AN EFFICIENT APPROACH FOR SELECTIVE COLLECTION MADE BY
SCAVENGERS FOR TRANSPORTATION LOGISTICS OF RECYCLABLE MATERIALS
Adelino Carlos Maccarini
Universidade Tecnológica Federal do Paraná (UTFPR),
Brazil
E-mail: maccarini@utfpr.edu.br
Gilson Adamczuk Oliveira
Universidade Tecnológica Federal do Paraná (UTFPR),
Brazil
E-mail: gilson@utfpr.edu.br
Naiá Mendes Maccarini
Universidade Tecnológica Federal do Paraná (UTFPR),
Brazil
E-mail: naia.mac@gmail.com
João Bosco Ladislau de Andrade
Universidade Tecnológica Federal do Paraná (UTFPR),
Brazil
E-mail: boscoladislau@mandic.com.br
Submission: 30/04/2013
Revision: 16/05/2013
Accept: 10/10/2013
ABSTRACT
The
advance of technology, associated to the increase in the production of
recyclable waste due to the increase of consumption and population, has been
led to a search for alternatives of management and minimization of this waste.
A part of this recyclable material is collected by scavengers, who do it to
guarantee their livelihood. Many of them face logistical difficulties in
transportation, mainly when they have to walk long distances and the streets
have high slopes.
Therefore,
to minimize these efforts, the purpose of this paper is to settle mobile
warehouses to receive recyclable items, with trucks that receive in bulk all
materials collected by the collectors, who will deliver them to someone who
will be in the truck for weighing and subsequent payment to the collector. With
the help of the Analysis of Variance – ANOVA, studies were made so that this
receipt is a quick operation, with the historical record of each sampling in a
spreadsheet and value calculations based on this description, thus minimizing
errors in weighing in bulk and improving, in every collection, the system
reliability.
Keywords: selective
collection, scavengers, waste material
picks, collector, solid waste, garbage, ANOVA, statistical methods.
The
selective collection made by scavengers has been structured each day. Methods
to minimize the effort often arise, but the collectors still face serious
logistical difficulties in transporting recyclable materials, especially when
they have to travel long distances and higher slopes streets.
Some
methods are uneconomical, with high and inaccessible costs to the collectors’
reality. An example is the installation of fixed warehouses, scattered
throughout the city, for delivery and commercialization of recyclable
materials. Beyond expensive, can cause discomfort to the surrounding residents
because of outbreaks of dirt and odors, also proliferation of vectors such as
rats, cockroaches and flies. If these fixed warehouses were managed by
collectors, the surrounding community, in a way, would further reject the
initiative, because, among other problems, many residents, by distrust, do not
accept the collectors.
The
purpose of this study is to install up mobile warehouses, rather than fixed
receiving warehouses, with trucks that receive, in bulk, all collected
materials. The scavengers would deliver the materials to someone who would stay
in the truck for weighing and subsequent payment to the collector. Using the
Analysis of Variance method – ANOVA, proposed by Ronald Aylmer Fisher in 1925,
this receipt should be a quick operation. With the historical record of each
sampling in a spreadsheet and value calculations based on this description, it
is possible reduce weighing time in bulk errors and improving, in every
collection, the system reliability.
The
aims of this research are: analyse the receipt processes of recyclable
materials; relate the weighing of materials collected daily by the pickers with
the historical of what was collected during a particular period; show that is
possible reduce the time in material separation tasks, delivering in
homogeneous groups formed through ANOVA; speeding up the materials weighing;
propose a more efficient and faster way to commercialize recyclable materials.
Developing
countries are faced with serious environmental and administrative challenges
with respect to solid waste (SW) management. The public sanitation system lacks
because of inadequate planning, as well as unsustainable management. Mexico,
for example, depends heavily on personnel with no technical training and the
separation of the waste is carried out by an ever-increasing number of
scavengers. It is essential include these groups in the decision-making process
in order to assure the success SW management programs (BUENROSTRO; BOCCO,
2003).
An
important goal of a successful solid waste management program is to handle and
dispose waste at a reasonable cost while minimizing adverse environmental
effects. A well-planned recycling program may help achieve this goal while also
creating job opportunities and conserving material resources. Recycling and
composting have been practiced advantageously in many cities of the developed
countries (AGUNWAMBA, 2003).
Also
it is relevant, mainly in developing countries, to reduce the amount of waste
generated and sent to the open dumps. Recycling and reuse practices can make
this possible. It is also very necessary to improve and help organize markets
for the recyclables. Information and education can bring a change to people’s
towards waste management, and it can encourage the public attitudes to take
responsibility for the waste generated (BATOOl; NAWAZ, 2009).
