text:
The Record-Journal
The Record-Journal Homepage
Dante Carrafa
Sacred Heart High SchoolWilby High School
Dellavecchia Funeral Home
Dante Carrafa, Sr., of Southington, CT, passed away peacefully at UConn John Dempsey Hospital in Farmington, CT, on Saturday, September 11, 2021, with his devoted family by his side. Dante was the beloved husband of Monica (Raudis) Carrafa and a much-loved son, father, grandfather, great-grandfather, brother, cousin, and uncle in a close-knit Italian-American family.
Never was there a man so interested - or interesting. Born in Waterbury, CT, on June 15, 1933, Dante approached life with gusto. He was the son of the late Michael and Rachel (Ciavarella) Carrafa, and was raised in Waterbury, along with his 11 siblings, in a house on Citizens Avenue, where large family get-togethers were an everyday occurrence and there was always room for one more at the table. He graduated from Mary Abbott Grammar School and Wilby High School, and attended the University of Connecticut. Over the course of his life, Dante was a successful businessman, entrepreneur, and public servant. As a young man, he was a photographer and sportswriter for the Naugatuck Daily News and the Waterbury Republican-American. He began his career in manufacturing as a tool designer and went on to start and manage successful companies that served the aerospace industry, including LCM Tool Company, National Tool Company, Cambridge Specialty Company, and Gemini Tool. He is a past president of the Smaller Manufacturers Association of CT, and owned and operated Dan's Top Dog restaurant in Southington. Dante served in the U.S. Army and U.S. Army Reserve for nearly 20 years, attaining the rank of captain. In Waterbury, the city he loved and served in many capacities for many years, he was Zoning Commissioner. He twice ran for State Senate. Dante was a people person who could talk to anyone. He loved making introductions and connecting people. He was known for his kindness, generosity, and sense of humor, as well as more than a few signature catchphrases, like "What luck!" He was a New York Yankees fan; lifelong member of the Waterbury Elks club; former member of Wethersfield Country Club and Indian Hill Country Club; lover of and participant in the arts and community theater, a passion he shared with and developed in his children; and benefactor of the Franciscan Sisters of the Eucharist, whose annual sports banquet he always looked forward to attending, and Sacred Heart High School, whose Carrafa-Tuttle scholarship fund was named in his honor. He was also a lifelong learner, who would discover something he wanted to do or know, attack it with passion, and master it in no time, adding pilot, wine connoisseur, golfer, military history buff, concert promoter, and more to his list of achievements. Besides his wife, Monica, Dante leaves his beloved children and their spouses: Cynthia and Anthony Petrello of Houston, TX; Dante, Jr. and Ann Marie Carrafa of New Hartford, CT; Valerie and Ben Barker of West Simsbury, CT; and Kimberly and Mike Russ of Kerrville, TX. He leaves 10 grandchildren: Carena; Dante III and his wife, Lisa; Derek and his fiancée, Kathryn; Devin; Leah and her fiancé, Rory; Alana; Evan; Peyton and his wife, Sarah; Isabelle; and Truly; as well as two great-grandchildren: Dante IV and Santino. He leaves his brother and sister-in-law Joseph and Wendy Carrafa; sisters Mary Imbimbo and Anita Disisto; sister-in-law Rosemarie Carrafa; and former wife, Charlotte Carrafa. He is also survived by several brothers-in-law, other sisters-in-law, nieces, nephews, a large, loving extended family, and many dear lifelong friends who will miss trips to Saratoga, concerts in the park, happy hours on the deck, and other fun times with Dante.
He was predeceased by his brothers Matthew, John, Michael, Eugene, Victor, and Alfred Carrafa, and his sisters Lucia and Elaine Carrafa.
A Mass of Christian Burial for Dante will be held on Friday, September 17, 2021 at 11:00 AM at St. Dominic Church, 1050 Flanders Rd., Southington, CT 06489. Everyone is asked to meet at church. Military honors will be held after the Mass at the church. Burial will be private. Calling hours for Dante will be held on Thursday, September 16, 2021 from 4:00 PM to 7:00 PM at the DellaVecchia Funeral Home, 211 N. Main St., Southington, CT 06489.
Memorial contributions in his memory may be made to The Franciscan Sisters of the Eucharist, 405 Allen Avenue, Meriden, CT 06451.
Published by The Record-Journal from Sep. 15 to Sep. 16, 2021.
Calling hours
211 North Main Street, Southington, CT
St. Dominic Church
1050 Flanders Rd, Southington, CT
Sponsored by Dellavecchia Funeral Home.
How do you know Dante Carrafa? (Optional)
Be the first to post a memory or condolences.


text:
SYNONYM

#### According to
The Catalogue of Life, 3rd January 2011

#### Published in
Mycoth. fenn. (Helsinki) 2: 122 (1873)

#### Original name
Plagiostoma petiolicola Fuckel, 1870

### Remarks
null

redpajama_set_name: RedPajamaGithub


text:
Q: CD Drive not recognized - 18.04 Problem: CD-Drive not working / mounting. When i insert a CD, file manager does nothing. The eject command in the terminal does not work. I do not have much knowledge about setting up hardware in Ubuntu. Until now, everything worked fine from the beginning. It is not the first time i am working on this issue. I was never able to solve it and i guess, i messed up something while creating a mounting point?
System: Lenovo T430s, Intel i5, Ubuntu 18.04
    andi@andi-ThinkPad-T430s:~$ sudo lshw -C disk
[sudo] password for andi:
  *-disk
       description: ATA Disk
       product: Samsung SSD 840
       physical id: 0.0.0
       bus info: scsi@0:0.0.0
       logical name: /dev/sda
       version: 6B0Q
       serial: S14GNEACA39356R
       size: 232GiB (250GB)
       capabilities: partitioned partitioned:dos
       configuration: ansiversion=5 logicalsectorsize=512 sectorsize=512 signature=ad175e01
  *-cdrom
       description: DVD-RAM writer
       product: DVD-RAM UJ8B2
       vendor: MATSHITA
       physical id: 0.0.0
       bus info: scsi@1:0.0.0
       logical name: /dev/cdrom
       logical name: /dev/cdrw
       logical name: /dev/dvd
       logical name: /dev/dvdrw
       logical name: /dev/sr0
       version: SB01
       capabilities: removable audio cd-r cd-rw dvd dvd-r dvd-ram
       configuration: ansiversion=5 status=ready
     *-medium
          physical id: 0
          logical name: /dev/cdrom

Tried to mount it:
andi@andi-ThinkPad-T430s:~$ sudo mkdir /media/cdrom
andi@andi-ThinkPad-T430s:~$ sudo mount /dev/sr0 /media/cdrom/
mount: /media/cdrom: no medium found on /dev/sr0.
andi@andi-ThinkPad-T430s:~$ sudo mount /dev/cdrom /media/cdrom/
mount: /media/cdrom: can't read superblock on /dev/sr0.
andi@andi-ThinkPad-T430s:~$ sudo mount /dev/dvd /media/cdrom/
mount: /media/cdrom: no medium found on /dev/sr0.
andi@andi-ThinkPad-T430s:~$ sudo mount /dev/sr0/ /media/cdrom/
mount: /media/cdrom: special device /dev/sr0/ does not exist (a path prefix is not a directory).
andi@andi-ThinkPad-T430s:~$ sudo mount /dev/sr0/ /media/cdrom
mount: /media/cdrom: special device /dev/sr0/ does not exist (a path prefix is not a directory).
andi@andi-ThinkPad-T430s:~$ sudo mount /dev/sr0 /media/cdrom

Wodim output:
andi@andi-ThinkPad-T430s:/dev$ wodim --devices
wodim: No such file or directory.
Cannot open SCSI driver!
For possible targets try 'wodim --devices' or 'wodim -scanbus'.
For possible transport specifiers try 'wodim dev=help'.
For IDE/ATAPI devices configuration, see the file README.ATAPI.setup from
the wodim documentation.

andi@andi-ThinkPad-T430s:/dev$ wodim -checkdrive
Device was not specified. Trying to find an appropriate drive...
Detected CD-R drive: /dev/cdrw
Using /dev/cdrom of unknown capabilities
Device type    : Removable CD-ROM
Version        : 5
Response Format: 2
Capabilities   :
Vendor_info    : 'MATSHITA'
Identification : 'DVD-RAM UJ8B2   '
Revision       : 'SB01'
Device seems to be: Generic mmc2 DVD-R/DVD-RW.
wodim: Cannot load media with this drive!
wodim: Try to load media by hand.
Using generic SCSI-3/mmc   CD-R/CD-RW driver (mmc_cdr).
Driver flags   : MMC-3 SWABAUDIO BURNFREE
Supported modes: TAO PACKET SAO RAW/R16 RAW/R96P RAW/R96R

