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text:
Poland: Trial Of 14 Former Nazis Accused Of War Crimes Moves From West Germany To Poland. 1977
VLVA8371DADTGKHNW6HW4DWZ7IU3K-POLAND-TRIAL-OF-14-FORMER-NAZIS-ACCUSED-OF-WAR-CRIMES-MOVES-FROM
In Poland a jury has started hearing evidence against 14 former Nazis accused of war crimes at a concentration camp near the town of Lublin.
GV Majdanek prisoner of war camp in Poland (3 shots)
GV Judges standing outside district court building in Lublin
GV INTERIOR District court President Mr. Ludwik Przyzlak addressing judges (2 shots)
GV EXTERIOR Government building
GV Judge entering courtroom
GV Polish witness, Dr. Aglaida Jaworska entering and being questioned by judge
In the earlier stages of the trial there have been few witnesses able to provide concrete evidence against the defendants. Most German witnesses said they could not remember details of events which occurred 34 years ago. But Polish journalist Anders Stanislawski, who testified in Dusseldorf, pointed at one of the accused, Emil Laurich, and said he had been given the nickname 'Angel of Death' at Majdanek. He would call out prisoners at roll call to send them to the crematorium and crack his whip over their heads in such a way as to 'knock out their eyes'. The trial is expected to be the last war crimes trial staged by the Germans, who have set a 1979 deadline for ending wartime murder prosecutions.
Initials BB/0300
Background: In Poland a jury has started hearing evidence against 14 former Nazis accused of war crimes at a concentration camp near the town of Lublin. The trial began in Dusseldorf two years ago but moved to Poland on Wednesday (5 October) to hear witnesses too old or ill to travel to West Germany.
SYNOPSIS: At least 250,000 prisoners died in the Majdanek concentration camp in western Poland during the Second World War. They were killed by the Nazis in the camp's gas chambers or through other forms of liquidation. Aside from Auschwitz, Majdanek was the biggest Nazi concentration camp but unlike Auschwitz it wasn't destroyed by the Germans. Majdanek has been preserved by the Poles and turned into a national museum. All the major features including the gas chambers -- and a mound of ashes -- have been preserved.
None of the 14 defendants, who are accused of murder, are attending the hearings in Lublin. They're all free on bail in West Germany. District court President Ludwik Przyzlak is presiding over the sessions, which are expected to last until the end of November before the trial resumes in Dusseldorf. On Saturday (8 October) the court was due to visit the camp itself and a number of witnesses too old or infirm to travel at all were to be questioned in their homes.
The Polish authorities said the evidence they had gathered included 'horrific' tales of Majdanek prisoners being gassed shot, drowned or dying of neglect.
Altogether 30 witnesses were due to give evidence in the capital of Warsaw and the city of Gdansk as well as Lublin.
On Wednesday the only witness to appear was 63 year old woman doctor Aglaida Jaworska, who worked for the Nazis at the Majdanek camp. She said the saw SS men select Jewish women for extermination at daily roll calls. Dr. Jaworska said Nazi doctors pointed with their whips at up to 60 weaker inmates a day who were then taken to be gassed. The Majdanek case is West Germany's longest war crimes trial and may not finish until 1980.
POLAND:
POLAND.
VLVA8371DADTGKHNW6HW4DWZ7IU3K
Reuters - Source to be Verified
Nuremberg Trials
Lawyers discuss the Germany's aggression towards several European countries before the war.
Footage of Nuremberg trials in progress. Evidence given on German aggression on Austria.
Auschwitz Guards On Trial
The guards of Auschwitz concentration camp on trial at Cracow, Poland.
Andre Robineau Trial Poland
Trial of Andre Robineau and others accused of spying. Szczecin, Poland.
Before The Warsaw Trials
German War Criminals, former rulers in Poland, are flown to Warsaw for their trial.
Josef Buhler, Ex Premier On Trial AKA Josef Buhler On Trial
Josef Buhler in Court
Kalevi Concentration Camp Memorial
People of Poland hold memorial service at Kalevi Concentration Camp. Also flashbacks of trial.
Forster Trial.
Albert Forster, former Gauleiter and Lt Gov of the Gdansk area on trial for war crimes at Wrzeazcz.

redpajama_set_name: RedPajamaCommonCrawl


text:
El Mosaico de la caza del ciervo (aprox. 325-300 a. C.) es un mosaico descubierto dentro de la casa denominada "Casa del rapto de Helena" en Pela, la antigua capital del reino de Macedonia. La obra, hoy conservada en el Museo Arqueológico de Pela en esa ciudad, está firmada por el artista griego Gnosis pero se considera que puede haber sido inspirada por una obra pictórica de Melancio de Sición. Los sujetos representados se identifican normalmente con Alejandro Magno, Hefestión y Péritas, el perro de Alejandro.

Descripción
La disposición de las figuras, con los cazadores a ambos lados de la presa, las armas levantadas, y la atención del animal (en este caso la mirada) dirigida al hombre a la derecha del espectador (es decir Alejandro), recuerda a otro mosaico descubierto en Pela: el "Mosaico de la caza del león" donde los sujetos representados son Alejandro y otro de sus generales, Crátero. El elemento discordante en el mosaico del ciervo es, además del ciervo en lugar del león, el perro representado en el centro, colocado delante del ungulado y de espaldas al espectador.

Interpretación
El cazador a la derecha del ciervo, armado con una espada, podría ser Alejandro Magno. El cazador a la izquierda, está armado con un hacha de doble hoja. Comunes en la época minoica y micénica, después solo se mantuvieron como elemento ritual y arma tradicionalmente ligada al dios griego del fuego y la forja Hefesto, por lo que se cree que es una alusión al nombre del retratado e identificado con el general macedonio Hefestión, amigo y amante de Alejandro. El perro de caza en consecuencia se identifica con Péritas, el perro de Alejandro cuyo nombre ha sido trasmitido por las fuentes históricas antiguas (Flavio Arriano, Diodoro Siculo, Plinio el Viejo).

Referencias

Alejandro Magno
Mosaicos
Arte helenístico
Perros en el arte
Ciervos en el arte
Caza en el arte

redpajama_set_name: RedPajamaWikipedia


text:
Q: vue js css modules are giving the same names to elements in each rendering I am working on a vue project and I made CSS as modules so that I can assign different class names to different elements.
But the component containing the CSS module is rendering multiple times like:
     <ButtonGroup
      v-for="(i, index) in buttons"
      :key="index"
      :label="i.label"
      :buttons="i.names"
      class="mt-3"
    ></ButtonGroup>

the button group component renders the buttons like this
 <button
        v-for="(i, index) in buttons"
        :key="index"
        type="button"
        @click="changeClass"
        class="btn"
        :class="[index < 1 ? [$style.active, $style.btnNew] : [$style.btnNew]]"
      >
        {{ i }}
      </button>

It assigns class names like
src-components-inputs-buttonGroup---active---PEcjn src-components-inputs-buttonGroup---btn-new---3RluI

But I want different class names in each rendering of same component

redpajama_set_name: RedPajamaStackExchange


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Need Digital Marketing experts ASAP. ------------------------------------------------------------------------------- Additional Information Added on 1st Dec, 2017 Please share your portfolio and phone number at (removed). ------------------------------------------------------------------------------- Additional Information Added on 1st Dec, 2017 Please share your portfolio and phone number at (removed).


text:
"""

Authors:
 - Frank Boers: f.boers@fz-juelich.de
 - Jürgen Dammers: j.dammers@fz-juelich.de

"""

import os, os.path as op
import numpy as np

import mne
from mne.preprocessing import ICA

from dcnn_utils      import (logger,get_chop_times_indices, auto_label_cardiac,expandvars,
                             auto_label_ocular, get_unique_list, transform_mne_ica2data, transform_ica2data)
from dcnn_utils       import collect_source_info, add_aux_channels
from dcnn_base        import DCNN_PATH,DCNN_MEG, DCNN_ICA, DCNN_SOURCES
from dcnn_performance import PERFORMANCE_PLOT

__version__= "2020.08.11.001"

# -----------------------------------------------------
# compute downsampling frequency and final chop length
# -----------------------------------------------------
def calc_sfreq_ds(times_orig, n_samp_chop, chop_len_init=180.0):

    chop_len_init = np.float64(chop_len_init)

    # compute number of chops with length with
    t_range = times_orig.max() - times_orig.min()
    n_chops, t_rest = np.divmod(t_range, chop_len_init, dtype=np.float64)
    n_chops = int(n_chops)
    if n_chops < 2:
        chop_length = chop_len_init + t_rest
    else:
        # distribute remaining time to all chops
        chop_length = chop_len_init + t_rest // n_chops  # chop_len in s

    # compute downsampling frequency given the chop length and number of samples
    sfreq_ds = np.int64(n_samp_chop) / chop_length

    # test if number of samples per chop is as requested
    n_samp = np.round(chop_length * sfreq_ds).astype(int)
    if n_samp != n_samp_chop:
        raise ValueError("Downsampling frequency does not match the required number of samples per chop!")

    return sfreq_ds, chop_length

# -----------------------------------------------------
# filter and resampling raw data
# -----------------------------------------------------
def meg_filter_resample(raw=None, flow_ica=None, fhigh_ica=None, picks=None, n_jobs=1,
                        res_time=None, chop_len_init=180.0):
    '''
    works in place overwrite raw

    Parameters
    ----------
    raw : TYPE, optional
        DESCRIPTION. The default is None.
    flow_ica : TYPE, optional
        DESCRIPTION. The default is None.
    fhigh_ica : TYPE, optional
        DESCRIPTION. The default is None.
    picks : TYPE, optional
        DESCRIPTION. The default is None.
    n_jobs : TYPE, optional
        DESCRIPTION. The default is 1.
    res_time : TYPE, optional
        DESCRIPTION. The default is None.
    chop_len_init : TYPE, optional
        DESCRIPTION. The default is 60.0.