As in
other major cities in developing countries, the informal sectors still hold an
important role in the recovery of usable materials from waste. However,
inorganic waste recycling activities from this sector have not even reached 8%
(wet weight) of the total waste generated (DAMANHURI et al., 2009). Batool et
al. (2008) suggest if the recycling practice is owned by the formal sector, it
can save substantial economic amounts by reducing the collection cost. If
recycling is adopted as an industry, it can generate more revenues and can also
save an enormous amount of energy, as well as the natural resources. It
indicates how the informal sector (the autonomous scavengers) has a high field
to advance to justify its future in this important activity.
According
Kimbugwe & Ibitayo (2013) there is an indication that the scavengers do not
consider waste picking as transitory, but as a full time and stable form of
employment. Scavengers are poor people, suffer harassment from officials and
face health and safety problems during the work. Despite of their low economic
and social status, the overall impact of activities of scavengers is positive
economically and environmentally. This can be improved further if the
government or organized private sector helps them by organizing them, providing
them medical and health facilities, personal protective equipment and financial
incentives (ASIM et al., 2012).
Despite
the innumerous social, economic, and environmental benefits from resource recovery
activity made by scavengers, it is still illegal in most places, as it is also
in Canada (GUTBERLET; JAYME, 2010). It may contribute to explain discrimination
against individuals who deal with selective collection of recyclables and
decrease the value of their work.
Porto
Alegre, a 1.5-million city, has one of the most affordable integrated solid
waste management systems in Brazil. Public participation as a part of the
integrated solid waste management system has been established by allocating a
participatory budget, involving former scavengers associations and implementing
an environmental education programme. It has led to a reduction in the quantity
of solid waste deposited in landfill, allowing income generation for the
scavengers, as a way to decrease local poverty (BORTOLETO; HANAKI, 2007).
According
to Cempre (2007), Brazil produces around 140,000 tons of waste per day. A
portion of this waste, around 90%, goes to dumps or landfills, and only 10% is
sent for recycling or composting. A great part of the considered good material
has been gone to waste and a lot of money has been thrown away, mainly due to
not reusing the materials, how complements Calderoni (1998).
The
generation of waste in urban areas depends on some factors, which are important,
among others, in the assessment of some issues
regarding to solid waste, described by Andrade (1989). They are: economic,
environmental, sanitary, community, cultural, political, number of local
inhabitants and city expansion, usual types of packaging, collections types and
collection equipment types, road system and flooring routes types, distance to
final destination and appropriate way to final destination, the relative area
of production, discipline and control of the producers points, seasonal variations;
climatic conditions; habits; educational level; segregation at source;
systematization of origin, specific laws and regulations.
The
number of scavengers existing in Brazil is very controversial. MNCR (2007)
mentions that there are between 500 thousand and one million of scavengers.
This model suffers variations in each region of the country, due to the country
size and diversity, where the activity is governed by the market laws. What
contributes to the support of the process itself and create working conditions
for those unemployed or those without employment expectation.
The
scavengers are also known as collectors, pickers, paper gatherer, rag picker,
trash collectors, unofficial waste sorters/recyclers, trash scavengers, waste
material pickers, litter-pickers, litter collector and others, according
Gutberlet et al. (2009). Maccarini and Hernandez (2007) divided the activity
into three primary classifications: the scavenger, who lives in the dumps
collecting recyclable materials and then sell them to intermediaries; those who
collect on the streets with their carts, wagons or other vehicles (Figure 1)
and are often called “paper gatherer” and also negotiate their materials with
intermediaries; and those who work in sorting recyclable materials centres and
are often linked to a cooperative or association.
Hence
the selective collection made by the scavengers is, according National Movement
of recyclables scavengers from Brazil (MNCR, 2007), a new model to perform the
selective collection. Preferably consists of, instead of the municipal agency
collect the selected material, the collectors, duly registered and organized,
would do it.
Figure 1 -
Scavenger with his trolley, collecting on the streets
According
Eigenheer (1989), scavengers usually live in suburbs or slums and collect
materials at random in the streets of the districts and commercial centres of
the cities. Most of them are semi-literate and are not organized in
associations as stated by Cempre/Eurostat (2006). Due to their lifestyle, for
realizing an activity which is not professionally recognized, many are
marginalized and discriminated by society. Some often get involved in police
incidents, due to alcohol ingestion and similar, like Folha de São Paulo
newspaper (2006) reports.