/dev directory:
andi@andi-ThinkPad-T430s:/media$ cd /dev/
andi@andi-ThinkPad-T430s:/dev$ ls
autofs           loop1               rfkill    tty37      ttyS20
block            loop10              rtc       tty38      ttyS21
bsg              loop11              rtc0      tty39      ttyS22
btrfs-control    loop12              sda       tty4       ttyS23
bus              loop13              sda1      tty40      ttyS24
cdrom            loop14              sg0       tty41      ttyS25
cdrw             loop15              sg1       tty42      ttyS26
char             loop16              shm       tty43      ttyS27
console          loop17              snapshot  tty44      ttyS28
core             loop18              snd       tty45      ttyS29
cpu              loop19              sr0       tty46      ttyS3
cpu_dma_latency  loop2               stderr    tty47      ttyS30
cuse             loop20              stdin     tty48      ttyS31
disk             loop21              stdout    tty49      ttyS4
dm-0             loop22              tpm0      tty5       ttyS5
dm-1             loop23              tty       tty50      ttyS6
dri              loop24              tty0      tty51      ttyS7
drm_dp_aux0      loop25              tty1      tty52      ttyS8
drm_dp_aux1      loop26              tty10     tty53      ttyS9
drm_dp_aux2      loop27              tty11     tty54      ubuntu-vg
dvd              loop3               tty12     tty55      uhid
dvdrw            loop4               tty13     tty56      uinput
ecryptfs         loop5               tty14     tty57      urandom
fb0              loop6               tty15     tty58      userio
fd               loop7               tty16     tty59      v4l
full             loop8               tty17     tty6       vcs
fuse             loop9               tty18     tty60      vcs1
hpet             loop-control        tty19     tty61      vcs2
hugepages        mapper              tty2      tty62      vcs3
hwrng            mcelog              tty20     tty63      vcs4
i2c-0            media0              tty21     tty7       vcs5
i2c-1            mei0                tty22     tty8       vcs6
i2c-2            mem                 tty23     tty9       vcsa
i2c-3            memory_bandwidth    tty24     ttyprintk  vcsa1
i2c-4            mqueue              tty25     ttyS0      vcsa2
i2c-5            net                 tty26     ttyS1      vcsa3
i2c-6            network_latency     tty27     ttyS10     vcsa4
i2c-7            network_throughput  tty28     ttyS11     vcsa5
i2c-8            null                tty29     ttyS12     vcsa6
i2c-9            nvram               tty3      ttyS13     vfio
initctl          port                tty30     ttyS14     vga_arbiter
input            ppp                 tty31     ttyS15     vhci
kmsg             psaux               tty32     ttyS16     vhost-net
kvm              ptmx                tty33     ttyS17     vhost-vsock
lightnvm         ptp0                tty34     ttyS18     video0
log              pts                 tty35     ttyS19     zero
loop0            random              tty36     ttyS2

Further output:
andi@andi-ThinkPad-T430s:/dev$ lsmod | grep sr_mod
andi@andi-ThinkPad-T430s:/dev$ lsmod | grep sg
andi@andi-ThinkPad-T430s:/dev$ ls -l /dev/sr0
brw-rw----+ 1 root cdrom 11, 0 Dez 30 14:21 /dev/sr0

Appreciate your help and wish you all a happy new year :)

A: I have this problem too. Audio CDs are not recognised on my 18.04 setup. Even when I open VLC media player and manually direct it to play, I just get errors.

redpajama_set_name: RedPajamaStackExchange


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text:
Дми́трий Ви́кторович Ковале́нин (род. 2 июня 1966 года, Южно-Сахалинск) — российский писатель, востоковед, переводчик.

Биография
Отец — филолог-славист, мать — преподаватель-историк. Дмитрий Коваленин вырос на Сахалине, учился в художественной и музыкальной школах. В 1985—1988 годах работал в «Интуристе» города Хабаровска, координируя и сопровождая туристические группы из Японии, Австралии и США в путешествиях по СССР. В 1988 году окончил восточный факультет Дальневосточного государственного университета по специальности «востоковед-филолог; переводчик с японского языка». В 1988—1989 годах стажировался в Университете Сока (Токио).

С 1991 года, уехав в Японию по частному приглашению, Коваленин работал судовым агентом в японском порту города Ниигата.

В 2000 году вернулся в Москву, где занимался свободными переводами и журналистикой. Коваленин — один из создателей сайта «Виртуальные суси» (1998), получившего в 2001 году «Интел-Интернет премию» в номинации «Персональные страницы».

Творчество
Известность Дмитрий Коваленин получил как переводчик на русский язык книг Харуки Мураками, первая из которых, «Охота на овец», была опубликована в 1998 году. Общий тираж всех переведенных Ковалениным и изданных разными издательствами романов Мураками превысил миллион экземпляров.

Переводчик
Среди его работ — переводы таких авторов, как Харуки Мураками («Дэнс, Дэнс, Дэнс», «Страна Чудес без тормозов и Конец Света», «Послемрак», «1Q84», «Бесцветный Цкуру Тадзаки и годы его странствий»), Фудзивара Иори («Тьма на ладони»), Патрик Несс («Жена журавля»), Макото Синкай (роман и манга «Твоё имя»), Кэйго Хигасино («Вещие сны», «Детектив Галилей»), Ёко Огава («Полиция памяти»), Юкико Мотоя («Брак с другими видами»);

в поэзии — Тавара Мати («Именины Салата»), Такамура Котаро («Стихи о Тиэко»), Роберт Стивенсон, Том Уэйтс, Роджер Уотерс, Леонард Коэн и др.

Также занимается переводом фильмов для дубляжа — «Твоё имя», «Ветер крепчает».

Лауреат литературной премии «Странник» (за перевод романа «Дэнс, Дэнс, Дэнс»).

Писатель
Автор книги «Суси-Нуар. Занимательное муракамиЕдение» — исследования жизни и творчества Харуки Мураками. Для его написания Коваленин провел год в Токийском университете в качестве стажёра-исследователя по гранту Министерства образования Японии.

Автор книги «Коро-коро» — сборника малой прозы, включающей повесть «Сила трупа», рассказы и эссе о современной Японии.

Журналист
С 1998 года вместе с Вадимом Смоленским поддерживает сетевой проект «Виртуальные суси» о современной японской культуре.

В 2002 году Дмитрий Коваленин опубликовал первое интервью с Харуки Мураками, адресованное русскоязычной аудитории.

В 2003 году Ковалениным опубликован репортаж о совместном путешествии с Харуки Мураками по югу острова Сахалин.

Частичная библиография
 Суси-Нуар. Занимательное муракамиЕдение

Примечания

Ссылки

 Дмитрий Коваленин о Восходящем солнце  — канал Дмитрия Коваленина на YouTube
 Журнал Forbes — интервью с Дмитрием Ковалениным о романе Ёко Огава «Полиция памяти»
 Журнал Esquire о Ёко Огаве и её романе «Полиция памяти» в переводе Д. Коваленина
 Журнал Forbes о романе Юкико Мотоя «Брак с другими видами» в переводе Д. Коваленина

Переводчики России
Переводчики с английского языка
Переводчики с японского языка
Переводчики прозы и драматургии на русский язык
Лауреаты премии «Странник»

redpajama_set_name: RedPajamaWikipedia


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text:
package server

import java.util.concurrent.ConcurrentHashMap

import akka.actor.ActorRef
import server.messages.internal.ClusterListenerMessages.{SettingsUpdatedMessage, DatabaseRemovedMessage, DatabaseAddedMessage}

/**
  * Contains the list of reference of all StoreManager actors
  */
object StaticSettings   {
  var mapManagerRefs = new ConcurrentHashMap[String, ActorRef]()
  var maxRowNumber = 2
  var ninjaNumber = 1
  var warehousemanNumber = 1
  var dataPath = "C:\\data\\actorbase"

  /**
    * Method used to add a new database to the map.
    * It also communicate the insertion to the SettingsManager.
    *
    * @param name name of the new database.
    * @param actor reference to the MapManager actor that manages the database to replicate the change to other nodes.
    */
  def subscribe(name: String, actor: ActorRef): Unit ={
    // put the database inside the map
    mapManagerRefs.put(name,actor)
    // send a message to the SettingsManager.
    Server.settingsManager ! DatabaseAddedMessage(name,actor)
  }

  /**
    * Method used to remove a database from the map.
    * It also communicate the deletion to the SettingsManager to replicate the change to other nodes.
    *
    * @param name name of the deleted database.
    */
  def unSubscribe(name: String): Unit ={
    // remove the database from the map
    mapManagerRefs.remove(name)
    // send a message to the SettingsManager.
    Server.settingsManager ! DatabaseRemovedMessage(name)
  }

  /**
    * Method used to modify the settings.
    * It also communicate the changes to the SettingsManager to replicate the changes to other nodes.
    *
    * @param mRN new max number of rows.
    * @param nN new number of ninjas.
    * @param wN new number of warehoseman.
    */
  def changeSettings(mRN: Integer = maxRowNumber, nN: Integer = ninjaNumber, wN: Integer = warehousemanNumber): Unit ={
    // update settings
    maxRowNumber = mRN
    ninjaNumber = nN
    warehousemanNumber = wN
    // send a message to the SettingsManager.
    Server.settingsManager ! SettingsUpdatedMessage(mRN,nN,wN)
  }
}


text:
Q: Estimate of a product of functions where $1/p + 1/q >1$ I have the following problem. I need to estimate the following quantity:
$$|\nabla|^{-1}A u \nabla u \label{1}\tag{$*$}$$
I know that $A\in L^6(B_R)$, $u \in L^{14/5}\cap L^2(B_R)$ and $\nabla u \in L^2(B_R)$ where $B_R$ is a ball of radius $R$ in $\mathbb{R}^3$.(1) Clearly, $\frac{1}{6}+\frac{5}{14} +\frac{1}{2} >1$, so this is not in any $L^p(B_R)$ with $p\geq 1$. However I don't have to obtain an estimate in $L^p$. I would also be satisfied with an estimate in $H^{s}(B_R)$ or $W^{s,p}(B_R)$ with $s<0$ i.e. a negative order Sobolev space.(2) So I thought about estimating, for $-1<s<-1/14$,
$$
\begin{split}
\|Au\nabla u\|_{H^s} &\leq \|Au\|_{H^{-1/14}}^{\theta} \|\nabla u\|_{H^{-1}}^{1-\theta} \\
    &\leq \|Au\|_{L^{21/11}}^{\theta} \|u\|_{L^2}^{1-\theta} \leq \|A\|_{L^6}^{\theta} \|u\|_{L^{14/5}}^{\theta}   \|u\|_{L^2}^{1-\theta} .
\end{split}$$
where in the second step I would use Sobolev's inequality with $\frac{1}{2}+\frac{1}{14}\cdot\frac{1}{3} = \frac{11}{21}$ and in the third step Hölder with $\frac{1}{6}+ \frac{5}{14} = \frac{11}{21}$. But I was wondering whether the first step is even remotely allowed. I know we can't really take products of distributions but the functions I'm dealing with here really are functions in $L^p$ spaces? I know this is all pretty hand-wavey and this is why I'm asking to clarify this or for you to suggest another path one might take.
(1)All these bounds follow from stuff like energy conservation etc. but I don't want to bother you with details.
(2) I need this for the Aubin-Lions lemma to work. Equation \eqref{1} corresponds to a term in the formula for $\partial_t A$. In fact the space I need to continuously embed is $W^{1,7/6}(B_R)$.


