos medios de $29,973 frente a los $21,425 para las mujeres. La renta per cápita para la localidad era de $14,870. Alrededor del 13.7% de la población estaban por debajo del umbral de pobreza.

Referencias

Enlaces externos

Localidades del condado de Herkimer
Pueblos de Nueva York


text:
Khandi Alexander (ur. 4 września 1957 w Nowym Jorku) – amerykańska aktorka.

Filmografia
 Streetwalkin' (1985) jako Gwiazda
 A Chorus Line (1985) jako Tancerka
 Dziewczyna na posyłki (Maid to Order, 1987) jako Prostytutka
 Inny świat (A Different World, 1987-1993) jako Theressa Stone
 Zagrożenie dla społeczeństwa (Menace II Society, 1993) jako Karen Lawson
 Oddajcie mi moje dzieci (Shameful Secrets, 1993) jako Rosalie
 Nowojorscy gliniarze (NYPD Blue, 1993-2005) jako Sonya (gościnnie)
 CB4 (1993) jako Sissy
 Drzewo Jozuego (Joshua Tree, 1993) jako Maralena
 Poetic Justice – Film o miłości (Poetic Justice, 1993) jako Simone
 Tina (What's Love Got To Do With It, 1993) jako Darlene
 Sknerus (Greedy, 1994) jako Laura Densmore
 House Party 3 (1994) jako Janelle
 To My Daughter with Love (1994) jako Harriet
 Sugar Hill (1994) jako Ella Skuggs
 Ostry dyżur (ER, 1994) jako Jackie Robbins
 NewsRadio (1995-1999) jako Catherine Duke (1995-1998)
 No Easy Way (1996) jako Diana Campbell
 Kres (Terminal, 1996) jako Doktor Deborah Levy
 Cosby (1996-2000) jako Karen (1999) (gościnnie)
 Spawn (1997-1999) jako Lakesha/Pielęgniarka (głos)
 Nikita (Femme Nikita, La, 1997-2001) jako Terry (1998) (gościnnie)
 Rude Awakening (1998-2001) jako Juanita Wilson (2000) (gościnnie)
 Złodziejski trick (Thick as Thieves, 1998) jako Janet
 Sposób na blondynkę (There's Something About Mary, 1998) jako Joanie
 Partnerzy (Partners, 1999) jako Charlie
 X-Chromosome (1999) jako Yolanda (głos)
 Brygada ratunkowa (Third Watch, 1999-2005) jako Beverly Saunders (2000) (gościnnie)
 Prawo i bezprawie (Law & Order: Special Victims Unit, 1999) jako Karen Smythe (2001) (gościnnie)
 The Corner (2000) jako Denise Francine 'Fran' Boyd
 Policja (Dark Blue, 2002) jako Janelle Holland
 Fool Proof (2002) jako Icarus
 CSI: Kryminalne zagadki Miami (CSI: Miami, 2002) jako szef analiz medycznych Alexx Woods
 Śmiertelna pułapka (Emmett's Mark, 2002) jako Detektyw Middlestat
 Life's a Bitch (2003) jako Yolanda
 Idealni nieznajomi (Perfect Strangers, 2004) jako Christie Kaplan
 TV Land Moguls (ona sama, 2004)
 Deszcz (2006) jako Latitia Arnold
 Narodziny obłędu (First Born, 2007) jako Dierdre

Linki zewnętrzne

Urodzeni w 1957
Amerykańskie aktorki filmowe
Ludzie urodzeni w Nowym Jorku


text:
Stephen Hoiles is a former Australian rugby union player. He played Super Rugby for the New South Wales Waratahs and previously turned out for the . He also represented the Australia national rugby union team 16 times between 2004 and 2008. He currently is the head coach of the LA Giltinis in Major League Rugby (MLR) where he won a championship in the team's inaugural season.

Career
Stephen Hoiles is a former International Rugby Union player for Australia. Hoiles represented the Wallabies for the first time in 2004 at the age of 22 in the Test match against Scotland. Prior to this he had represented Australia in 7's Rugby Union at the age of 20. His professional career spanned over 13 years with some significant setbacks along the way.

Stephen grew up in Sydney and is a member of the Randwick Rugby Club where he won the 2004 Sydney Club competition. His father Alan is also a former 1st grade player at Randwick who won three 1st grade premierships in the 70's.

Stephen played over 100 first grade games for his club side Randwick as well as over 100 Super Rugby games for the NSW Waratahs and the ACT Brumbies where he was captained for 3 seasons. His professional playing career was put on hold for three & a half seasons with a long term achilles injury. During this time Hoiles travelled to Sweden to have his foot operated on. This surgery allowed Hoiles to return to Professional Rugby where he joined the NSW Waratahs and was a starting member of the Super Rugby Championship winning team in 2014.