The
following is a brief description of recyclable characterization and statistical
analysis. Costa Neto (1989) says that, since the product is formed by solid
material if the homogenization is not feasible, such as the recyclable
materials in this study, it is possible to apply the quartering as called by
Tchobanoglous (1993). This method recommends the division of the material to be
characterized in four parts, sorting one or more parts to constitute a sample
or removing a sample from them.
Toledo &
Ovalle (1988) recommend, after obtaining these data for the characterization,
the use of simple arithmetic average of relative quantity () defined by:
Where:
simple
arithmetic average of relative quantity;
amount of these materials at the present time and
basic zero;
n =
number of samples.
For
the selective collection, there are various possibilities for statistical
calculations, such as proposed by Hines (2006). Therefore, to increase the
reliability of data collected and minimize errors, like Stevenson (1986) says,
it is necessary, first of all, defined its purpose: how, where and what is the
intended information. Also, mentions the author that is also relevant to
recognize, measure and understand the causes of variability, to act about them
and then, the results should be measured and interpreted from technical and
scientific measures. Complement Shimazaki (2007) that these measures start with
simple methods, such as the arithmetic mean, and advance in extremely complex
calculations, now aided by computer technology.
Statistical
surveys may assist the work of scavengers logistics, but due to a lack of
adequate procedures and technical support, was noticed the difficulty in
putting into practice. To apply the results collected on this work, any error
made in the evaluation of the selective materials collected percentage may
mainly affect he collector, who lives on sparing resources. If, however, there
is any error of judgment in favor of the collector, who will suffer are those
who will make the purchase of materials, in this study, the association or
cooperative of scavengers.
The
simple and usual ANOVA hypothesis test was applied. According to Caten (2007),
it essentially divides the variability between groups and within groups and
compares both. This feature allows realizing a simple variance analysis for two
factors with only one sample per group. ANOVA is used to determine if the means
of two or more samples are from the same population. In this case are formed
groups of recyclable materials that have the same relative amount.
The
simple and usual ANOVA hypothesis test was applied. The independent variable is
composed by the 12 groups of recyclable materials and the dependent variable is
the percentage of collected recyclables.
The installation
of fixed warehouses, scattered throughout the city, for the delivery and
commercialization of recyclable materials collected by scavengers, beyond
costly, would result, according to Maccarini studies (2007), discomfort to
surrounding residents. Besides, it could cause dirt and odors outbreaks, with
the proliferation of vectors such as rats, cockroaches, flies, among others.
Besides, what the society has not accepted much, is the agglomeration of
collectors in their neighbourhood. Another procedure to be performed could be
the one with which the collector performs triage in loco in their own stand.
However the space is small to accomplish this separation, which makes also this
procedure unfeasible. The distances, that usually are long to transport the
trolley to the store, are also determinant factors to new thoughts about
alternatives.
One
of these alternatives is that, instead of creating fixed warehouses to
receiving material, settle them in mobile ones. These warehouses would be
formed by a truck and receivers strategically located in the neighbourhood, at
points near the collection sites.
For
the realization of this method, should be implemented before the model of
selective collection made by scavengers proposed by Maccarini (1998). This model
involves the participation of the local community who should leave the
separated garbage in front of their houses, on determined days of the week. The
pickers can then start collecting, and, so that, as soon as they fill the
stands, take to these mobile centres of receiving recyclable materials.
The
receivers would weigh the bulk of material from each collector, depositing them
into bins within the mobile centres of receiving material (which may be a truck
or similar) to then be transported to sorting centres with subsequent
separation of each specific item. This procedure would tend to be fast, given
that would not be needed a receiver or scavengers to make a detailed screening
of the materials, to then know the quantity and what kind of materials were
collected. This would provide the pickers return to stretch to make more
collections than by the traditional method. Figure 2 illustrates the Bulk weighing
method.
Figure 2 - Bulk
weighing method: an illustrative example
In
the sorting centres, the recyclable materials can generate more than 20
different types and which each one is sold with different prices. Some with
higher value than the average of other materials (aluminium, for example, is
sold at an average of R$ 2,00 per kilogram, copper at R$ 7,00, while other
materials ranging from R$ 0,05 to R$ 0,40 per kilogram). To avoid future
troubles, these materials with much higher values, above average, must first be
separated, weighed and paid apart, because, in conformity with Downing &
Clark (2000), they have a large amplitude range.
To
facilitate the study, in this paper the recyclable materials were divided into
12 items only: waste, newspapers, paper (white), cardboard, thin plastic, hard
plastic, PET, glass, ferrous metals, aluminium, copper and similar, and others.