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text:
Orne – rzeka w Normandii w północno-zachodniej Francji. Jej źródło znajduje się w departamencie Orne, w miejscowości Aunou-sur-Orne na wschód od Sées. Rzeka uchodzi do kanału La Manche w Ouistreham.

Zobacz też
 Rzeki Europy

Rzeki w departamencie Calvados
Rzeki w departamencie Orne


text:
\section{Introduction}
Coronavirus disease 2019 (Covid-19) has emerged very fast as an emergent health risk disease affecting the whole world.
It has been observed that this infection spreads through the surfaces which might be infected from the infected person.
The spread of Covid-19 is categorized into different stages. The stage1 and stage2 refer to the small scale spread, whereas stage3 and beyond refer to the large scale spread due to chain reaction.
Covid-19 pandemic is being witnessed as the toughest time of the century during April-May 2021 due to its $2^{nd}$ wave which has already entered into stage3/stage4 (i.e., community spread) of Covid-19 infection spread.
Thus, the pandemic has led to a huge burden on the healthcare systems across the world.
Testing for Covid-19 is the most important part of the process and must be scaled as much as possible. CXR based testing can one of the fastest way using existing infrastructure and can be scaled very quickly and cost effectively.
The radiograph image of the lungs can be captured using different imaging tools such as CT-Scan and X-Ray. Getting the CT-Scan is again a costly and time-consuming process. Moreover, only major hospitals have CT scanners. However, capturing an X-Ray is a very affordable as well as an efficient process.
The covid-19 disease is caused by severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) and the infected patients show distinct visual features in the Chest X-Ray (CXR) images. Hence, artificial intelligence based automated techniques can be utilized to detect the infection in CXR images. Such testing methods can be fast, scalable, economical, and affordable.

Researchers have tried to explore the artificial intelligence based deep learning techniques for Covid-19 detection, such as COVID-Net \cite{Wang2020}, CovidAID \cite{covidaid}, COVID-CAPS \cite{afshar2020covidcaps}, CovXNet \cite{covxnet}, DarkCovidNet \cite{darkcovidnet} and Convolutional Neural Network (CNN) Ensemble \cite{cnnensemble}. The lack of sufficient data to train and test the models is the main problem in the development of the deep learning based models for Covid-19 detection in CXR images. Hence, it is an urgent requirement to develop a deep learning model that would learn distinctive features from the limited data. In order to learn the discriminative and localized features, we propose an attention guided contrastive CNN (AC-CovidNet) for Covid-19 recognition from CXR images. Following are the commitments of this work:
\begin{itemize}
    \item We propose a novel AC-CovidNet deep learning framework for Covid-19 recognition in CXR images.
    \item The use of the attention module enforces the learning of localized visual features corresponding to Covid-19 symptoms.
    \item The contrastive loss increases the discriminative ability and robustness of the model by learning the similarity between Covid-19 infected samples and dissimilarity between Covid-19 positive and negative samples.

    \item The impact of the proposed method is analyzed for different amount of training data w.r.t. the recent state-of-the-art models.
\end{itemize}

The remaining paper is organized as follows: Section \ref{relatedworks} summarizes the related works; Section \ref{proposedmethod} illustrates the proposed AC-CovidNet model; Section \ref{experimentalsetup} details the experimental settings; Section \ref{experimentalresults} presents the results and analysis; and finally Section \ref{conclusion} summarizes the findings with concluding remarks.

\section{Related Works}
\label{relatedworks}
It has been observed in the primary research conducted by Wang and Wong (2020) \cite{Wang2020} that chest radiograph images can be used for the Covid-19 detection. It opened up the new urgent and demanding area of the possible usage of Artificial Intelligence for early, efficient and large-scale detection of viruses among people.
Ng et al. released the imaging profile of the Covid-19 infection with radiologic findings \cite{ng2020imaging}.
Li et al. discovered the spectrum of CT findings and temporal progression of Covid-19 disease which reveals that this problem can be solved using imaging AI based tools \cite{li2020coronavirus}.
Bai et al. performed a performance study of radiologists which can differentiate the Covid-19 from viral pneumonia on chest CT \cite{bai2020performance}.

Deep learning is also utilized for Covid-19 detection from Chest X-Ray (CXR) images \cite{narin2020automatic}.
In one of the first attempts, CXR radiograph images are used for Covid-19 detection using a Deep Learning based convolutional neural network (CNN) model COVID-Net \cite{Wang2020}.
A projection expansion projection extension module is used heavily in COVID-Net which is experimented on various configurations of the model. Authors used a human-machine collaborative design strategy to create COVID-Net architecture where human driven prototyping and machine based exploration is combined. A COVIDx dataset is also accumulated from various sources and being updated with new data. The dataset and models are publically released for further research\footnote{https://github.com/lindawangg/COVID-Net/}. Using COVID-Net model, 96\% sensitivity is observed in \cite{Wang2020} on a test set of 100 CXR images.
A CovidAID model is proposed in \cite{covidaid} which is a pretrained CheXNet \cite{rajpurkar2017chexnet} - a 121 layer DenseNet \cite{huang2018densely} followed by a fully connected layer. Using the CovidAID model, 100\% sensitivity is observed on a test set having 30 Covid-19 images.
A capsule networks based deep learning model (COVID-CAPS) is investigated in \cite{afshar2020covidcaps}. Authors in \cite{afshar2020covidcaps} aim to prevent the loss of spatial information which is observed in CNN based methods. Using COVID-CAPS model, a sensitivity of 90\% is reported on 100 test CXR images.
CovXNet model \cite{covxnet} is proposed to use transferable multi-receptive feature optimisation. Basically, 4 different configurations of a network are utilized in CovXNet for training and prediction. Using CovXNet model, 91\% sensitivity is reported on 100 test CXR images.
The DarkNet architecture based DarkCovidNet model is introduced in \cite{darkcovidnet} with You Only Look Once (YOLO) real time object detection system for Covid-19 detection. Using the DarkCovidNet model, a classification accuracy of 98.08\% for binary classes and 87.02\% for multi-class cases are observed.
CNN ensemble of DenseNet201, Resnet50-v2 and Inception-v3 is utilized for Covid-19 recognition in \cite{cnnensemble}. Samples from only 2 classes (i.e., covid and non-covid) are used to train the CNN ensemble model. Using CNN ensemble model, a classification accuracy of 91.62\% is reported. Researchers from \cite{he2020sample} tried to develop an open source framework of algorithms to detect covid19 using CT scan images. Also, researchers at \cite{javaheri2020covidctnet} developed Covid-CT using selftrans approach. We have tested these algorithms on our CXR dataset configurations.

From the above presented works, it is convincing that AI powered deep learning methods can play a vital role for the Covid-19 screening. The CT scans and CXR radiographs are used majorly for the imaging based techniques. Less attention has been given to CXR images so far due to the not so great generalization performance caused by the limited availability of data \cite{ahmed2021discovery}, \cite{degrave2021ai}.
Given the need to conduct the mass screening at affordable cost, the further fast research over CXR images of lungs is very much needed using the limited data. Thus, in this paper, we utilize the capability of attention mechanism and contrastive learning to tackle the learning with limited data for Covid-19 recognition from CXR images.

\section{Proposed AC-CovidNet CNN Model}
\label{proposedmethod}
In this section, first we provide a brief of deep learning, attention mechanism and contrastive learning. Then we present the proposed AC-CovidNet architecture.

\subsection{Background}
Deep learning has shown a great impact from last decade to solve many challenging problems \cite{lecun2015deep}. Deep learning models consist of the deep neural networks which learn the important features from the data automatically. The training of the deep models is generally performed using stochastic gradient descent optimization \cite{adam}, \cite{diffgrad}. Convolutional neural network (CNN) based models have been used to deal with the image data, such as image classification \cite{alexnet}, face recognition \cite{hmloss}, image retrieval \cite{dubey2020decade}, hyperspectral image analysis \cite{hybridsn}, and biomedical image analysis \cite{lbpdad}.

Attention mechanism in deep learning facilitates to learn the localized features which is more important in the context of the problem of Covid-19 recognition from CXR images \cite{bahdanau2015neural}. It is also discovered that the attention based model can outperform the plain neural network models \cite{vaswani2017attention}. The attention mechanism has been also utilized for different applications such as facial micro-expression recognition \cite{gajjala2020meranet}, breast tumor segmentation \cite{vakanski2020attention}, and face recognition \cite{rao2017attention}. Thus, motivated from the success of attention mechanisms, we utilize it in the proposed model for Covid-19 recognition.