    Returns
    -------
    raw : TYPE
        DESCRIPTION.
    sfreq_ds : TYPE
        DESCRIPTION.
    chop_length : TYPE
        DESCRIPTION.

    '''

    # 1. apply filter prior to ICA processing
    raw.filter(flow_ica, fhigh_ica, picks=picks, n_jobs=n_jobs,
               filter_length='auto', l_trans_bandwidth='auto', h_trans_bandwidth='auto',
               method='fir', phase='zero', fir_window='hamming')

    # 2. compute downsampling frequency given the requested number of samples per chop
    #    we will have a chop duration of about 60s
    sfreq_ds, chop_length = calc_sfreq_ds(raw.times, res_time, chop_len_init=chop_len_init)

    # 3. apply downsampling
    raw.resample(sfreq_ds, npad='auto', window='boxcar', stim_picks=None,
                 n_jobs=n_jobs, events=None)

    return raw, sfreq_ds, chop_length

# =====================================================
# gDCNN class
# =====================================================
class DCNN(object):
    """
    gDCNN class
    ----------------------------------------------
    Apply ICA and add data to training/test set
     => read MEG data and
       - optional apply noise compensation (CTF annd 4D)
       - optional apply filter and/or notch filter
     => apply ICA
        - filter MEG data
        - donwsampling (model expects a fixed number of  samples)
        - crops data into about 2-3 minutes chops
        - automatic ECG/EOG labeling (CTPS, correlation, SVM)

    """

    def __init__(self, version=None, n_jobs=1, path={}, meg={}, ica={}, sources={}, res={},
                 info=None, verbose=False):
        """
        init via config dict:
                dcnn = gDCNN(**config)

        Parameters
        ----------
        version : string, optional, default: None
        n_jobs  : int,    optional, default: 1.
        path    : dict,   optional, default: {}

        meg     : dict,   optional, default: {}
                  init MEG CLS
        ica     : dict,   optional, default: {}
                  init ICA CLS
        sources : dict,   optional, default: {}
                  init SOURCES CLS
        res     : dict,   optional, default: {}
                  keys: res_time,res_space

        Returns
        -------
        None

        """

        self.version = version
        #self.path    = path
        self.config_info = info

        if res:
            self.model = res
        else:
            self.model = {'res_time': None ,'res_space': None}

        # the following will later be saved in one file for each experiment
        self._PATH    = DCNN_PATH(**path)
        self._MEG     = DCNN_MEG(**meg)  # MEG system and data settings
        self._ICA     = DCNN_ICA(**ica)
        self._SOURCES = DCNN_SOURCES(**sources)
        self.n_jobs   = n_jobs # set n_jobs for MEG  not ICA
        self.verbose  = verbose
        self._PP      = PERFORMANCE_PLOT()

    @property
    def path(self): return self._PATH

    @property
    def meg(self): return self._MEG

    @property
    def ica(self): return self._ICA

    @property
    def sources(self): return self._SOURCES

    @property
    def n_jobs(self): return self._n_jobs

    @n_jobs.setter
    def n_jobs(self ,v):
        # set n_jobs for MEG,ICA too
        if v is None:
            v = 1
        self._n_jobs    = v
        self.meg.n_jobs = v

    @property
    def verbose(self): return self._verbose

    @verbose.setter
    def verbose(self ,v):
        self._verbose     = v
        self.path.verbose = v
        self.meg.verbose  = v
        self.ica.verbose  = v
        self.sources.verbose = v

    @property
    def PerformancePlot( self ): return self._PP

    def _meg_filter_resample(self,raw=None):
        '''
        wrapper for meg_filter_resample

        Returns
        -------
        None.

        '''

        self.ica.chop_n_times = self.model['res_time']
        if not raw:
            raw = self.meg.raw

        # apply filtering and downsampling
        raw ,sfreq_ds ,chop_length = meg_filter_resample(raw=raw ,n_jobs=self.n_jobs,
                                                       picks=self.meg.picks.chan,
                                                       res_time=self.model['res_time'],
                                                       flow_ica=self.ica.flow_ica,
                                                       fhigh_ica=self.ica.fhigh_ica,
                                                       chop_len_init=self.ica.chop_len_init
                                                       )
        self.meg.sfreq_ds     = sfreq_ds
        self.meg.chop_length  = chop_length
        self.ica.chop_length  = chop_length

        return raw

    # -----------------------------------------------------
    # - crop data into chops of 2-3 minute length to increase
    #   data size for training
    # - apply ICA on each chop
    # -----------------------------------------------------
    def _ica_apply_chops(self, raw=None):
        if not raw:
            raw = self.meg.raw

        # get chop times and indices using the fixed number of samples required per chop
        chop_times, chop_indices = get_chop_times_indices(raw.times, chop_nsamp=self.model['res_time'])
        n_chop  = len(chop_times)

        # check if we chop_n_times is larger than origial n_times
        if n_chop == 1:
            nt = chop_indices[0][1]  + 1    #
            if nt < self.ica.chop_n_times:
                self.ica.chop_n_times = nt

        # ---------------------------------------
        # crop data and apply ICA on each chop
        # ---------------------------------------
        n_samples_chop = self.ica.chop_n_times
        sfreq_ds       = self.meg.sfreq_ds
        raw_chop_list  = []
        ica_list       = []

        for ichop in range(n_chop):
            # crop data if n_chop > 1
            if n_chop > 1:
                tmin, tmax = chop_times[ichop]
                raw_chop = raw.copy().crop(tmin=tmin, tmax=tmax)

                # resample last chop to fit the number of samples required (last chop has more samples)
                if ichop + 1 == n_chop:
                    sfreq_last = (n_samples_chop - 1) / raw_chop.times[-1]
                    raw_chop.resample(sfreq_last, npad='auto', window='boxcar', stim_picks=None, events=None)
            else:
                raw_chop = raw.copy()  # here we have a single chop only
                sfreq_last = sfreq_ds

            # collect chops in list
            raw_chop_list.append(raw_chop)

            # apply ICA
            ica = ICA(method=self.ica.ica_method, fit_params=self.ica.fit_params, max_iter=400,
                      n_components=self.ica.n_components, random_state=self.ica.random_state, verbose=None)
            ica.fit(raw_chop, picks=self.meg.picks.meg, decim=None, verbose=True)
            ica_list.append(ica)

        # add chop details to ica dict - set in sub class ica.chop
        self.ica.n_chop          = n_chop
        self.ica.chop.n_samples  = n_samples_chop
        self.ica.chop.sfreq_ds   = sfreq_ds
        self.ica.chop.sfreq_last = sfreq_last   # (self.ica.chop_n_times -1) /raw_chop.times[-1]
        self.ica.chop.picks      = self.meg.picks.meg.copy()
        self.ica.chop.times      = chop_times
        self.ica.chop.indices    = chop_indices
        self.ica.chop.ica        = ica_list

        return raw_chop_list

    # -----------------------------------------------------
    #  label ICs to get cardiac and ocular ICs
    # -----------------------------------------------------
    def _ica_label_chops(self, raw_chop_list):

        n_chops      = self.ica.chop.n_chop
        self.ica.chop.exclude.clear()

        # loop across chops
        logger.info("ICA chops: {}\n list: {}".format(self.ica.chop.n_chop ,self.ica.chop.ica))

        events_ecg     = []
        events_eog_ver = []
        events_eog_hor = []
        for ichop in range(n_chops):
            raw_chop = raw_chop_list[ichop]
            msg = ["ica idx: {}".format(ichop),
                   "ica obj: {}".format(self.ica.chop.ica[ichop])]
            logger.info("\n".join(msg))

            # ica = self.ica['chop']['ica'][ichop]
            ica = self.ica.chop.ica[ichop]

            # get ICs with cardiac activity
            decg = auto_label_cardiac(raw_chop, ica, self.meg.ecg_ch, tmin=-0.4, tmax=0.4,
                                      flow=self.ica.flow_ecg, fhigh=self.ica.fhigh_ecg,
                                      thresh_ctps=self.ica.ecg_thresh_ctps, thresh_corr=self.ica.ecg_thresh_corr)

            # get ICs with ocular activity
            deog = auto_label_ocular(raw_chop, ica, self.meg.eog_ch1, name_eog_hor=self.meg.eog_ch2,
                                     flow=self.ica.flow_eog, fhigh=self.ica.fhigh_eog,
                                     thresh_corr_ver=self.ica.eog_thresh_ver, thresh_corr_hor=self.ica.eog_thresh_hor)