The tailings are all that material which cannot be recycled and eventually
appear on the collected materials, mainly due to lack of knowledge or education
of who separates the trash at home. They include organic waste, toilet waste,
pruning and weeding, among others, which should be directed to the ordinary or
special domicile collection. The classified like papers, include all those
white papers that were not dirty or contaminated by other residues. The thin
plastic is particularly LDPE (low density polyethylene), such as the plastic
bags. The hard plastics are HDPE (high density polyethylene), PP
(polypropylene), PS (polystyrene), PVC (polyvinyl chloride), among others. PET
(polyethylene terephthalate) is the plastic used in soda bottles and other
containers. The glass comprises mainly canning containers and glass bottles.
Ferrous metals are the “tin plate” and other ferrous metals. Copper and related
products represent all non-ferrous metals except aluminum. The "others"
are those which do not fit into any classification previously exposed, such as:
rubber, furniture, electronics, clothes and rags, wood, among others.
Maccarini
(1998) conducted studies and characterizations of recyclable materials
collection performed by scavengers (Table 1). These studies provided 11
characterization data (11 samples) to be interpolated and used with other
realized by Maccarini & Hernandez (2007) (Table 2) and also by data
collection performed by Maccarini (2008) (Table 3).
Thus,
the collected information was grouped to form three distinct data groups. The
first called "Group 1" is one whose data from 11 characterizations
shown in Table 1. For practical purposes, even though these data were outdated,
they were used in this study, mainly by having a large number of samples and
detail level. Thus, the amount of information was increased enabling the
results to be completed with the highest degree of reliability. Another reason
for using these samples was because the percentages of some materials differ a
little in relation to data collected by Maccarini & Hernández (2007), which
were also used as historical data. These were called "Group 2" (Table
2).
For
more data and to make better comparisons with the existing, Maccarini (2008)
made a new characterization from the materials found on a trolley collector,
chosen at random, in the streets of Pato Branco city - PR. These materials were
fully separated and weighed, item by item, as shown in Table. Thus, the total
sum of the collected samples is 13, forming the three groups for being studied.
Table
1 data are about a single district of the city and in one day of the week
(Wednesday). Those raised in 2007 (Table 2) we extracted from a study by
Maccarini & Hernández (2007), in the shed of the Association of Scavengers.
There, the materials were mixed and homogenized. Finally, those identified in
Group 3 (Table 3) are about a day of the week (Thursday), without definition of
a place of origin.
Table
1: Detailed characterizations, from the collections made by collectors
MATERIALS |
QUANTITY (%) / collected days (group 1) |
||||||||||||
|
1st collects |
2nd collects |
3rd collects |
4th collects |
5th collects |
6th collects |
7th collects |
8th collects |
9th collects |
10th collects |
11th collects |
average% |
standard deviation |
Reject |
11,6 |
19,2 |
1,9 |
1,6 |
2,4 |
3,8 |
3,5 |
1,4 |
7,1 |
1,1 |
3,1 |
4,43 |
5,59 |
Newspaper |
6,4 |
5,3 |
32,1 |
2,9 |
6,2 |
12,6 |
6,0 |
4,5 |
8,8 |
4,8 |
3,4 |
10,66 |
8,29 |
White paper |
8,6 |
7,7 |
6,4 |
13,9 |
20,3 |
10,0 |
10,5 |
10,6 |
23,8 |
21,5 |
10,4 |
11,86 |
6,01 |
Cardboard |
24,0 |
31,9 |
11,6 |
13,1 |
24,2 |
19,8 |
13,4 |
17,5 |
18,9 |
21,4 |
18,8 |
17,80 |
5,88 |
Thin plastic |
5,4 |
4,2 |
2,3 |
3,8 |
6,8 |
4,0 |
2,9 |
5,0 |
3,2 |
4,6 |
3,8 |
3,89 |
1,25 |
Hard plastic |
12,3 |
12,4 |
5,8 |
5,8 |
9,7 |
6,7 |
4,9 |
5,8 |
6,9 |
7,4 |
5,0 |
7,04 |
2,73 |
PET |
0,0 |
0,0 |
0,0 |
6,3 |
8,2 |
5,8 |
3,8 |
4,9 |
7,2 |
7,5 |
5,7 |
4,00 |
3,13 |
Glass |
25,8 |
14,8 |
12,9 |
21,9 |
10,4 |
22,6 |
47,8 |
37,8 |
14,2 |
19,7 |
26,3 |
23,38 |
11,27 |
Ferrous metal |
3,3 |
3,8 |
7,1 |
24,6 |
8,6 |
8,7 |
3,7 |
6,5 |
4,6 |
6,3 |
10,1 |
8,75 |
5,97 |
Aluminum |
1,4 |
0,7 |
1,3 |
0,5 |
2,0 |
1,5 |
1,7 |
0,9 |
1,0 |
1,1 |
0,9 |
1,17 |
0,45 |
Copper and
related |
0,0 |
0,0 |
1,1 |
0,0 |
0,0 |
0,0 |
0,0 |
0,0 |
0,3 |
0,0 |
0,7 |
0,30 |
0,37 |
Other |
1,3 |
0,0 |
17,4 |
5,5 |
1,2 |
4,4 |
1,7 |
5,0 |
3,9 |
4,4 |
11,9 |
6,71 |
5,17 |
Source:
Maccarini (1998).