Contrastive learning is the recent trend to learn the similarity and dissimilarity between the similar and dissimilar samples in the abstract feature space for visual representations \cite{chen2020simple}, \cite{supcon}. Generally, contrastive learning is dependent upon the feature similarity between positive pairs and negative pairs \cite{tian2020makes}. The contrastive learning has shown very promising performance for different problems, such as face generation \cite{deng2020disentangled}, image-to-image translation \cite{park2020contrastive}, medical visual representations \cite{zhang2020contrastive}, and video representation \cite{qian2020spatiotemporal}. Thus, motivated from the discriminative and robust feature representation by contrastive learning, we utilize it in the proposed method.

\begin{figure}[!t]
    \centering
    \includegraphics[width=8cm]{img.png}
    \includegraphics[trim={0 40 0 40},clip, width=4.1cm]{PEPX.png}
    \caption{Left: Architecture of the proposed AC-CovidNet. Right: Projection Expansion Projection Extension (PEPX) Module. Here, DWConv representsthe depth wise convolution operation.}
    \label{fig:proposed_model}
\end{figure}

\subsection{Proposed Model}
In this paper, we propose an attention guided contrastive CNN for Covid-19 recognition, named as AC-CovidNet. The architecture of the proposed AC-CovidNet model is illustrated in Fig. \ref{fig:proposed_model}. The proposed model is based on the popular COVID-Net model \cite{Wang2020}. It heavily uses light weight residual projection expansion projection extension (PEPX) mechanism. The PEPX component is shown in Fig. \ref{fig:proposed_model} (right side). This architecture also uses selective long range connectivity in model which improves the representational capacity. It also facilitates the training of the model easier. However, the extensive use of these long range connections may bring a lot of redundant low level features. In order to resolve this issue, the proposed model uses an attention mechanism. Attention helps the model to prioritize the regions of important w.r.t. the problem being solved. Attention is also useful to suppress the activations from the redundant features from the initial layers and helps to focus on the important features that are required to solve the given problem. We use the attention gates in the proposed architecture as suggested in \cite{oktay2018attention}, at various layers in the COVID-Net architecture where many long range connections are used. This improves the sensitivity as the model attends better to the important visual features of infected regions in CXR images due to Covid-19.
As the difference between Covid-19 and Pneumonia features is very subtle, we propose to use the supervised contrastive loss. The contrastive loss facilitates the network to increase the distance between the learnt representation of the classes as much as possible.

\subsubsection{Architecture}
The proposed AC-CovidNet architecture is an extension of COVID-Net by utilizing the attention gates where multiple long range connections converge. The details of the architecture of the proposed model is illustrated Fig. \ref{fig:proposed_model}.
We use PEPX layers and attention gates heavily as a part of our architecture. We also use the contrastive loss function while training.
The model is first trained using supervised contrastive learning before final fine tuning using supervised learning.

\subsubsection{PEPX Layer}
The architecture of a Projection-Expansion-Projection-Extension (PEPX) is shown in Fig. \ref{fig:proposed_model} (right side). The idea of this module is to project features into a lower dimension using the first two conv1x1 layers, then expand those features using a depthwise convolution layer (DWConv3x3) and project into lower dimension again using two conv1x1 layers. Thus, the PEPX layer leads to the efficient model by reducing the number of parameters and operations.

\subsubsection{Attention Gate}
We use attention gates in the proposed AC-CovidNet model at various layers as depicted in Fig. \ref{fig:proposed_model}. The block diagram of the attention module is shown in Fig. \ref{proposedmethod}. Features from multiple layers are passed through conv1x1 and are added together. Then, the aggregated features are passed through Relu activation function followed by conv1x1 and then sigmoid activation function. The feature map output of the sigmoid layer is then passed through a resampler. The output of the resampler is added to the features from the nearest input layer to the attention module in order to produce the output of the attention gate.

\begin{figure*}[!t]
\centering
\includegraphics[trim={0 58 0 48},clip,width=12cm]{attention-gate.png}
   \caption{The block diagram of an attention gate.}
\label{fig:short}
\end{figure*}

\subsubsection{Network Details}
The following are the main components of the proposed AC-CovidNet model. a) Encoder network, $E(.)$: It is the AC-CovidNet model as discussed above after removing the last three layers which form the classifier network. The encoder network maps the input image into a vector of size 1024. b) Projection network, $P(.)$: This network projects the output of the encoder network into a vector of size 128. This is a multilayer perceptron with input size of 1024, one hidden layer of length 512, and an output vector of size 128. This network is used while training the encoder and later discarded. c) Classifier network, $C(.)$: This is the last three layers of AC-CovidNet that take a 1024 length output of the encoder as the input and produces an output of size $c = 3$ (corresponding to the classes, Normal, Pneumonia, and Covid-19).

First we train the encoder network $E(.)$ with supervised contrastive loss (SupConLoss) using the projection network $P(.)$. Then we discard the projection network and add the classifier network $C(.)$ to the encoder network. Then we freeze the weights of the encoder model and train the classifier with categorical cross entropy loss. The training of the encoder of the proposed model is summarized in Algorithm \ref{algo_encoder}.

\begin{algorithm}[!t]
\label{algo_encoder}
\SetAlgoLined
$E$: Encoder Network, $P$: Projection Network\\
$C$: Classifier Network\\
$SupCon$: Supervised Contrastive Loss\\
$CrossEntropy$: Cross Entropy Loss\\
\While{$epochs--$}{
\tcp{Stage 1}
\For{batch $X$ in $Data$}{
    Initialize $Z$ as null\;
    \For{$x_i$ in $X$}{
        $h_i = E(x_i)$\;
        $z_i = P(h_i)$\;
        $Z.append(z_i)$\;
    }
    $\mathcal{L}_{SC} = SupCon(Z_i)$\;
    Update $E$ and $P$ to minimise $\mathcal{L}_{SC}$\;
}
}
Discard $P(.)$ and freeze weights of $E(.)$\;
Final model, $M(\boldsymbol{x}) = C(E(\boldsymbol{x}))$\;
\While{$epochs--$}{
\tcp{Stage 2}
\For{batch $X$ in $Data$}{
$\hat{Y} = M(X)$\;
$\mathcal{L}_{CE} = CrossEntropy(Y, \hat{Y})$\;
Update $M$ to minimise $\mathcal{L}_{CE}$\;
}
}
 \caption{Training AC-CovidNet}
\end{algorithm}

\subsection{Objective Function}
We use the supervised contrastive learning method \cite{supcon} to train the encoder network for feature extraction. We train the classifier network using the cross entropy loss function after freezing the encoder network.

\subsubsection{Supervised Contrastive loss}
Contrastive loss is most commonly used in unsupervised and self-supervised learning. In order to adapt this method to supervised learning and take advantage of the labels available, the supervised contrastive learning has been investigated in \cite{supcon}. This loss is used to train the encoder network of the proposed AC-CovidNet.

Consider $\boldsymbol{z}_{\ell}=\operatorname{P}\left(\operatorname{E}\left({\boldsymbol{x}}_{\ell}\right)\right)$ where ${\boldsymbol{x}}$ is the input and $A(i)$ is a set of all indices ($I$) except $i$. Then, the supervised contrastive loss is given as,
\[\mathcal{L}_{SC}=\sum_{i \in I} \frac{-1}{|P(i)|} \sum_{p \in P(i)} \log \frac{\exp \left(\boldsymbol{z}_{i} \cdot \boldsymbol{z}_{p} / \tau\right)}{\sum_{a \in A(i)} \exp \left(\boldsymbol{z}_{i} \cdot \boldsymbol{z}_{a} / \tau\right)}\]
where, $\tau \in \mathcal{R}^{+}$ is scalar temperature parameter, $P(i) \equiv\left\{p \in A(i): \tilde{\boldsymbol{y}}_{p}=\tilde{\boldsymbol{y}}_{i}\right\}$ is the set of indices of all the positive samples other than $i$, and $|P(i)|$ is its cardinality. Note that $\tilde{\boldsymbol{y}}$ represents the class label.

\subsubsection{Cross Entropy Loss}
Cross entropy loss is used to train the classifier which takes input from the feature extractor. It produces the output probability corresponding to three class from the softmax activation function. The cross entropy loss is given as,
\[\mathcal{L}_{CE} = -\frac{1}{N}\sum_{i=1}^{\mathrm{N}}\sum_{j=1}^{\mathrm{3}} y^j_i \cdot \mathrm{log}\; {\hat{y}}^j_i\]
where ${\hat{y}}^j_i$ and $y^j_i$ are the output probability and ground truth value, respectively, for $j^{th}$ class corresponding to $i^{th}$ sample and $N$ represents the number of samples in a batch.

\begin{table*}
\caption{Datasets configurations used for training and testing w.r.t. the number of samples in Covid-19, Pneumonia and Normal categories.}
\centering
\resizebox{12cm}{!}{
\begin{tabular}{|c|c|c|c|c|c|c|c|}
\hline
\multirow{2}{*}{S. No} & \multirow{2}{*}{Configuration} & \multicolumn{2}{c|}{Covid-19} & \multicolumn{2}{c|}{Pneumonia} & \multicolumn{2}{c|}{Normal} \\ \cline{3-8}
 &  & \#Training Images & \#Test Images & \#Training Images & \#Test Images & \#Training Images & \#Test Images \\ \hline
I & COVIDx-v1 & 517 & 100 & 7966 & 100 & 5475 & 100 \\ \hline
II & COVIDx-v2 & 467 & 150 & 7916 & 150 & 5425 & 150 \\ \hline
III & COVIDx-v3 & 417 & 200 & 7866 & 200 & 5375 & 200 \\ \hline
\end{tabular}}
\label{table:dataset}
\end{table*}

\begin{table*}[!t]
\caption{The results comparison in terms of the sensitivity.}
\resizebox{12cm}{!}{
\begin{tabular}{|l|l|l|l|l|l|l|l|l|l|}
\hline
\multicolumn{1}{|c|}{Model} & \multicolumn{3}{c|}{COVIDx-v1} & \multicolumn{3}{c|}{COVIDx-v2} & \multicolumn{3}{c|}{COVIDx-v3} \\ \hline
\multicolumn{1}{|c|}{} & \multicolumn{1}{c|}{Covid} & \multicolumn{1}{c|}{Pneumonia} & \multicolumn{1}{c|}{Normal} & \multicolumn{1}{c|}{Covid} & \multicolumn{1}{c|}{Pneumonia} & \multicolumn{1}{c|}{Normal} & \multicolumn{1}{c|}{Covid} & \multicolumn{1}{c|}{Pneumonia} & \multicolumn{1}{c|}{Normal} \\ \hline
COVID-Net \cite{Wang2020} & 96 & 89 & 95 & 94.66 & 87.33 & 95.33 & 94 & 88.5 & 94 \\ \hline
CovidAID \cite{covidaid} & 93 & 95 & 73 & 91 & 92.66 & 70.66 & 88 & 92.5 & 74 \\ \hline
Ensemble Learning CNNs \cite{cnnensemble} & 89 & 91 & 87 & 87.33 & 92 & 86 & 83 & 91 & 89 \\ \hline
DarkCovidNet \cite{alexnet} & 86 & 88 & 92 & 84.66 & 84 & 89.33 & 84.5 & 89.5 & 90.5 \\ \hline
Covid-Caps \cite{afshar2020covidcaps} & 90 & 87 & 77 & 88 & 86 & 74 & 86.5 & 84.5 & 76 \\ \hline
CovidCTNet \cite{javaheri2020covidctnet} & 83 & 76 & 89 & 79 & 74.33 & 87.66 & 79 & 74.5 & 88 \\ \hline
Covid-CT \cite{he2020sample} & 87 & 82 & 86 & 85.66 & 79.33 & 85 & 85 & 77 & 85.5 \\ \hline