            # ICs to be excluded
            ic_ecg = get_unique_list(decg['ic_ctps'], decg['ic_corr'])
            ic_eog = get_unique_list(deog['ic_ver'], deog['ic_hor'])

            # check for overlapping ICs (identified as ECG & EOG)
            ic_common = list(set.intersection(set(ic_ecg), set(ic_eog)))
            for ic in ic_common:
                # determine which score is larger
                sc_ecg1 = decg['scores_ctps'][ic]  # 0: ECG
                sc_ecg2 = decg['scores_corr'][ic]  # 1: ECG
                sc_eog1 = deog['scores_ver'][ic]   # 2: EOG
                sc_eog2 = deog['scores_hor'][ic]   # 3: EOG
                ix_max = np.array(np.abs([sc_ecg1, sc_ecg2, sc_eog1, sc_eog2])).argmax()
                # group IC based on the largest abs score
                if ix_max < 2:
                    ic_eog.remove(ic)    # is ECG, thus remove IC in the list of EOG
                else:
                    ic_ecg.remove(ic)   # is EOG, thus remove IC in the list of ECG
            ica.exclude = get_unique_list(ic_ecg, ic_eog)

            # collect events from each chop
            events_ecg.append(decg['events_ecg'])
            events_eog_ver.append(deog['events_ver'])
            events_eog_hor.append(deog['events_hor'])

            # ToDo in self.ica.chop.exclude append function
            #  e.g.  self.ica.chop.exclude.update( ecg=decg,eog=deog )
            # -------------------------------
            # store info in ica.chop object
            # -------------------------------
            self.ica.chop.ica[ichop] = ica
            self.ica.chop.exclude.exclude.append( ica.exclude )       # ICs to be excluded

            # ECG ICs
            self.ica.chop.exclude.ecg.append(ic_ecg)
            self.ica.chop.exclude.ecg_ctps.append(decg['ic_ctps'])
            self.ica.chop.exclude.ecg_corr.append(decg['ic_corr'])
            # ECG scores
            self.ica.chop.exclude.ecg_ctps_scores.append(decg['scores_ctps'])
            self.ica.chop.exclude.ecg_corr_scores.append(decg['scores_corr'])

            # EOG ICs
            self.ica.chop.exclude.eog.append(list(ic_eog))
            self.ica.chop.exclude.eog_ver.append(deog['ic_ver'])
            self.ica.chop.exclude.eog_hor.append(deog['ic_hor'])
            # EOG scores
            self.ica.chop.exclude.eog_ver_scores.append(deog['scores_ver'])
            self.ica.chop.exclude.eog_hor_scores.append(deog['scores_hor'])

        # store events in sources class
        self.sources._events_ecg     = np.array(events_ecg)
        self.sources._events_eog_ver = np.array(events_eog_ver)
        self.sources._events_eog_hor = np.array(events_eog_hor)
        # store scores in sources class
        self.sources.score._ecg_ctps = np.array(self.ica.chop.exclude.ecg_ctps_scores)
        self.sources.score._ecg_corr = np.array(self.ica.chop.exclude.ecg_corr_scores)
        self.sources.score._eog_ver  = np.array(self.ica.chop.exclude.eog_ver_scores)
        self.sources.score._eog_hor  = np.array(self.ica.chop.exclude.eog_hor_scores)

    # -----------------------------------------------------
    # get ICA sources (ICA time courses)
    # -----------------------------------------------------
    def _get_source_data(self, raws=None):
            n_comp    = self.ica.n_components
            n_chop    = self.ica.chop.n_chop
            n_samples = self.ica.chop.n_samples
            picks_meg = self.meg.picks.meg
            picks_aux = self.meg.picks.aux
            n_aux = len(picks_aux)

            # init data
            _data_ica = np.zeros([n_chop, n_comp, n_samples], dtype='float64')
            _data_aux = np.zeros([n_chop, n_aux, n_samples], dtype='float64')

            # loop across chops
            for ichop in range(n_chop):
                ica = self.ica.chop.ica[ichop]
                raw = raws[ichop]

                # compute ICA sources
                data = raw._data[picks_meg]
                data, _ = ica._pre_whiten(data, raw.info, picks_meg)
                _data_ica[ichop] = ica._transform(data)

                # extract AUX data
                _data_aux[ichop] = raw._data[picks_aux]

            return _data_ica, _data_aux

    # -----------------------------------------------------
    # label ICA sources
    # -----------------------------------------------------
    def _get_source_labels(self):
            n_comp = self.ica.n_components
            n_chop = self.ica.chop.n_chop
            _labels = []
            label_default = ['other'] * n_comp
            for ichop in range(n_chop):
                labels_chop = label_default.copy()
                for ix in self.ica.chop.exclude.eog[ichop]:
                    labels_chop[ix] = 'EOG'
                for ix in self.ica.chop.exclude.ecg[ichop]:
                    labels_chop[ix] = 'ECG'
                _labels.append(labels_chop)

            return _labels

    # -----------------------------------------------------
    # update excludes based on scores
    # -----------------------------------------------------
    def _update_exclude(self):
        for ichop in range(self.ica.chop.n_chop):
            # get ICA info
            ica = self.ica.chop.ica[ichop].copy()
            label = ['ECG', 'EOG', 'EOG']
            ic_ecg_ctps  = ic_ecg_corr  = []
            ic_eogV = ic_eogH = []

            for ic in ica.exclude:
                # init relative scores
                rel_score_ecg_ctps = rel_score_ecg_corr = 0.0
                rel_score_eogV     = rel_score_eogH     = 0.0

                # compute score relative to threshold
                if self.sources.score.ecg_ctps[ichop][0] >= 0:
                    rel_score_ecg_ctps = self.sources.score.ecg_ctps[ichop][ic] / self.ica.ecg_thresh_ctps
                if self.sources.score.ecg_corr[ichop][0] >= 0:
                    rel_score_ecg_corr = self.sources.score.ecg_corr[ichop][ic] / self.ica.ecg_thresh_corr
                if self.sources.score.eog_ver[ichop][0] >= 0:
                    rel_score_eogV = self.sources.score.eog_ver[ichop][ic] / self.ica.eog_thresh_ver
                if self.sources.score.eog_hor[ichop][0] >= 0:
                    rel_score_eogH = self.sources.score.eog_hor[ichop][ic] / self.ica.eog_thresh_hor

                # get score with largest ratio
                ix = np.array([rel_score_ecg_ctps, rel_score_ecg_ctps, rel_score_eogV, rel_score_eogH]).argmax()
                if ix == 0:                  # ECG CTPS
                    ic_ecg_ctps.append(ic)
                elif ix == 1:                # ECG CORR
                    ic_ecg_corr.append(ic)
                elif ix == 2:                # EOG ver CORR
                    ic_eogV.append(ic)
                elif ix == 3:                # EOG hor CORR
                    ic_eogH.append(ic)
            # update exclude info
            self.ica.chop.exclude.ecg[ichop]      = get_unique_list(ic_ecg_ctps, ic_ecg_corr)
            self.ica.chop.exclude.ecg_ctps[ichop] = get_unique_list(ic_ecg_ctps)
            self.ica.chop.exclude.ecg_corr[ichop] = get_unique_list(ic_ecg_corr)

            self.ica.chop.exclude.eog[ichop]      = get_unique_list(ic_eogV, ic_eogH)
            self.ica.chop.exclude.eog_ver[ichop]  = get_unique_list(ic_eogV)
            self.ica.chop.exclude.eog_hor[ichop]  = get_unique_list(ic_eogH)

    # -----------------------------------------------------
    # plot ICA traces and scores for all chops
    # -----------------------------------------------------
    def plot_ica_traces(self, fname_npz):

        import matplotlib
        import matplotlib.pylab as plt
        from mpl_toolkits.axes_grid1 import make_axes_locatable

        backend_orig = matplotlib.get_backend()  # store original backend
        matplotlib.use('Agg')                    # switch to agg backend to not show the plot

        # settings
        figsize   = (16, 13)
        col_ecg   = 'red'
        col_eog   = 'green'
        col_other = 'lightsteelblue'
        col_kurt  = 'darkgray'
        col_aux   = 'magenta'

        figs      = []
        captions  = []
        name = op.basename(fname_npz[:-4])
        n_chop = self.ica.chop.n_chop