Having retired from playing in 2015, Hoiles began his role as a Rugby Commentator and TV presenter with Fox Sports. In 2018 Hoiles began coaching professionally where he is the current assistant coach of the Australian Mens 7's team.

https://www.smh.com.au/sport/rugby-union/nsw-waratahs-forward-stephen-hoiles-playing-through-tenacity-20140724-zwiz9.html

https://www.rugby.com.au/news/2018/09/21/hoiles-sevens-walsh

References

External links

Randwick profile
It's Rugby player profile

1981 births
Australian rugby union players
Australia international rugby union players
ACT Brumbies players
New South Wales Waratahs players
Living people
Rugby union number eights
Rugby union flankers
Rugby union players from Sydney
Male rugby sevens players
New South Wales Country Eagles players
Barbarian F.C. players


Grab some rays with the Julbo Eyewear(R) and the MonteRosa Sunglasses.
Performance sunglasses for glacier-ready travel.
Lightweight frames made from flexible nylon.
Wraparound style with single-bridge design.
Contoured arms with Grip Tech pads for added stability.
RX Trem(R) frame can be equipped with corrective lenses.
100% UVA, UVB, and UVC radiation.
Spectron4 lenses: Cat. 4 lens with flash +AR coating. It is suitable for all sports where there is exceptionally bright sunlight.
WARNING This product can expose you to chemicals including Bisphenol A (BPA), which is known to the State of California to cause cancer and birth defects or other reproductive harm. For more information go to www.P65Warnings.ca.gov.


Velocity Robotics is pioneering the internet of power tools.
Are you a part of Velocity Robotics? Fill out the form below to request a user license from your company admin or to inquire about membership.


Persson, Kristin. Materials Data on Rb2TlInF6 (SG:225) by Materials Project. United States: N. p., 2016. Web. doi:10.17188/1316831.
Persson, Kristin. Materials Data on Rb2TlInF6 (SG:225) by Materials Project. United States. doi:10.17188/1316831.


DHCR has been roasting and serving quality coffee in Truckee since 2014.
Stop by our shop any day of the week 7am - 5pm.
Our goal is to provide Tahoe with a comfortable, unique communal space, freshly roasted specialty coffee, and excellent service.
Dark Horse Coffee Roasters has a bit of a cult following in southern California and now their fresh roasted coffee is located in Truckee in a stone building that used to be a saloon.
See Whats Brewing: It's crucial to leave the resorts to experience the true vibe of Tahoe. After snowboarding in the sunshine for a few hours, we headed to downtown Truckee. First stop: Dark Horse Coffee Roasters for a pick-me-up. Lattes in hand, we perused the books, pet all the dogs, and lounged for a bit before exploring the rest of the laidback town.
Dark Horse After Hours · Truckee's Underground Music Scene.


Tyron Woodley's comeback clash with Darren Till is set to fascinate UFC fans this weekend.
Last week, Woodley was 4/5 with bookmakers to beat the Englishman, who was at that point a 12/11 underdog.
A week later, however, and Till is now favourite with some bookies, while most price the pair at an identical 10/11.
It's easy to see why the likes of Bet365, Sky Bet and William Hill can't separate the two fighters. Welterweight champion Woodley, a standout wrestler on a four-fight win streak, has been out of action since last July while recovering from shoulder surgery.
Till, meanwhile, only got his shot after interim champion Colby Covington pulled out. His odds have steadily risen, though, due to his unbeaten record, impressive wins over Stephen Thompson and Donald Cerrone and 10 KO victories.
So often, mixed martial arts fights boil down to a clash of styles. Certain fighters are known for their wrestling supremacy and, on paper, Woodley is the master grappler here, boasting a takedown accuracy of 45.6% and a 94.8% takedown defence.
Till is the theoretical striker who prefers to stand and trade, averaging 2.67 significant strikes per minute thanks to his unique style and solid counterpunching.
Woodley is a great striker in his own right and, adding to the intrigue, Till is seen by many as an underrated grappler.
Still, the fighters' reputations reflect clearly in their odds. Till is the 2/1 favourite with Betfair to win via KO, TKO or disqualification, while Woodley is 11/4 with the same bookmaker to win via decision. In the latter market, Till is 7/2.
Both recently proved they can last the distance and the overall round betting favours a points verdict.
In other words, it's too close to call. Who needs Conor McGregor to keep things interesting?


text:
Tag Archive for: Mississippi
Mississippi's Claim That Tennessee Is Stealing Groundwater Is A Supreme Court First
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