CovXnet \cite{covxnet} & 91 & 71 & 86 & 89.33 & 69.33 & 86.66 & 88 & 70 & 84 \\ \hline
CovidNet + attention & 95 & 86 & 95 & 95.33 & 82.66 & 95.33 & 94 & 87 & 94.5 \\ \hline
CovidNet + contrastive loss & 96 & 89 & 95 & 96 & 87.33 & 94 & 95 & 90 & 95 \\ \hline
\textbf{AC-CovidNet} & \textbf{96} & \textbf{88} & \textbf{95} & \textbf{96.66} & \textbf{87.33} & \textbf{95.33} & \textbf{96.5} & \textbf{87.5} & \textbf{95} \\ \hline
\end{tabular}}
\label{table:results}
\end{table*}

\section{Experimental Setup}
\label{experimentalsetup}

\subsection{Dataset Used}
We use COVIDx dataset \cite{Wang2020} in this work to experiment with the proposed AC-CovidNet model. It is the largest open-source dataset for Covid-19 Chest X-Ray (CXR) images currently available. This dataset is a combination of several other open datasets, including Covid-19 Image Data Collection, Covid-19 Chest X-ray Dataset Initiative, ActualMed Covid-19 Chest X-ray Dataset Initiative, RSNA Pneumonia Detection Challenge dataset, and Covid-19 radiography database.
This dataset contains three classes of CXR images, i.e., Covid-19, Pneumonia and Normal. It has a total of 14,258 images from 14,042 patients. It has 7,966 Normal images, 5,475 Pneumonia images and 517 Covid-19 images in the training set and 100 images from each category in the test set. In our experiments we create three different sets of data by varying the distributions of samples in training and test sets. We name the original COVIDx dataset as COVIDx-v1 by following the above said distribution. COVIDx-v2 is the COVIDx dataset with 150 test images from each category and 7,916 Normal images, 5,425 Pneumonia images and 467 Covid-19 images in the training set. Similarly, COVIDx-v3 has 200 test images from each category and 7,866 Normal images, 5,375 Pneumonia images and 417 Covid-19 images in the training set. These configurations are summarized in Table \ref{table:dataset} w.r.t. the number of samples in Covid-19, Pneumonia and Normal categories.

\subsection{Training Settings}
The proposed AC-COVIDNet model is pretrained on imagenet as suggested by \cite{Wang2020}. Then the entire model is trained in two stages. In the first stage, the encoder network (i.e., feature extractor) is trained using contrastive loss function as suggested in \cite{supcon} for feature extraction, so that the distance between the learnt features is optimized. In the second stage, the feature extractor is frozen and trained by adding a classifier on the top with cross entropy loss function.
We train the proposed model as well as the state-of-the-art models on all three variations of COVIDx dataset, i.e., with 100, 150 and 200 test images of different categories. The models are trained using Adam optimiser \cite{adam}. The learning rate is set as 1.7e-4. The batch size of 64 is used. We use Relu activation function in every layer of the network and softmax in the last layer. Max-pooling is used after every batch of PEPX layers. The three versions of the COVIDx dataset are used for training and the sensitivity of the classes are compared. Covid-19 sensitivity is the percentage of instances with Covid-19 that are correctly identified. The model is trained using the computational resources provided by Google Colab. Keras deep learning library is used with tensorflow as a backend.

\section{Experimental Results and Analysis}
\label{experimentalresults}

We test the proposed AC-CovidNet model on all three configurations of the COVIDx dataset and calculate the sensitivity for Covid-19 and other classes. In order to demonstrate the superiority of the proposed method, we also compute the results using state-of-the-art deep learning based Covid-19 recognition models, such as CovXNet \cite{covxnet}, COVID-CAPS \cite{afshar2020covidcaps}, CNN Ensemble \cite{cnnensemble}, DarkCovidNet \cite{darkcovidnet}, COVID-Net \cite{Wang2020}, and CovidAID \cite{covidaid}.
The results in terms of the sensitivity for the Covid-19 class are reported in Table \ref{table:results}.
On configuration I (i.e., COVIDx-v1 dataset with 100 test images), configuration II (i.e., COVIDx-v2 dataset with 150 test images), and configuration III (i.e., COVIDx-v3 dataset with 200 test images), the observed Covid-19 sensitivity using the proposed AC-CovidNet model is 96\%, 96.66\%, and 96.5\%, respectively.
It can be observed in Table \ref{table:results} that the proposed model outperforms the remaining models over all three settings of the COVIDx dataset.

Note that the proposed model is able to achieve better results than the other compared models because the proposed model learns the Covid-19 specific features using the attention module and increases the separation between different classes in feature space using the contrastive loss. In the configuration I of the dataset (with 100 test images), the performance of the proposed model is better than CovXNet, COVID-CAPS, CNN Ensemble, DarkCovidNet and CovidAID models and same as COVID-Net. Thus, in order to demonstrate the advantage of the proposed model, we compare the results with less number of training samples and more test samples. Basically, it depicts the generalization capability of the proposed model. On an expectation, a bigger test set can reflect the better generalization of the deep learning models. Thus, we experiment with configuration II having 467 training samples and 150 test samples of Covid-19 category. It can be seen in Table \ref{table:results} that the proposed model is able to retain the similar performance by correctly classifying 145 Covid-19 images out of 150 in the dataset. However, the performance of other models dropped significantly. We also test the performance by further reducing the number of training samples and increasing the number of test samples in configuration III with 417 training images and 200 test images from Covid-19 category. It can be noticed that the performance of the proposed AC-CovidNet model is still similar. However, the other models drastically fail to generalize in case of limited training set. Thus, it clearly indicates that the proposed AC-CovidNet model is able to capture the robust and discriminative features pertaining to the Covid-19 infection and generalize well even with the limited training data. It also shows the positive impact of attention modules and contrastive learning for the Covid-19 recognition from CXR images.

The impact of the attention and contrastive mechanism is also investigated by considering the only attention and only contrastive mechanism with base network CovidNet (i.e., CovidNet + attention and CovidNet + contrastive loss, respectively). As shown in the results using these methods in Table \ref{experimentalresults}, the performance of AC-CovidNet, which uses both attention and contrastive mechanisms, is improved than the models which use only attention and only contrastive mechanisms for Covid-19 recognition. We also report the results for other two classes in Table \ref{experimentalresults}, i.e., Pneumonia and Normal. It is observed that the performance of the proposed model is comparable to the state-of-the-art for Pneumonia and Normal classes.

\section{Conclusion}
\label{conclusion}
In this paper, an AC-CovidNet model is proposed for Covid-19 recognition from chest X-Ray images. The proposed model utilizes the attention module in order to learn the task specific features by better attending the infected regions in the images. The proposed model also utilizes contrastive learning in order to achieve the better separation in the feature space by increasing the discriminative ability and increasing robustness. The results are computed over three different configurations of Covid-19 dataset with varying number of training and test samples. The results are also compared with six recent state-of-the-art deep learning models. It is noticed that the proposed AC-CovidNet model outperforms the existing models in terms of the sensitivity for the Covid-19 category. Moreover, it is also observed that the performance of the proposed model is consistent with a limited training set. Whereas, the existing methods fail to do so. It shows the better generalization capability of the proposed method. The future work includes the utilization of recent development in deep learning to solve the Covid-19 recognition problem from chest X-Ray images with better performance.