        # compute topo images with 'head'
        self.ica.update_topo_images_head(res=300)

        # loop across chops
        for ichop in range(n_chop):
            aux_data = self.sources.data_aux[ichop]
            if len(self.meg.picks.aux_types) > 0:
                aux_types = self.meg.picks.aux_types
            else:
                aux_types = ['aux'] * aux_data.shape[0]
            n_aux = aux_data.shape[0]
            n_k = 2  # show ICs with large kurtosis
            # calc number of ICs below threshold
            n_max = 12
            n_ecg = len(self.ica.chop.exclude.ecg[ichop])
            n_eog = len(self.ica.chop.exclude.eog[ichop])
            n_bt = n_max - n_k - n_aux - n_ecg - n_eog
            src_data, src_label, src_info, src_ics = collect_source_info(self.sources, self.ica.chop.exclude, ichop,
                                                                         n_below_thresh=n_bt, n_kurtosis=n_k)
            # add aux info
            data = np.concatenate([src_data, aux_data])
            # label = np.concatenate([src_label, aux_types])
            info = np.concatenate([src_info, aux_types])

            n_ics = len(src_ics)
            n_chan, n_times = data.shape
            twin = self.ica.chop.times[ichop]
            times = np.linspace(twin[0], twin[1], n_times)

            topo_img = self.ica.topo.images_head[ichop]   # topo head image

            fig, axlist = plt.subplots(n_chan, 1, figsize=figsize, sharex=True)
            plt.subplots_adjust(left=0.05, right=0.97, bottom=0.1, top=0.9, wspace=0.1, hspace=0.3)
            for ichan, ax in enumerate(axlist):
                # title
                if ichan == 0:
                    title = name + ' chop#%d of %d' % (ichop, n_chop)
                else:
                    title = ''
                # color
                if ichan < (n_chan - n_aux):
                    if src_label[ichan] == 'ECG':
                        col = col_ecg
                    elif src_label[ichan] == 'EOG':
                        col = col_eog
                    elif src_label[ichan] == 'other':
                        if ichan < (n_ecg + n_eog + n_bt):
                            col = col_other
                        else:
                            col = col_kurt
                else:
                    col = col_aux

                # plot topography
                divider = make_axes_locatable(ax)  # add axes for topo and time course
                ax_topo = divider.append_axes('left', size='10%', pad=0.0)
                if ichan < n_ics:
                    topo = topo_img[src_ics[ichan]]
                    ax_topo.imshow(topo, cmap='RdBu_r', interpolation='bilinear')
                    ax_topo.figure.tight_layout()
                ax_topo.axis('off')

                # plot time course
                ax.axes.set_title(title)
                ax.plot(times, data[ichan], label=info[ichan], color=col)
                ax.spines["top"].set_visible(False)
                ax.spines["bottom"].set_visible(False)
                ax.spines["right"].set_visible(False)
                ax.axes.set_xlim(twin)
                ax.legend(loc=1, fontsize='medium', bbox_to_anchor=(1., 1.5))
            plt.tight_layout()
            figs.append(fig)
            # captions.append('%s ... Chop#%d' % (name[:25], ichop))
            captions.append('%s ... Chop#%d' % (name.split(",")[0], ichop))

        # switch to original backend
        matplotlib.use(backend_orig)

        return figs, captions

    def plot_artifact_performance(self):
        """
        plot artifact performance averaged on ECG and EOG onsets
        for reconstructed raw data (meg,ecg,eog,stim) from ICA

        Returns
        -------
        figs,captions
        """
        captions  = []
        self.PerformancePlot.clear_figures() # clear list of figs
        name      = op.basename( self.meg.fname.split(".",-1)[0] )

        msg=["plot artifact rejection performance:",
             "fname: {}".format(os.path.basename( self.meg.fname )),
             "path : {}".format(os.path.dirname(  self.meg.fname )),
             "-"*30,
             "name : {}".format(name)]

        logger.info("\n  -> ".join(msg))
        toffset = 0.0 # time range info

        for ichop in range( self.ica.chop.n_chop ):
            # captions.append('AR %s ... Chop#%d' % (name.split(",")[0], ichop))
            captions.append('%s ... Chop#%d' % (name.split(",")[0], ichop))
            logger.info("plot ARP ICA chop: {} caption: {}".format(ichop,captions[-1]))

            ica = self.ica.chop.ica[ichop].copy()

           # --  get data from sources
            data_ica   = self.sources.data_ica[ichop]
            data_aux   = self.sources.data_aux[ichop]
            aux_labels = self.meg.picks.aux_labels
            aux_types  = self.meg.picks.aux_types

            if data_aux.shape[0] != len(aux_labels):
                logger.exception("ERROR : channel count in aux data [{}] is not equal to counts in aux labels [{}]".
                                 format(data_aux.shape[0], len(aux_labels)))
                return

           # -- reconstruct: raw, raw_clean + add aux data
            raw_chop, raw_chop_clean = transform_ica2data(data_ica, ica)
            raw_chop, raw_chop_clean = add_aux_channels([raw_chop, raw_chop_clean], data_aux, aux_labels, aux_types)

            # -- ck for eog_ch2
            # ToDo implement lists of ECG,EOG artifacts in DCNN cls!!! not fixed channel numbers !!!
            artifacts = [ self.meg.ecg_ch,self.meg.eog_ch1 ]
            events    = [ self.sources.events_ecg[ichop],self.sources.events_eog_ver[ichop] ]

            if self.meg.eog_ch2:
                artifacts.append( self.meg.eog_ch2 )
                events.append( self.sources.events_eog_hor[ichop] )

            # -- mk ICs info
            n_ecg = len(self.ica.chop.exclude.ecg[ichop])
            n_eog = len(self.ica.chop.exclude.eog[ichop])

            trange    = "Time: {:.3f} <> {:.3f}".format(toffset,raw_chop.times[-1]+toffset) # time range info
            suptitle  = trange +"  ECG: cnts: {}  ICs: {}".format( n_ecg,",".join( [str(i) for i in self.ica.chop.exclude.ecg[ichop] ]))
            suptitle += "   "
            suptitle += "EOG: cnts: {}  ICs: {}".format( n_eog,",".join( [str(i) for i in self.ica.chop.exclude.eog[ichop] ]))

            # -- init plot
            self.PerformancePlot._fig            = None
            self.PerformancePlot.idx             = 1
            self.PerformancePlot.n_cols          = len( artifacts )
            # self.PerformancePlot.picks           = self.meg.picks.meg
            self.PerformancePlot.picks           = np.arange(len(self.meg.picks.meg))
            self.PerformancePlot.raw             = raw_chop
            self.PerformancePlot.raw_clean       = raw_chop_clean

           # -- loop for ECG,EOGs
            for idx in range( self.PerformancePlot.n_cols ):
                evt = events[idx]
                if len(evt) > 2: # must have at least 3 elements
                    self.PerformancePlot.plot(ch_name=artifacts[idx], events=evt, event_id=evt[0,2],
                                              fig_nr=ichop+1, suptitle=suptitle)
                self.PerformancePlot.idx += 1

            toffset += raw_chop.times[-1]

        return self.PerformancePlot.figures, captions

    # -----------------------------------------------------
    # get ICA sources & labels
    # -----------------------------------------------------
    def get_sources(self, raws=None):
        self.sources._data_ica, self.sources._data_aux = self._get_source_data(raws=raws)
        self.sources._labels = self._get_source_labels()

    # -----------------------------------------------------
    # get scores
    # -----------------------------------------------------
    def update_scores(self):
        self._update_exclude()
        self.sources._labels  = self._get_source_labels()

    # ---------------------------------------
    #
    # label ICA components (cardiac, ocular)
    #
    # ---------------------------------------
    def label_ica(self ,save=True):

        # make a copy
        raw = self.meg.raw.copy()

        # 1. filtering and downsampling is applied directly on raw
        #    here we also compute the chop size for cropping the data
        raw = self._meg_filter_resample(raw=raw)

        # 2. apply ica on chopped raw data (about 2-3min data chunks)
        raw_chop_list = self._ica_apply_chops(raw=raw)
        del raw   # we continue to work on raw_chop_list

        # 3. apply auto labeling ICA components
        self._ica_label_chops(raw_chop_list)  # ica.excludes are saved in object: self.ica

        # 4. compute ICA sources for each chop and component
        #    returns: IC timeseries (components), aux data and labels
        self.get_sources(raw_chop_list)

        # 5. compute topographies and images for each chop and component
        #    - ICA weights for each sensor and component: np.array([n_chop, n_chan, n_comp])
        #    - topo images for each sensor and component: np.array([n_chop, n_chan, 64, 64])
        self.ica.update_topo_data()
        self.ica.update_topo_images(res=self.model['res_space'])
        # self.ica.update_topo_images_head(res=300)  # for plotting only

        # 6. copy info to sources
        # self.sources.topo._data = self.ica.topo.data
        # self.sources.topo._images = self.ica.topo.images
        # self.sources.topo._images_head = self.ica.topo.images_head

        if save:
            fout_gdcnn = self.save_gdcnn()
        else:
            fout_gdcnn = None

        logger.info('DONE ICA and auto labeling')

        return fout_gdcnn

    # ---------------------------------------
    #
    # apply manual correction to ICA labels
    #
    # ---------------------------------------
    def labels_correct(self, save=True, path_out=None):
        # ica_check_labels(self, save=save)

        for ichop in range(self.ica.chop.n_chop):
            # get ICA info
            ica = self.ica.chop.ica[ichop].copy()
            ic_exclude = ica.exclude  # copy original selected ICs

            data_ica = self.sources.data_ica[ichop]

            # reconstruct MEG signals and create raw object
            data_meg = transform_mne_ica2data(data_ica, ica)
            raw_chop = mne.io.RawArray(data_meg, ica.info)

            # plot sources and components
            # NOTE: click on ICA number (e.g. ICA001) to add or remove the IC to the list of ica.exclude[]
            # ica.plot_components()
            ica.plot_sources(raw_chop, block=True)
            # ica.plot_overlay(raw_chop, exclude=ica.exclude, picks='mag')

            # update ICA object
            if save:
                ica.exclude = list(np.unique(ica.exclude))
                self.ica.chop.ica[ichop] = ica
                self.ica.chop.exclude.exclude[ichop] = ica.exclude  # overwrite excludes

        # 7. save results to disk
        if save:
            self.update_scores()
            fout_gdcnn = self.save_gdcnn(path_out=path_out)
            logger.info('DONE check ICA auto labeling')
            return fout_gdcnn

    # ---------------------------------------
    #
    # load gDCNN info and data
    #
    # ---------------------------------------
    def load_gdcnn(self, fname):
        """

        Parameters
        ----------
        fname : TYPE
            DESCRIPTION.

        Returns
        -------
        npz : TYPE
            DESCRIPTION.

        """

        # with open('data.pickle', 'rb') as f:
        # The protocol version used is detected automatically, so we do not
        # have to specify it.
        # data = pickle.load(f)

        # load gDCNN data
        fname= expandvars(fname)
        logger.info('Start loading gDCNN results from disk ....\n  -> {}'.format(fname))
        npz = np.load(fname, allow_pickle=True)
        logger.info('Done loading gDCNN results from disk\n')

       # if self.verbose:
       #     for k, v in npz.items():
       #         logger.info("gDCNN data: {}\n{}".format(k, v))

        # init clases
        self.path.init(**npz.get('path').item())  # load dict

        self.model = npz.get('model').item()  # load dict

        # data objects cls
        self.meg.init(**npz['meg'].item())  # get dict from np.array
        self.ica.init(**npz['ica'].item())  # get dict from np.array
        self.sources.init(**npz['sources'].item())  # get dict from np.array

        return npz

    # ---------------------------------------
    #
    # save results from auto labeling of ICs in npz format
    #
    # ---------------------------------------
    def save_gdcnn(self, fnout=None, path_out=None):

        logger.info('Start saving results to disk ....')
        from os import makedirs

        if not path_out:
            path_out = self.path.data_train
            if not op.exists(path_out):
                makedirs(path_out)

        from os import makedirs
        # save results to disk
        try:
            if not fnout:
                logger.info("input fnout: ".format(fnout))
                name = op.basename(self.meg.fname).rsplit('.')[0]
            else:
                name = op.basename(fnout).rsplit('.')[0]
            fnout = os.path.join(path_out, name + '-gdcnn.npz')
            logger.info("output file: {}".format(fnout))
        except:
            logger.exception("ERROR\n  -> path_out: {}\n  -> fnout: {}".format(path_out, fnout))
            return False

        self.model['fname_gdcnn'] = fnout

        np.savez(fnout,model=self.model, path=self.path.dump(),
                 meg=self.meg.dump(), ica=self.ica.dump(), sources=self.sources.dump())

        logger.info('Done saving results to disk: {}'.format(fnout))
        return fnout

    def get_info(self):
        # get details
        # --- init dicts
        msg = ["DCNN Info",
               "  -> model:",
               "  -> {}".format(self.model)]
        logger.info("\n".join(msg))

        # -- objs
        self.path.get_info()
        self.meg.get_info()
        self.ica.get_info()
        self.sources.get_info()

redpajama_set_name: RedPajamaGithub


Over the past few centuries, nothing has done more to make lives better than science. And over the past few decades, supercomputing has emerged as a key tool for pushing science forward. It's why our CEO آ— Jen-Hsun Huang آ— will headline our presence at next week's SC16 annual supercomputing show at Salt Lake City, Utah, an event that draws 14,000 researchers, national lab directors and others from around the world. Jen-Hsun will kick off our presence at the show on Monday at 7:30pm MT with an appearance at the NVIDIA Theater we've set up at our booth on the show floor. Over the course of the week, our theater will be the setting for talks from more than a dozen supercomputing experts.


text:
Bryan Beasley is a native Oklahoman who studied at NYU's Tisch School of the Arts earning a Bachelors degree in Film & Television. After graduation he made the move to LA and has had the good fortune to work in Film ("Unconquered" with Val Kilmer), Television (Revolver Magazine's Golden Gods Awards), Webseries ("The SuperMan" & "The Talking Head") and Theater (Off-Broadway's "HurlyBurly" & LA's "Barefoot in the Park").
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text:
MLS Rundown: The Elusive Perfect Ten
Posted By: Craig Thompson February 9, 2018
NO.10 STARTING SPOT UP FOR GRABS IN PHILADELPHIA
When the 2017 season ended, Philadelphia Union had a set of priorities to address and top of that list was signing a new Number 10. Last month at the MLS Superdraft director Earnie Stewart confirmed it remained a position of need, despite bolstering their wingers with a trade for David Accam.
With less than a month to go before the curtain rises on the 2018 MLS season, Union have yet to acquire someone for that spot. Head coach Jim Curtin has played down the signing of a big name and began focusing on creating an intra-squad battle for the Number 10 spot. Flashy Brazilian Ilsinho, 23-year-old Adam Najem and 18-year-old Homegrown talent Anthony Fontana are in the mix.
"They're all at different points in their careers, different points in their growth as players," the Union coach said in a conference call with reporters. "You talk about Ilsinho, who's been a wide player his whole life and maybe was unfairly forced in there last year but who rose to the occasion and produced some really good moments. And Adam Najem has done excellent this preseason. He's gotten the bulk of the reps and has impressed."
A former New York Red Bulls academy player and University of Akron star, Najem is a promising young playmaker. But having only played 153 minutes last season, he's still unproven.
And while Ilsinho did have some flashes of brilliance after moving over from the wing last season, he also had games in which he mostly disappeared. At the end of the season, the 32-year-old Brazilian had his option declined, before being offered a new contract.
"There's a fitness element with anyone who might come in, getting used to the demands of the league, the travel, all those different things," Curtin said. "Obviously the guys here are putting in a ton of work and will naturally be ahead of anyone coming in from the outside. … I would say the later it gets, the more likely it is that we're gonna go with the guys who are here and performing on the field. We still have to choose which one that is. The games coming up will tell us a lot."
Curtin said last week that it "remains to be seen" whether a new No. 10 might arrive this preseason or perhaps in the summer transfer window. But either way, the club is being especially careful with who they might sign.
"Obviously it's difficult throughout the world to sign players," the Union coach said. "A lot has to go right for it to shake out and be a fit for the club. A wide variety of variables go into it. It has to make sense – the timing, the money, the player, their skillset. All those things weigh in. And again, we're happy with the guys we have at camp right now."
Sadly for Union fans, Rundown can envisage Curtin sticking with what he has for the start of the campaign.
CHICAGO WON'T SAY NO TO ONE EITHER
Chicago Fire president and GM Nelson Rodriguez have been speaking to MLSsoccer.com, revealing that the club, who acquired Serbian midfielder Aleksandar Katai on loan from Spanish club Alaves on Tuesday, are still looking for a No. 10 to help fill out an attack left somewhat thin by the draft day trade of winger David Accam to Philadelphia and the torn ACL that Michael de Leeuw suffered last fall.
"We would still like to find a more classic 10, a more classic attacking midfielder who can find pockets in between the lines, who can play and break lines with good final balls and who can also help dictate rhythm," Rodriguez said over the phone. "[We'd like someone who] knows when to slow the game down and when it's available to accelerate it, accelerate it. That is still a skill set that we seek."
The Fire were reportedly after just that type of player earlier this offseason, with numerous reports linking the club to Colombian international Juan Quintero. The president of Independiente Medellin, where Quintero played on loan last year, even went as far to say that the 25-year-old was preparing to move to the US. An MLS move fell through, however, with Argentina's River Plate swooping in to acquire Quintero on loan in late January.