\bibliographystyle{splncs04}

redpajama_set_name: RedPajamaArXiv


With a heritage dating back over two hundred years, Robert Sorby is the world's premier manufacturer of specialist woodworking tools. Originating in Europe, these chisels have gained a reputation for their superb handling qualities on spindle work.Size: 1/2"
With a heritage dating back over two hundred years, Robert Sorby is the world's premier manufacturer of specialist woodworking tools. Originating in Europe, these chisels have gained a reputation for their superb handling qualities on spindle work.


text:
Iran Facing Pressure to Cooperate with IAEA - 2004-10-13
The Group of Eight industrialized nations is set to discuss Iran's nuclear program Friday In Washington. A top U.S. official says Iran can avoid possible sanctions if it cooperates with the U.N. nuclear watchdog.
Officials from the Group of Eight, including Deputy Secretary of State Richard Armitage and Undersecretary of State John Bolton, say they will explore a common strategy on Iran just days after Tehran rejected European efforts to halt the Islamic Republic's uranium enrichment program.
Speaking in Tokyo, Mr. Armitage praised Germany, the United Kingdom, and France for trying to stop Iran's program, saying the Iranians had made the decision to conceal it.
"They continue to hide their program and they have made some very scurrilous statements publicly. We hold a view that Iran needs to be brought to account," he said.
While saying Washington is open to all ideas, Mr. Armitage told reporters Tehran should understand that the G8 wants to see an Iran free of nuclear weapons.
Iranian Foreign Minister Kamal Kharrazi said Tuesday his country would not be forced through negotiations to stop its enrichment activities.
The United States and others believe Iran's nuclear activities are aimed at developing atomic bombs. Iran says the program is for generating electricity and wants to enrich uranium so that it does not have to depend on imported fuel.
The United States has been pressing the International Atomic Energy Agency to find Iran in violation of the Nuclear Nonproliferation Treaty.
The U.N. nuclear watchdog last month called on Tehran to halt its enrichment activities. The IAEA said it might refer the issue to the Security Council if Tehran fails to take action before the Agency's governors meet on November 25.

redpajama_set_name: RedPajamaCommonCrawl


text:
Climate Change: A Concern For Society?
Aidan Radcliffe, Editor
Climate change has long produced often-bitter debate, with many signaling it as a bringer of the end of the world—and others calling it a nothingburger. This difference matters, perhaps more than anything else in our time. Children are now used as speakers for international debates as they vociferously claim we've begun a campaign of destroying childhoods, likening our situation to a world war, and characterizing the US as intent on world destruction—but are we truly at war with an unseeable foe?
Throughout the history of the Earth, climate has been mercurial: Earth has varied, bouncing between periods of intense cold and severe warming. Yet with the advent of modern amenities and the subsequent burning of fossil fuels, many claim the release of greenhouse gases directly affects the current climate. It's ignorant to deny climate change itself, yet as many scientists have acknowledged, all of Earth's history intrinsically involves climate change, reaching depths and heights that effectively segregate Earth's natural history into ice ages and green ages (periods of intense heat)—but why is this now a concern that has children skipping school for protests and environmentalists up in arms?
As AP Biology teacher Mr. Como argues, "..we haven't had any type of standardization of direct temperature for over two hundred years," indicating that the precise technology required to analyze climate change over a long period of time wasn't always readily available. Isotopic frequencies from ice cores are often used as a proxy for direct temperature and this lack of standardized measurement leaves a large gap for speculation from both scientists and the general public.
Yet, is the burning of fossil fuels directly related to global warming? "Yes, [humans affecting global climate through extraneous means] is very, very possible," Mr. Como agrees. "…[But] there are periods in Earth's history where we've had as much as eighteen times the amount of CO2 in the atmosphere making it difficult to determine if humans really have contributed substantially." So without concrete evidence, perhaps this period of global warming we're experiencing isn't a cause for uproar, but instead a natural progression.
But what of Greta Thunberg—the 16-year-old climate activist who recently spoke at the UN Climate Summit? As many know, Thunberg is a Swedish teenager who happens to be on the Autism spectrum and has received relatively little formal science education as a whole. Anyone should be ashamed of needlessly bullying Thunberg for her condition, but how she's paraded around as the "messiah of climatology" is nearly as bad. Any teenager, regardless of mental status or personal views, should not be displayed in a public forum in such a way that they become not only a political object, but a target ripe for attack and insult.
Yet despite the genuine nature of Thunberg's horror for the state of the Earth's future, many ethical questions have been raised about the political use of Thunberg from both sides of the partisan lines. And with the German inquiry into child abuse on part of Thunberg's parents—we as a society should encourage Thunberg to live as a normal teenager and not transform her into a political punching bag.
The German investigation raised this past week details the profiteering and political power given to others because of Thunberg and her stance. As Thunberg has now written two books and profits are given and controlled by her parents who act as her managers, many questions are left as to why Thunberg needs money when her sole goal is to save the environment from the greedy capitalists who have put profit over the well being of the environment.
Before becoming a climate activist, Greta would be too anxious to go to school for months and would often go long periods of time without eating, yet she is now paraded on stages and in streets where she is very likely anxious—so is this really the best thing to do to a teenager with an anxiety disorder? On top of this, many have claimed that Swedish companies have profited millions off her public appearances and her speeches have no doubt affected global viewing of climate change which in turn may help with lobbying and policy making;however, the German Inquiry has not concluded their investigation yet.
This clearly affects not only the world but Bethpage as well. Bethpagians should do their own due diligence regardless of political bias. But should Bethpagians make a general movement to be environmentally conscious even if global warming is a natural process? Should we lower our carbon footprints? Should we recycle and try to reduce pollution? Absolutely, protection of the environment is one of the most important things we as individuals should partake in. Recycling, preventing litter, and lobbying for control and to reduce environmental pollution is incredibly important and every individual from Bethpage to Hong Kong should make an active attempt to prevent everything from fertilizer runoff to the release of harmful toxins into nature.
Amalia Lal
Amalia Lal is a Sophomore in Bethpage High School taking her first year of journalism. Although her given name is Emily, she often goes by the name Amalia, which is her name in Greek. Amalia is fluent...
Questiones per Dylan Morales
Hidden Talent: Teacher Edition
Top Five Songs of 2019
Verbatim Interview: Ms.Pillittier
Bethpage's Chris McGuggart Commits to Play Baseball at New York Tech
The Eagle's Cry Interview; BHS Social Studies Teacher, Mr. Lynch
Michael Melendez Verbatim Interview
Verbatim Interview: Ms. D'Alleva Part 1
The Eagle's Cry Interview: Ms. Aguirre


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FEATURES "Dada Distractions" is Aan's Comeback From a Very Difficult Year By Michael White · November 22, 2016
Everyone loves music borne of tragedy: mortal, romantic or otherwise. Alas, in these circumstances, the listener's gain is inevitably a product of the artist's loss—which Bud Wilson, linchpin and singer-guitarist of Aan, knows better than most. The band's just-released second album, Dada Distractions, is largely the result of 2015, a year Wilson's record label succinctly describes as having been "a motherfucker" for the man: two of his close friends died, as did his relationship of six years and the previous incarnation of Aan. Meanwhile, he looked on helplessly as his adopted hometown of Portland, Oregon, became "steadily less familiar and more expensive" in the face of gentrification.
Fortunately, rather than a document of defeat, Dada Distractions is the sworn testimony of an artist coming out fighting. A combination of simplicity and sonic surprises in the manner that has made Spoon and Built to Spill endlessly intriguing, producer Riley Geare (former drummer in fellow Portland group Unknown Mortal Orchestra) captured the sound of Wilson and his newly recruited cohorts—Travis Leipzig, Gabriel Nardin and Dana Valatka—seemingly playing for their lives in a small room. From the power chords and bongo beats of opening track "Lookout!," the album makes plain that rock is Wilson's redemption.
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Bandcamp recently spoke to Wilson—who, despite his recent past, seemed good-humored, thoughtful, and ready to delve into the next chapter of his personal and musical life.
The circumstances that inspired Dada Distractions are, frankly, brutal. Is it helpful for listeners to understand the context in which the album was written?
In this instance, the gravity of this record is important to me that people kind of understand, otherwise it might seem kind of boring. (pause) Not boring. It might seem… just heavy for its own sake, and that's not the intention. It's just sort of [an emotional] release in that way. When I read the bio [which his label wrote], I was like, "Oh, shit." But it's true! Let's go with it.
Does the use of the term "Dada" in the title [in reference to an early 20th-century art movement that celebrated irreverence and the nonsensical] meant to show that you see the humor in it?
That's spot-on. I think that's the only way to handle some of the shitty things that have gone on recently. You've gotta laugh and have fun with it!
As much of a cliché as it is, has it proved to be a blessing in disguise? Despite the circumstances that inspired these songs, is the album, as an end product, more gratifying to you than the last one [2014's Amor Ad Nauseum]?
I think it's more immediate. It certainly was written and recorded more quickly than the last record, so it has more impact for me. When I perform the songs, they're much more real than the last record, which was more a patchwork of sonic ideas instead of 'Let's write a song and play it.' I enjoy these songs more, and I think they're just… they're more succinct.
This album was recorded much more quickly and much more "live" than the previous one? Is one recording process more enjoyable than the other, or do they both have their virtues?
They both certainly have their virtues. The last record, it was basically recording school for me, so when we worked on it I wanted to be involved in everything we were doing. The producer and I would just pore over every idea and we were so meticulous, whereas with this record… First off, we didn't have time to do that, because Riley—half the time was playing with [Unknown Mortal Orchestra], so he'd be in Turkey or he'd be packing up and getting ready to go to Spain. He was leaving for a tour so often that what little time we had together needed to be productive, so we didn't dig so deep into effects. It was more about capturing the performance as best we could.
And in the moment, that didn't bother you? Your previous instinct to tinker with things, was that gnawing at you at all?
We had a manifesto from the beginning, basically, that we weren't going to manipulate anything in a digital way. I thought it was really important to do that this go-round, because the last record was so "in the box," as they say. I'd written down four or five rules to go by, and one was "No tuning in the box [in post-production]"—like, the sounds that we capture are the sounds we're going to use, so no beat correction or anything like that. It was a little frustrating at times, because I would hear maybe a kick drum not being exactly in the right spot. These are things you don't notice even in rehearsals when you're getting ready to record, because a lot of times you're focused on your own parts. I might think, "That's not exactly how I wanted it to be," but I'm not sure that it makes for a stronger record. As a group, with everyone having a little bit of input—which is different from the last record—I think it sustained everyone's appetite a little more. They're glad they took part in it, versus everything getting pushed around in a computer.
Were you more of a dictator the last time, if that's the right word?
Frankly, yes. I would change things and not tell everybody. Even on this record, I was the only one who was consistently in the control room with the engineer, checking to make sure we were getting what we want, and showing up for mixing sessions and things where not everybody else in the band could or wanted to be there.
But were you happy to surrender some of the control you enjoyed last time?
I think so, yes. And the more control that I gave up—particularly with Riley, when he had time—the more pleased I was with the outcome. I was nervous about it, and Riley's a confident engineer and producer, so he had his own ideas. And I guess that's part of—when you work with a producer, that's the understanding, that they're gonna play some role. There are things that I would maybe change, but there are a lot of things I didn't think of that I like.
The sonic detail of your music is important to you, and you've described it in the past as "experimental pop." But most people think of "experimental" as cerebral and not about emotional expression in the same way that pop music is. Were you trying to bridge the gap between those two worlds?
I think a lot of those tags—they get applied to us and I'm like, "OK." Someone recently called us "prog-pop" because our new material has a bit more noodling in it. I don't concern myself too much with the pop elements. I guess it's important to make sure there's always something in the song that keeps the listener piqued or curious. It's hard to call us experimental, as much as I would enjoy that title. I think we're more along the lines of a rock band by default, but I don't necessarily push for pop or any one element. It is what it is.
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CLUB WYNDHAM®, one of more than 20 brands in the premier portfolio of Wyndham Destinations, offers 100 resorts and more than 14,000 vacation ownership units across North America and the Caribbean for approximately 509,000 owner families around the world. Whether you're looking for scenic escapes, a romantic getaway, or exciting new adventures — you'll find a CLUB WYNDHAM resort to suit your vacation needs.
Wyndham Destinations makes vacation dreams a reality. We want our owners to create lasting memories with their loved ones by offering them the ease of vacationing together more often. And that's the beauty of our product — allowing our nearly 900,000 owners the flexibility to use our vacation products at more than 220 resorts throughout North America, Mexico, the Caribbean, South America and the South Pacific.
We also have an ever-growing innovative culture throughout our organization and are always looking for new ways to improve our owners' vacation experience, expand our portfolio of products, and evolve our business models, allowing us to remain the industry leader.
CLUB WYNDHAM® is part of Wyndham Destinations, the world's largest vacation ownership, exchange and rental company serving nearly 900,000 owners through 20+ brands including CLUB WYNDHAM, WorldMark® by Wyndham and RCI®. We offer vacation experiences in 110 countries, more than 220 vacation ownership resorts and 4,300+ affiliated exchange properties across the globe, as well as nearly 10,000 vacation rentals in popular North American locations. We help people experience the limitless possibilities of vacations — of owning them forever, exchanging for a new view, or renting for a visit.
From the breathtaking mountains of Tennessee and Colorado...to the exciting attractions of Orlando and Myrtle Beach...to the star-filled stages of Branson and Las Vegas...to the sandy shores of California and Florida, you'll find CLUB WYNDHAM® resorts in America's most scenic and popular destinations. Every vacation unit is fully furnished, and many feature special amenities such as washers and dryers, private whirlpool spas, and fireplaces.
From active efforts to reduce resort carbon footprints to offsetting electric usage with solar panel installations to the sustainably-sourced materials used in your suites, CLUB WYNDHAM delivers great vacations while also being environmentally conscious. By adopting sustainable practices, we're ensuring that the planet is a better place for future generations of vacationers just like you to enjoy.
Wyndham Cares is a free solutions service for those who are interested in learning how to maximize their ownership, may be experiencing changes in their financial status, or are considering whether vacation ownership is still right for them.


Pueblo Community College Southwest kicked off the school year on Aug. 20 with its ninth annual Celebration Walk. Students enrolled this semester all got a free PCC T-shirt. PCC Southwest offers general education college classes that are guaranteed to transfer to any four-year college in Colorado as well as degrees and certificates in nursing, welding, automotive service technology, cosmetology and law enforcement.
Courtesy photoPueblo Community College Southwest kicked off the school year on Aug. 20 with its ninth annual Celebration Walk. Students enrolled this semester all got a free PCC T-shirt. PCC Southwest offers general education college classes that are guaranteed to transfer to any four-year college in Colorado as well as degrees and certificates in nursing, welding, automotive service technology, cosmetology and law enforcement.


There are a lot of companies out there who are interested in buying your cell tower lease, however many will disguise themselves, making you believe otherwise. Here are some things you should consider when asked to sell your lease or if you have been approached by someone you suspect wants to buy your lease. Understand that every lease has different value. Companies who are trying to buy your lease use these uniform formulas to come up with a purchase offer.
Don't assume that the offer made to you is a fair one. In fact, you should always seek guidance from someone who is on your side, helping you determine what your lease is really worth. When property owners enter a buyout transaction they will often be asked to allow the company purchasing the cell tower lease use of their property for 50 years or more, impacting the development, disposition and financing of the overall property.
Lastly, be aware of deceptive practices. Finance companies trying to buy your lease will often make themselves appear to be telecom companies, claiming they can add tenants and revenue to your property. They will use this tactic to grab your attention, and once they have that, they will try to proceed with the real motives behind contacting you. Vertical Consultants strives to keep you informed, providing you with insider information and delivering results that benefit your bottom line.


Licorice is one of those candies you either hate or love. Chewy, sweet, and with a touch of anise, the taste is notoriously polarizing. But if the taste of licorice makes you cringe, fear not: you don't have to actually ingest it to benefit from its powerful skincare properties.
Licorice root extract has been used for hundreds of years in traditional medicine. It's said to help treat canker sores, as well as to treat peptic ulcers, indigestions and a host of other gastrointestinal issues. Licorice root extract also helps clear up upper-respiratory problems, like phlegm and mucus buildup, when you have a sore throat or a flare up of allergies.
Okay, okay, so even if you hate the taste, it might be worth trying licorice root tea every once in a while. But what about the skincare benefits of licorice root extract? You haven't heard the name thrown around for no reason.
If you have particularly sun-damaged or red, irritated skin, licorice root extract could be what you're looking for. Licorice root extract contains the antioxidant glabridin and licochalcone A. They both have powerful anti-aging and skin-soothing properties.
Glabridin in particular has been shown to mitigate the effects of sun damage. It "disperses melanin and inhibits melanin biosynthesis" — basically, it brightens damaged skin and blocks the enzyme that triggers skin to darken after being damaged by UV radiation.
That means licorice root extract can combat hyperpigmentation: those annoying dark marks you get from sun spots or acne scars that don't just fade away. It's a natural and soothing way to treat those marks that doesn't involve harsh chemical peels.
Licochalcone A, on the other hand, works to defend your skin against free radicals. Its anti-inflammatory properties mean that products containing licorice root extract are great choices to treat skin disorders like rosacea and eczema.
And as a bonus, licochalcone also regulates your skin's oil production. So if you've been experiencing breakouts caused by super oily skin, this anti-bacterial, anti-inflammatory ingredient might just be your holy grail.
Even if it's not your go-to movie snack, licorice root extract is worth adding to your skincare regimen. We love it so much we knew we had to include it when we revamped the formula of our Daily Face Repair. It's a natural ingredient that helps this moisturizer give your skin powerful regeneration properties, a healthy glow, and a soothing touch. Give it a try. We promise there's no aftertaste!


Pender's own American Heritage Girls Troop VA1907 will host an Ash Wednesday Spaghetti Dinner at Pender on Feb. 18 from 6 – 6:45 p.m ~ prior to our Ash Wednesday Service at 7pm.
The dinner i ncludes a choice of white or wheat pasta and meat or vegetarian sauce, garlic bread, salad and dessert. A gluten-free option is also available.
Reservations are requested to help with planning. Please sign up by Feb. 15 by clicking on this link.
Proceeds from donations to the dinner will help support the needy in our community.


Look skyward on a clear evening and you can see planets, nebula, galaxies and, of course, billions of stars dotting the night sky. Among those stars, you can visualize the ancient connections that make up constellations and many of the wonders of our solar system. Could this interconnected view of the universe inspire a new, global mindset to create social impact and generate action here on Earth?
Organizations could make a major impact if they teamed up together.
With imagination, you can see how to create social impact in an entirely new light. Because while individual organizations serving society may shine brightly on their own, the impact they could make if they teamed up to solve the world's most intractable societal problems could be truly spectacular.
That new mindset took center stage last year in Copenhagen at the inaugural global innovation lab, UNLEASH. There, a thousand carefully chosen, young social entrepreneurs came together from across the world to develop innovative approaches to the United Nations Sustainable Development Goals (SDGs).
Implementing blockchain technology to detect counterfeit vaccines.
Wrapping cargo pallets with reusable, stretchable Lycra® instead of single-use plastic wraps to greatly reduce plastic waste, petroleum use and CO₂ emissions.
Creating black soldier fly farms to transform food waste into animal feed and fertilizer.
Enabling people to use artificial intelligence to self-monitor and detect colorectal cancer.
These are just a small number of the solutions that are now being supported by the UNLEASH ecosystem of investors, experts, mentors and more than 200 organizations globally, including Deloitte.
In connecting people and organizations from all over the world to imagine new solutions to intractable societal problems, UNLEASH has created a new mindset around social impact, a new mindset focused on working together to deliver innovative, coordinated, global action that achieves results.
This mindset continued to gain momentum this week in Singapore at UNLEASH 2018. For the second straight year, Deloitte served as UNLEASH's primary innovation leader and facilitated the world's largest innovation workshop.
It's a role we're proud to play. Multiple surveys show public trust and confidence in government, business, NGOs and media is at an all-time low. Business, however, is considered the most likely of these groups to have a positive impact on the world's most difficult challenges.
Responsiveness: Business is wired with a bias for action—either preemptively, as a source of first-mover advantage; or reactively, as a mechanism to regain competitiveness. Individual and institutional buyers who once purchased products and services now buy brands and relationships, and they can see through inauthentic corporate gestures to win market favor. They demand—and businesses are delivering—responsive action to buyers' concerns.
Innovation: Business prizes the ability to meet customer and client needs better, quicker and more efficiently, and has tangible incentives for introducing creative, never-before-conceived ideas that eradicate problems.
Scalability: Coordinated global efforts to solve the complex problems of our time have not kept pace with societal needs. In other words, the problems are more agile and adaptive—so coordination to solve them requires the same. Business has what it takes to scale coordinated efforts that take big bites out of big problems instead of nibbling on the edges.
Talent: Businesses, including Deloitte, are preparing their people for the Fourth Industrial Revolution. The ability to innovate, think creatively and deliver social impact alongside financial returns are all core competencies that businesses can offer to these challenges.
Business cannot succeed if society fails. But society has far less chance at succeeding if business fails to lead. So, it's up to us to work together to contribute everything that business knows—including responsiveness, innovation and scalability—and channel these resources with focus and force to address society's most difficult challenges. Unleashing that kind of power has the potential to brighten our collective future. That's something I think we should all fix our gazes upon.