"We don't discuss players who are under contract to another team," Rodriguez said when asked about Quintero, who Chicago were linked to as far back as last summer. "We have made pursuit of a few different players this offseason, made offers for a few different players this offseason. In the end, what I feel good about is the process by which we have evaluated players and I feel good that we've remained disciplined in our approach and have not reacted to anything other than what our valuations are."
That process led them to Katai. The 26-year-old, who a club spokesperson said is on loan until July 31st (at which point Chicago will have an option to buy), primarily lines up as a right winger, but can play on the left and in the middle, as well. Rodriguez said he'll add some diversity to how the Fire can attack in 2018, something both he and head coach Veljko Paunovic cited at the draft as part of their motivation for trading Accam.
"We think he is different than the attacking players we have currently," Rodriguez said. "He has a little bit of a different skill-set, he has an ability to beat defenders off the dribble, he has a very good shot from distance, he serves a good ball right footed or left footed, he's a good set piece taker and we also think he has some versatility in that we think he could play three of our front four spots. I wouldn't say he's a classic No. 10, but I would say he could playmake a bit. And so we like his technical ability, we like his mentality, his desire to get at goal and we look forward to trying to integrate him with our other pieces."
The Fire do have some money to play with after shedding Accam's substantial salary and landing a total of $1.2 million in Targeted and General Allocation Money from the Union for the Ghanaian. Rodriguez said they'll look to use that on another goalkeeper, another centre back and another central midfielder in addition to a potential new No. 10.
He also mentioned that it's possible Juninho could return to Toyota Park in 2018. The former LA Galaxy midfielder was acquired on a season-long loan from Tijuana last winter, but fell behind Bastian Schweinsteiger and Dax McCarty on the depth chart and only started 17 regular season matches. Fire didn't exercise their option to buy him from Xolos after the season, but Rodriguez said he's remained in touch with his representatives throughout the offseason.
It remains to be seen just who they'll target, but Rundown is a lot more confident Katai won't be the last addition Chicago will try to make this winter than in the Union's quest.
"At the draft, I had mentioned that we were still looking to add two or three parts – [Katai] is one," Rodriguez said. "There's still at least two other pieces that we're trying to secure and acquire and then the budget will determine how much more beyond that we'll be able to add."
WILLIS IS BACK IN HOUSTON
Houston Dynamo have re-signed goalkeeper Joe Willis, adding a second goalkeeper to their 2018 squad following the signing of free agent Chris Seitz earlier this winter.
Willis, 29, started eight regular-season games for Houston in 2017, recording clean sheets in two of them. He also started the final three games of La Naranja's unexpected run in the Audi 2017 MLS Cup Playoffs, stepping in for Tyler Deric after the Dynamo Homegrown was suspended by MLS following his arrest on Oct. 31 for a misdemeanour assault charge in connection with an alleged domestic incident.
"We are pleased that Joe Willis will be returning to the Dynamo for the 2018 season. He brings a reliable and steady presence to our group on the field and in the locker room," said Dynamo VP and general manager Matt Jordan in a club statement. "With this signing we are confident that we've strengthened our team in the goalkeeping position to create a highly competitive environment."
A cult hero in some quarters thanks to a social-media meme earlier in his career, Willis has made 37 regular-season appearances since joining the Dynamo from D.C. United in December 2014. The St. Louis native was named the Dynamo Defensive Player of the Year in 2016, posting a career high of 89 saves that season. Willis also recorded his first career assist that year, becoming the second goalkeeper in Dynamo history to do so. With this re-signing, Houston now have 24 players under contract for the 2018 season.
JAMAICAN INTERNATIONAL ARRIVES IN D.C.
D.C. United have acquired Jamaican international defender Oniel Fisher from the Seattle Sounders in exchange for $50,000 in General Allocation Money, the clubs have announced.
Fisher has made 32 regular-season and playoff appearances across three MLS seasons since the Sounders selected him with the 40th overall pick of the 2015 MLS SuperDraft. He featured in four of six matches last summer for the Jamaican national team during their run to the 2017 CONCACAF Gold Cup final, and holds 14 international caps to date.
He joins Reggae Boyz teammate Darren Mattocks in D.C., like Mattocks, Fisher has a US Green Card and thus won't count toward an allotted international roster slot.
"Oniel is a versatile defender who has proven that he can compete to be a starter in this league," said United general manager Dave Kasper in a club statement. "His speed and ability to get forward in the attack, along with his sound defensive ability, provides us with a solid option at either outside back positions. We look forward to integrating Oniel into the team immediately."
Fisher's signing addresses United's need for depth at the fullback slots. Of the players in the Black-and-Red's current squad, only Nick DeLeon and Taylor Kemp are regulars in those spots. Paul Arriola and Chris Durkin could also figure into wide defensive roles, as could Chris Odoi-Atsem, who is on trial after not having his contract renewed following the 2017 season.
REAL SALE LAKE ENGINE ROOM ENHANCED
Real Salt Lake added a potentially key piece to their engine room this week, announcing the signing of Croatian central midfielder Damir Kreilach via the use of Targeted Allocation Money.
Kreilach, 28, joins RSL from Union Berlin of Germany's 2. Bundesliga, where he scored 33 goals in 147 matches over the past five seasons and became a fan favourite.
"We're really excited about bringing Damir in. He's got a ton of experience and challenges our depth immediately," said RSL general manager Craig Waibel in a club statement. "He brings talent. He brings leadership – he was the co-captain at Union Berlin. He's a good person. He's going to be a good fit in our locker room."
According to Union's website, the German club released Kreilach from his contract, which ran until summer 2019, at his request as he pursued a "dream" move to MLS. He made his final match appearance for Union on Monday night, playing 71 minutes in a 1-1 draw against Arminia Bielefeld.
"I've played for two clubs in my 10 professional years so far, [Croatian side HNK] Rijeka and Union. Now I have the chance to make a dream come true and to go to America with my family," said Kreilach, a former Croatian youth international. "That is why I am very grateful to Union for allowing me to take advantage of this opportunity. I know that's not a matter of course."
He will occupy an international slot on Salt Lake's roster and will join the club in preseason, pending receipt of his International Transfer Certificate and visa.
Both New York City FC and Sporting Kansas City have released new 2018 away kits. New York City's new away kit is a predominantly grey design inspired by the "grit and attitude" of the concrete jungle that the club calls home and uses the tagline 'Everywhere We Go' while Kansas offer an evolution to the designs of previous years with a black shirt featuring metallic silver lettering… the MLS transfer window is now officially open with it remaining as such until 11:59 pm ET on May 1st.


Accentuate your wrist wearing this gold cuff bracelet set. This bracelet comes in a set of 5 with different motifs at the center of the half-opened bangle that is adjustable. This set will perfectly complement your daily wear outfits.


text:
MARRIAGE NEWS WATCH
Federal Courts Enter Frustrating Standoff Over Freedom To Marry
By Matty B September 22, 2014 at 10:09am · 19 comments
We've been waiting years for the U.S. Supreme Court to make a decision about marriage, and now an off-the-cuff comment from Ruth Bader Ginsburg has just provided a hint that the Supreme Court might've been waiting for us this whole time. Somehow, marriage equality has turned into a lame chicken-and-egg joke.
Here's the problem: there are a bunch of marriage cases that are ready for the Supreme Court to take. But the Supreme Court might not want to take it (RBG hinted last week) because all of those cases agree that marriage bans are unconstitutional, and the court would prefer to wait until lower courts disagree with each other.
So far, only one federal judge has upheld a marriage ban since the Windsor decision, and he's at the bottom of the ladder: a District Court judge. Before that case gets to the U.S. Supreme Court, it has to pass through an appellate court, which could take years.
So if Ginburg's comment is any indication, the Supreme Court might not take a case for years. Or maybe it will take a case next week! There is literally no way to know what the hell they're going to do, other than wear robes and look solemn.
Making things even more complicated: some courts (but not all courts) are afraid of stepping on the Supreme Court's toes, so they'd decided to freeze their marriage lawsuits until the Supreme Court rules. But the Supreme Court might not want to make a decision until those cases advance further. And that means that the whole legal system's in a traffic jam, waiting for someone to get out of the way and figure out where they're going.
And that, apparently, is now important issues are settled here in the land of the free.
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nospecial
If the court denies cert. to a case they've issued a stay in, then the stay will be lifted by the court. By the same measure, if a federal court has stayed its own decision and the case is denied cert. by the Supreme Court, either party is free to ask the federal court to lift its stay, which it obviously would be inclined to do, if it hasn't already done it on its own.
MarionPaige
so the advice to gay people is to put their lives on hold for another 10 – 15 years until gay marriage is legal in all 50 states? History will show that I was there (on queerlaw) in 1996 suggesting gay family units form llcs. At that time, the mantra was Gay Marriage in Hawaii and the gay marriage fuckwards were yelling "wait till full marriage". As I've said, only a fucking idiot would have dragged their families and partners through the ups, downs and sideways of this fucking gay marriage fiasco (when they could have had A LEGAL PARTNERSHIP via llc law in 1996). The fact that no one is taking advantage of gay marriage where it is legal (relatively speaking) proves that.
MacAdvisor
We can easily have national marriage equality without every obtaining a Supreme Court ruling. We've had pro-marriage equality rulings from the 1st, 2nd, 3rd, 4th, 7th, 9th and 10th Circuits. The 9th is about to rule again and I think we can count on a pro-marriage equality ruling from them. The 6th is also about to weigh in and the guesses are it will not be pro-marriage equality, but let's assume for the moment that it is. That will give use rulings in 1st, 2nd, 3rd, 4th, 6th, 7th, 9th and 10th. All that is left is the 5th and the 11th Circuits. There are already cases head to the 5th circuit (which handles Texas, Louisiana, and Mississippi), so we will hear from them this year. The same is true for the 11th (which handles Florida, Georgia, and Alabama). Once those to Circuits rule and assuming they rule pro-marriage equality, the entire country will have marriage equality. All of the Circuit Courts of Appeal will have ruled on marriage equality not later than the end of next year and perhaps even by the end of this year, assuming the Supremes don't take up the question. At that point, we have national marriage equality, in all fifty states, and marriage equality is the law of the land without the SCOTUS ever having issued a opinion on point.
If the 5th, 6th, or 11th rule against marriage equality, we will have a circuit split and the Supremes will all-but be forced to settle the dispute. I don't see how we leave 2015 without national marriage equality, but it might, at worst, drag into 2016, but that's it. Two years, people, that is the worst realistic case.
Kamuriie
@MarionPaige: You're a moron.
September 22, 2014 at 1:09pm
re MacAdvisor
In 1996, the mantra was "Full Faith And Credit", that all 49 states would be FORCED to recoginize gay marriage once Hawaii legalized it.
I'm sure the Queerlaw archives for gay marriage are still on the net somewhere. You can see just how long this PROPAGANDA has been going on. You can also see my posts about llcs to the list, in 1996,
AzLights
Why should I be forced into some "partnership" when I married legally in Canada? I want the dignity and ALL the rights conferred by legal marriage. YOU take a "partnership" if you think it's so wonderful.
Canada is selling dignity now? Is by the bottle or the can?
d3clark48
@MarionPaige:
55% of all marriage licenses recently issued by New Mexico were for same-sex couples.
Wikipedia says: Several hundreds to thousands of marriage licenses were issued to same-sex couples in Utah, Michigan, Arkansas, Wisconsin and Indiana between the time their bans were struck down by federal or state courts and when those rulings were stayed." That doesn't include the other states that now have SSM like: CT, MA, PA, NY, etc.
California had enough SSMs to stop its declining marriage rate and actually increase it.
So I think your claim that relatively few SSM couples are getting married is unfounded.
@MarionPaige: While the Full Faith and Credit Clause was the scare attic of the right, the Clause has always had the Public Policy exception, that is the limitations to the extent to which a state may be required by the full faith and credit clause to enforce even the judgment of another state in contravention of its own statutes or policy. See Wisconsin v. Pelican Insurance Co., </i?127 U.S. 265. Typically, a state is free to not recognize the marriages performed legally in another state is such a marriage is contrary to the laws of that state. For example, if one can marry at the age of 12 in the State of Disgrace, but the age of consent for marriage in State of Prudence is 16, the State of Prudence can refuse to recognize the marriage of two 13-year olds who married in the State of Disgrace and moved to the State of Prudence. Given the decision in Bowers v. Hardwick, 478 U.S. 186 (1986), I think the Public Policy Exception would have prevented states from recognizing gay marriages that state didn't want to. That would have been less clear after Romer v. Evans, 517 U.S. 620 (1996), but we didn't have a definitive ruling until US v. Windsor, 570 U.S. ___ (2013).
pjm1
So, the bottom line is that the Supreme Court will NOT take
up the marriage issue until there is a split in the Federal Circuit Courts.
Currently, there is no split in the Circuits so it should be no surprise when the
Supremes do not take any of the cases.
Judge Posner (a conservative intellectual heavy-weight, and he really is)
of the 7th Circuit ruled earlier this month that the Wisconsin and Indiana bans on same sex
marriage were unconstitutional. He made some powerful arguments that will appeal (pun intended) to
Justice Kennedy and Chief Roberts. On this issue, Judges Scalia and Thomas are pretty much a lost
cause.
1EqualityUSA
May they're waiting for Ruth Bader Ginsberg to not be able to participate.
passingthru
@d3clark48: It's not at all about someone who "dragged their families and partners through ups and downs". Rather, it's about keeping the movement going forward. Families and partners realize victory with each positive step in the journey. It's about moving the needle which is an amazing thing. Let's all get there! MarionPaige doesn't get it at all and never will. Life is much better than he/she can possibly realize or enjoy. Too bad but there isn't any value in arguing or trying to explain.
Saint Law
@MarionPaige: "You can also see my posts llcs to the list, in 1996."
Yes the internetz are fairly humming with all the traffic to those even as we speak.
Visceral is the only way I can describe the disappointment I feel when I see MarionPaige's moniker come up. I won't even read her stuff anymore. The last thing I ever read was some tirade with variations of the F-word strewn throughout. It was then that I realized she's a loon. Now, I can't stand the name Marion nor Paige. Together, it's as ugly as the words spit out in haste. (Troll.) Maggie Gallagher has competition. I picture a rock basement, Silence of the Lambs-like, as "Mother" clomps around incessantly in sensible nun-shoes upstairs while MP types her vile spew.
NoCagada
Maybe MARIONPAIGE is really fatass Maggie Gallagher trying to eat her way out of her closet
if you search (even in the "fucking" gay marriage obsessed New York Times and Washington Post) for "estate planning" or "financial planning" for married heterosexual couples,you will find copious mentions of the terms LLC and Family Limited Partnerships.
Heterosexual couples (who obviously could always marry) were using LLCs along with getting married to the point where the IRS was actively trying to limit their use. AND YET, there was (and is) essentially no mention of the terms LLC or Family LP from the gay marriage fuckwads. AND WHY?
Because the gay marriage fuckwads wanted / want the focus only on gay marriage, even though gay couples could have created family llcs and family limited partnerships as far back as 1996. In other words, the focus of gay marriage hustlers like Rob Reiner and AFER is on THEIR AGENDA, not helping gay people.
But hey, we're talking about adults. If you are an adult and you think Rob Reiner created AFER to help gay people … you go with that.
MarionPaige settles for second class citizenship and becomes foul mouthed when others don't drink her LLC koolade. One trick pony law clerk just won't shut the Hell up. Maggie Gallagher must pay this wipe to try to sway the gay.
Elloreigh
@MacAdvisor: "I don't see how we leave 2015 without national marriage equality, but it might, at worst, drag into 2016, but that's it. Two years, people, that is the worst realistic case."
I respectfully disagree. I remember what a shock and setback the Bowers ruling was. At that time, around half the states had already repealed their sodomy statutes, and several more repealed them following the Bowers ruling. But it was another 17 years before the remaining 13 states had their sodomy statutes overturned by the Lawrence decision, reversing Bowers.
Now take a sober look at where we stand legally concerning same-sex marriage. As of this writing only 19 states recognize same-sex marriage. Worse, most that ban that recognition do so not only by statute, but also through voter-enacted amendments to state constitutions.
Legally speaking, it can be argued that we were in a much better position at the time of Bowers concerning sodomy laws, than we are right now with same-sex marriage equality. Despite the positive elements of the Windsor ruling striking a portion of DOMA, I do not think the Court will be in any hurry to get out in front of the states on this issue.
It is a mistake in my view for the bulk of the effort to obtain marriage equality to be focused on the courts. We need to be doing everything we can to repeal those state amendments. But I also recognize that doing so is a daunting, if not impossible task at this point in time.
I am proud to go down in history as the lone and loudest voice in the gay community to alert gay people and their families to the fact that they could create family llcs (just like married straights) IN 1996. And, I am also confident that gay famillies that created llcs in 1996 are better off today than the ones stupid enough to buy into the "wait for full gay marriage koolaide".
game over?
Now Trump might be losing the lease on his golf course in West Palm Beach
Melania won't meet Dr. Jill Biden for tea, won't even talk to her on the phone
girl bye!
As Melania looks back on the legacy of #BeBest, the rest of Twitter tells her to #BeGone
Twitter rejoices over photos of moving boxes outside the White House


Notes on ancient Mayan sites like Chichen Itza, the Pyramid of the Sun, the Caracol — all show evidence that the Mayans had a superior grasp of mathematics and the length of the solar year. Their buidlings were used as observatories, as deduced from their alignment to key sunrises of the Solstices and Equinoxes.
How did Venus lose its water and become the inferno it is today? Venus's surface water evaporated and entered the atmosphere. "Water vapor is a powerful greenhouse gas and it caused the planet to heat-up even more. This is turn caused more water to evaporate and led to a powerful positive feedback response known as the runaway greenhouse effect," says Grinspoon.
A new planet has been discovered in the constellation Leo. While most planets discovered recently are gas giants, this one is more likely to be a rocky type similar to Earth.
The main news this week is that Venus enters Taurus Wednesday and quickly forms a trine to Pluto in Capricorn and Saturn in Virgo. Earth sign types will be favored during this brief alignment Thursday (and while it is waxing), so roll out your website, blog about your book, and generally promote anything that you yourself have produced.
What Kind of Pope Will Benedict Be?
The most striking thing about the chart is the Jupiter-Mercury conjunction in late Pisces, plus Uranus in the first degree of Aries. Jupiter is the natural ruler of Sag and ninth-house matters, which include publishing, higher education, religion and law. With Sag in the tenth house of career, it is interesting that Ratzinger has pursued a career that has spanned all four areas.
There are only two places I would go to get a decent astrological report. One is from the A.R.E. (Association for Research and Enlightenment) in Virginia. The other place is Asto Communications dot com.


As the hydraulic components of CNC press brakes play a specific role in the hydraulic system, so the performance of hydraulic components is bound to affect the performance of the entire CNC bending machine.
Therefore, before the system is assembled, each hydraulic component must be rigorously inspected by its technical performance indicators to determine whether its performance meets the requirements and is cleaned before entering the assembly stage.
After being assembled and testing, the hydraulic system must be commissioned.
The purpose of the commissioning is to enable the system to meet the performance requirements in the normal operating condition to ensure that the hydraulic equipment can work normally when it enters the actual working condition.
Test and adjust the force of various components, speed, the end and start point of stroke, the order of the action, the time of action and the total time of the entire cycle in the automatic working process, make it reaches the predetermined value and requirements.
Check the adjustable features of pressure, speed and stroke and observe the changes in hydraulic oil temperature. Correct and take measures to solve those do not meet the requirements.
The commissioning of CNC press brake hydraulic system is very important, it must be prepared well in advance.
Prepare a variety of instruments, tools well in advance.