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If you find this guide useful, we thank you. Our content development team have been working on these guides for your enjoyment and use. We pride ourselves on creating great content for our users. If you have a suggestion for an article or guide, please contact us via Support Ticket or our 24/7 Live Support. For more articles like this, check out our Articles, Guides, and TShock tips on our TShock Terraria Knowledge Base.
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Using TShock with Terraria can evolve your gameplay to levels you would never be able to reach with vanilla Terraira. By following this guide you will know everything to do with installing TShock Plugins. It's easy, and it will enrich your gameplay on many levels!
First, you must select your plugin. Go to TShocks Plugin Directory linked here to find a list of all available TShock plugins. For this example, I chose a plugin called TeleportRequest. This plugin allows you to request to teleport to other players locations, permission is required so this would be great for a multiplayer server. If you want to use this as your first plugin, you may download it from this link.
The next step, under "Game Services" STOP your server from your GameServerKing's Server Management panel, and then locate "File Manager."
Next, you must locate the plugin installation folder on your Terraria installation, for Gameserverkings.com Terraria Tshock servers, it is located at "/ServerPlugins/".
This is the file you want to upload your plugin's .dll file. In this instance, my file is "TeleportRequest.dll." In other instances, your file may be in a zipped or compressed folder. To unzip, depending on your operating system, you may have to download a .zip extractor to access the .dll file. To upload your plugin's file click on the "ServerPlugins" folder to enter it, and then click upload in the top left corner of the file manager. From there, click browse and find the location of your saved .dll file. Mine was inside my "Downloads" folder.
An alternative to using our management panel is to use FileZilla or another FTP client. We allow our users to have free access to an FTP service. Our guide is located here: How to Use FileZilla with your GameServerKings Server.
Reboot your server and the plugin will now be installed!
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May 1st marked the 60th annual Law Day, as well as the inaugural celebration hosted by Lakeland Christian School. Members of the local legal and judicial community intermingled with LCS law students, celebrating the support and generosity provided to mentor the next generation of legal professionals. Members of the LCS Mock Trial Team were honored for their sterling performance and professionalism at the State Finals by Erin Watson, director of the Mock Trial program in Florida. Florida Supreme Court Justice Charles Canady spoke about the role of the separation of powers in promoting balance in government and rule of law.


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text:
package com.zxytech.designpatterns.gof.behavioralpatterns.templatepattern;

/**
 * Created by ryan on 2016/12/18.
 */
public class Cricket extends Game {
    @Override
    void initialize() {
        System.out.println("Cricket Game Initialized!");
    }

    @Override
    void startPlay() {
        System.out.println("Cricket Game Started. Enjoy the game!");
    }

    @Override
    void endPlay() {
        System.out.println("Cricket Game Finished!");
    }
}


text:
Ecclesiastes 7:6
Only my translations
6 For as the crackling of thorns under a pot, so is the laughter of the fools; this also is vanity.[1] (Ps 58:9; Ps 118:12; Joe 2:5)
(Ps 58:9; Ps 118:12; Joe 2:5)
6 Like the crackling of thorns under the pot, so is the laughter of fools. This too is meaningless.
New International Reader's Version
6 A foolish person's laughter is like the crackling of thorns burning under a pot. That doesn't have any meaning either.
6 For as the crackling of thorns under a pot, so is the laughter of the fool: this also is vanity.
Copyright: English Standard Version – The ESV® Bible (The Holy Bible, English Standard Version®) copyright ©2001 by Crossway Bibles, a publishing ministry of Good News Publishers. ESV® Text Edition: 2016. The ESV® text has been reproduced in cooperation with and by permission of Good News Publishers. Unauthorized reproduction of this publication is prohibited. All rights reserved. The ESV® Bible (The Holy Bible, English Standard Version®) is adapted from the Revised Standard Version of the Bible, copyright Division of Christian Education of the National Council of the Churches of Christ in the U.S.A. All rights reserved. | New International Version – Holy Bible, New International Version ® (Anglicised), NIV TM Copyright © 1979, 1984, 2011 by Biblica, Inc. Used with permission. All rights reserved worldwide. The "New International Version" is a trademark registered in the European Union Intellectual Property Office (EUIPO) and United States Patent and Trademark Office by Biblica, Inc. The "NIV", "Biblica", "International Bible Society" and the Biblica Logo are trademarks registered in the United States Patent and Trademark Office by Biblica, Inc. Used with permission. | New International Reader's Version – Holy Bible, New International Reader's Version®, NIrV® (Anglicised) Copyright © 1995, 1996, 1998, 2014 by Biblica, Inc.® Used with permission. All rights reserved worldwide. "Biblica", "International Bible Society" and the Biblica Logo are trademarks registered in the United States Patent and Trademark Office by Biblica, Inc. Used with permission. | King James Version – Copyright © Biblica, Inc.® Used by permission. All rights reserved worldwide.
Further contents


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text:
HomeAerial LiftsGenie GS 4047
Genie GS 4047 Scissor Lift
The Genie GS-4047 electric scissor lift has four 12V 350ah batteries and a turning radius of over 7 feet. This lift can operate on grades up to 25% and has an excellent combination of height and lifting capacity. Buy or lease the GS-4047 from CanLift.
GS 4047 Electric Scissor Lift From Genie – Overview
Designed specifically to meet the needs of tightly-packed indoor floor spaces in modern warehouse-style buildings, this self-propelled electric scissor lift from Genie does everything you'd want it to and more besides. By offering an excellent combination of both height and lifting capacity, quiet but powerful drive motors only help to maximize the performance. At the same time, the unit's excellent build quality serves to increase the confidence of operators working at full height.
Genie GS-4047 Electric Scissor Lift- Making Light Work Of Any Task
The first thing you notice about the GS-4047 scissor lift is that it's been designed with the end user in mind. The smart-link control system, for instance, allows full and precise control of movement to allow perfect positioning. The four-wheel braking system makes for a truly responsive unit while the zero inside turning radius and compact nature of this scissor lift (just 8ft in length and 47 inches wide when stowed) means that it's perfect for working in restrictive environments, where space is at a premium. With a top speed of 1.9 mph and grade-ability of up to 25%, it allows operators access to many places that other similar models in its class can't, such as loading ramps and slopes. The 3 ft extension on the platform offers a total operating length of 10ft 5in. This coupled with the generous 3ft 9in width, allows up to 3 people to work in both comfort and safety. The powerful hydraulic system means that the platform can be raised to its full 45ft height in just 71 seconds and lowered in 41 seconds, while four heavy duty 12v 350ah batteries ensure longer battery life and less downtime. When it comes to servicing and maintenance everything about the GS-4047 has been made easy too. An easily accessible, swing-out engine tray means that components can be fault diagnosed, identified, and changed easily, while many other component parts are fully interchangeable with other GS scissor models, meaning service departments need to stock fewer parts all around.
Buy this GS -4047 Electric Scissor Lift from CanLift
At CanLift we offer a wide variety of lifting gear to buy at great prices and this includes the GS-4047 scissor lift from Genie. Why not contact us today and speak to our friendly and experienced team and let us show you how we can help you find the exact equipment to match your needs and/or budget.
GS 4047


This longline, tapered long sleeve winter wardrobe basic is perfect alone or underneath shirts, vests, dresses and more.
The fabric is superfine and contains lycra for excellent fit and feel. These are figure-hugging shirts, if you prefer a looser fit, order one size larger. Made from 95% fairtrade certified organic cotton with 5% lycra.


Storage: Make sure the leaves are completely dry. Better to hold off rinsing them until you're about to use them. Fill a jar or a water glass partially with water and place the stem ends of the herbs into the water in the jar. If you are storing the herbs in the refrigerator, cover loosely with a plastic bag.


Sightsavers' partner Lotus College of Optometry (A Primary Eye Care Profession) set a record of sorts in terms of the number of research papers selected for the upcoming Asia Pacific Optometric Congress (APOC) later this year. A total of 11 papers (oral as well as poster) were been selected.
Asia Pacific Council of Optometry (APCO) represents the Asia-Pacific region as one of the regional secretariats of the World Council of Optometry. The mission of APCO is to facilitate the enhancement and development of primary eye and vision care by optometrists in the Asia and the Pacific regions.
A bi-annual scientific meeting, the Asia Pacific Optometric Congress (APOC), has been held since 1978.The upcoming 18th APOC with the theme "Optometry – A Primary Eye Care Profession" will be held in November this year at Suntec Singapore International Convention and Exhibition Centre, Singapore.
Sightsavers has been partnering with Lotus College of Optometry for a few years to support the Masters in Optometry course. The objective of this partnership is to strengthen the course and support research studies, improve service delivery at primary level and develop teaching faculty for the B. Optometry level.
Sightsavers is happy to see its support reach new heights.


A VERY BIG THANK YOU!!!!
For the brave soles that braved the light rain to the flood by afternoon. We thank each and everyone of you that sloshed their way through the events today.
Awesome shooting by Jason Burroughs even in this weather.
Congratulations to our "Drawing Winners"
Sun will be Shining and Birds will be Singing!!