NEW YORK—Dear social media pioneers: You have set a high bar for social media marketing, but now brands are catching up.
Huge companies like Dell Inc., International Business Machines Corp. (IBM) and PepsiCo Inc. have started to discover your once seemingly mysterious strategies and insights, and they are teaching them to thousands of their employees.
As it turns out, these socially engaged employees aren't just good — they rock. They are 27-percent more likely to feel optimistic about their company's future and 20-percent more likely to stay at their current company, according to a report from LinkedIn and Altimeter Group. In addition, socially engaged companies are 57-percent more likely to get increased sales leads and 58-percent more likely to attract talent.
Social pioneers, you have done well setting the stage, and companies are finally realizing that anyone can be a social rock star, too. So they're raising social armies—aka social businesses where the ethic of social media creates happier employees who discover their own voice, drive increased engagement and co-own the voice of the brand. They are the social marketers of the future.
With time and determination, many early social adopters became respected thought leaders. So how do you inspire an entire workforce to become an enterprise of social leaders and influencers? You need a framework.
1. Develop social media policies that encourage engagement. Pick a social business champion who will earn the support of leaders from legal, compliance and HR. This group of experts will develop social media policies, which serve as guardrails for their co-workers, answering questions such as: How should employees use social? What should they talk about? Who will create original content or identify content to share? How do we address FTC guidelines or other laws? This same group will participate in selecting internal and external social media platforms that fit the company's vision and engagement needs.
2. Establish training for all levels of social acumen. Determine how you will approach social media training, develop a program and invite employees to participate. If time is available to scale slowly, start with a pilot group that will inform the evolution of your training strategy as employees learn the company's social media policies and get acquainted with your social technologies. Demonstrate how the platforms should be used. For instance, on external social networks, what do employees do with content? Provide practical, hands-on training.
3. Enable and equip employees as advocates. Build a steady flow of content and let your employees begin to share over Facebook, Twitter, LinkedIn, Pinterest or whichever social networks your team wants to target. Just as you did before, observe what works and what does not work. You will certainly find ways to improve your advocate strategy and training program.
By reducing the complexity of social business into this framework, you'll free up space to figure out how you can act on these concepts.
To get the most out of this framework, look at examples from companies that have done it well. There are infinite ways to go through the steps I described, but some techniques work better than others.
PepsiCo, for example, provides a useful example of tackling a social business framework. According to a 2010 survey, 65 percent of PepsiCo employees said friends and family asked questions about the company or its products, and more than half said they would like PepsiCo to provide them with content to share across social media channels.
So PepsiCo's communications team built this wish into a social program, then educated employees on what they could or could not share on social media. They realized that about 85 percent of PEPline, PepsiCo's internal email newsletter, was relevant for a public audience. So they added social icons to this daily email and employees started sharing the articles.
Advocating for your brand must always remain a choice, because the benefits of social business depend on it. Employees with choice will know what's going on in the company because they will review blogs, infographics, videos and other content before they post. They will only share when they are proud of what's happening in the company.
You cannot control a force that, by nature, democratizes communication. You can, however, end the monopoly over social media that you may believe social media pioneers have. It's going to happen anyway, with or without your consent. So let your employees do the talking.
Lee Diaz, previously senior manager of emerging communications at AT&T, is director of strategy and solutions at SocialChorus. He wrote this for Advertising Age, a New York City-based sister publication of Tire Business.


text:
Ancylosis biflexella is a species of snout moth in the genus Ancylosis. It was described by Julius Lederer in 1855, and is known from Niger, Tunisia, Algeria, Israel, Lebanon, Iran, Cyprus and the Canary Islands.

References

Moths described in 1855
biflexella
Moths of Africa
Moths of Asia


text:
HomeMusicClassic HitsElton John to be honored as one of Variety's Hitmakers of the Year
Elton John to be honored as one of Variety's Hitmakers of the Year
Elton John is one of several artists set to be honored at Variety's sixth annual Hitmakers celebration, which honors artists who have the 25 most-consumed songs of the past year, according to Luminate.
Elton is being honored alongside Dua Lipa as Hitmakers of the Year thanks to the success of their collaboration "Cold Heart-PNAU Remix," which combines Elton's hits "Rocketman," "Sacrifice" and more. It peaked at seven on the Billboard chart and became Elton's 28th top-10 hit. The honor also recognizes Elton for his incredible six-decade career, as well as his "mentorship of young artists."
Also being recognized at the event is Kate Bush's '80s single "Running Up That Hill" for Sync of the Year, due to its resurgence on the chart after its use in season 4 of Netflix's Stranger Things. It turned out to be the 12th most consumed song of 2022.
This year's honorees, which include Imagine Dragons, Selena Gomez and Lizzo, will be celebrated on December 3 with an invitation-only brunch.
It's official: Elton John's Farewell Yellow Brick Road tour is the highest-grossing tour of all time
Elton John fans upset at last-minute New Zealand show cancelation due to flooding
Duran Duran's John Taylor says Andy Taylor's Hall of Fame appearance was always "touch and go"
Bernie Taupin releasing memoir, 'Scattershot: Life, Music, Elton & Me,' next fall
Asia's John Wetton subject of upcoming book


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Calcasieu Parish SNAP Benefits (Louisiana)
Calcasieu Parish Food Stamp Offices provide nutrition benefits through the federal Supplemental Nutrition Assistance Program (SNAP). SNAP, also known as food stamps, provides nutrition assistance for income-eligible households in Calcasieu Parish, Louisiana. Local Food Stamp Offices process applications for Calcasieu Parish SNAP benefits, determine whether individuals or families meet the eligibility requirements, and provide nutritional education resources. Food Stamp Offices also help administer monthly food benefits, distribute food assistance, and accept applications for Calcasieu Parish SNAP benefits. Food Stamp Offices provide information about their services or making an appointment online.
Lake Charles Calcasieu Economic Stability Food Stamp Office Lake Charles LA 2133 Oak Park Boulevard 70601 888-524-3578
Calcasieu Parish Child, Youth, and Family Services Offices offer programs and services to assist children and families, such as emergency assistance, income support programs, and protective services. Many offer children's welfare services, including nutritional assistance in Calcasieu Parish, Louisiana. Food assistance can include monthly food benefits, access to food banks, and other nutrition assistance resources. Child, Youth, and Family Services Offices provide information on applying for SNAP benefits, meeting income eligibility requirements, and receiving food assistance. Calcasieu Parish Child, Youth, and Family Services Offices list their resources and services on their website.
Louisiana Correctional & Industrial School Children & Family Services Department DeQuincy LA 4336 Edgerly Road 70633 337-786-2234
SNAP Benefits near Calcasieu Parish
Beauregard Parish
Allen Parish
Vernon Parish


I have the Doctor's ok to wear deet from my knees down and I bet I could spray clothing or a blanket and put it over me... but as I am BRAND new to turkey hunting, I need some help with how prepared I should be.
I tuck my pants into my Woody Max. Nothing ever gets in.
You obviously won't be belly crawling through the grass to see over a rise this year but for future reference, snug sleeves tucked into gloves helps.
I could be in a bubble suit and they would still get to me. Will they be out this early?
Let me just say that deer ticks are nothing to take lightly. I have been struggling with lyme disease and the medical problems brought on by such for many years now. For example I am only 50 and I have to have my hips replaced because of arthritis that has been brought on by lyme disease so with that being said PROTECT YOURSELF with whatever works and constantly check yourself whenever you go outdoors.
We use a product called "REPEL" which has Deet but what we like about it is once you spray your clothes and boots down with it, it will stay in your clothes up to 10 washings so you don't have to keep re-applying. They advise you to NOT spray it on your body.
We use it and then tuck in all shirt tails and pant legs. We stay chigger and deer tick free during our Spring and Fall hunts. Chiggers are our kryptonite, not so much the deer ticks.
We get Repel from our local Walmart but you can get it on-line too.


text:
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	<titles>
		<title type="short" as="introduced">Federal and Military Retiree Health Care Equity Act</title>
		<title type="official" as="introduced">To amend the Internal Revenue Code of 1986 to allow Federal civilian and military retirees to pay health insurance premiums on a pretax basis and to allow a deduction for TRICARE supplemental premiums.</title>
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	</cosponsors>
	<actions>
		<action date="1235538000" datetime="2009-02-25"><text>Referred to the Committee on Ways and Means, and in addition to the Committees on Oversight and Government Reform, and Armed Services, for a period to be subsequently determined by the Speaker, in each case for consideration of such provisions as fall within the jurisdiction of the committee concerned.</text></action>
		<action date="1235538000" datetime="2009-02-25"><text>Referred to House Ways and Means</text></action>
		<action date="1235538000" datetime="2009-02-25"><text>Referred to House Oversight and Government Reform</text></action>
		<action date="1235538000" datetime="2009-02-25"><text>Referred to House Armed Services</text></action>
	</actions>
	<committees>
		<committee name="House Ways and Means" subcommittee="" activity="Referral, In Committee" />
		<committee name="House Oversight and Government Reform" subcommittee="" activity="Referral, In Committee" />
		<committee name="House Armed Services" subcommittee="" activity="Referral, In Committee" />
	</committees>
	<relatedbills>
		<bill relation="unknown" session="111" type="s" number="491" />
	</relatedbills>
	<subjects>

	</subjects>
	<amendments>

	</amendments>
	<summary>

	</summary>
</bill>