Table
2: Detailed characterization of selective materials, held in Association of
Collectors
MATERIAL |
AMOUNT
(%)/collection (group 2) |
Reject |
4,29 |
Newspaper |
10,11 |
White
paper |
12,35 |
Cardboard |
18,29 |
Thin
plastic |
3,75 |
Hard
plastic |
7,04 |
PET |
5,15 |
Glass |
22,48 |
Ferrous
metal |
8,31 |
Aluminum |
1,29 |
Copper
and related |
0,29 |
Other |
6,66 |
Source: Maccarini & Hernández (2007).
Table
3: Detailed characterization from material collected by a collector street,
chosen at random
MATERIAL |
AMOUNT (%) / collection (group 3) |
Reject |
3,69 |
Newspaper |
5,13 |
White paper |
13,98 |
Cardboard |
34,52 |
Thin plastic |
2,90 |
Hard plastic |
5,64 |
PET |
3,16 |
Glass |
16,87 |
Ferrous metal |
4,55 |
Aluminum |
0,74 |
Copper and
related |
0,17 |
Other |
8,63 |
Source: Data collected by the
author in January 2008.
The
analysis of the percentage of collection by type of waste is shown in Figure 3.
In this figure, the mean values appear with intervals LSD (Least Significant
Differences Intervals) with 95% confidence level, confirming the F test
significance performed in ANOVA (F = 4.24), which shows significant differences
(p= 0.0015 < 0.005) between some of the percentage of collection by type of
waste. Using a Levene´s test it was investigated the variance homogeneity which
p-value = 0.49, showing there is not a statistically difference amongst the
variances at the 95% confidence level.
The
Table 4 shows the multiple comparisons to determine what type of waste has
similar percentages, which do not differ significantly at a level of
significance of 5%. The method used was the procedure of Least Significant
Difference (LSD) of Fischer. The residues, that are in the same group, appear
with an "X" in the same column. According the Table 4, may be checked
the division of the waste in five groups. Table 5 presents new groupings
performed, in order to achieve the mean percentage of each new group,
multiplied by the sales per tonne value.
Sum of squares
Degree freedom F-ratio p-value Between the groups 1293.1 11 4.24 0.0015 (<0.005) Within the groups 664.9 24
Figure 3:
Results of ANOVA and means plot for all analysed recyclables
Table
4: Multiple comparison multiple to determine the affinity between the materials
|
Portion (%) |
Group |
||||
|
|
1 |
2 |
3 |
4 |
5 |
Copper and
related |
0,25 |
X |
|
|
|
|
Aluminum |
1,19 |
X |
X |
|
|
|
Other |
4,60 |
X |
X |
X |
|
|
PET |
5,17 |
X |
X |
X |
|
|
Ferrous metal |
5,51 |
X |
X |
X |
|
|
Thin plastic |
5,54 |
X |
X |
X |
|
|
Reject |
8,47 |
X |
X |
X |
X |
|
Hard plastic |
8,59 |
X |
X |
X |
X |
|
Newspaper |
9,97 |
|
|
X |
X |
|
White paper |
12,93 |
|
|
X |
X |
|
Glass |
15,14 |
|
|
|
X |
X |
Cardboard |
22,65 |
|
|
|
|
X |
Table 5: Analysis and groups formation, without
repeating the type of waste
Materials |
Portion
(%) |
Total
clusters (%) |
Arithmetic
mean of clusters (%) |
Value of sales per tonne (R$) |
Amount
due to trade |
||||
Copper and
related |
0,25 |
1,44 |
0,72 |
7.000,00 |
R$ 50,41 |
|
|||
Aluminum |
1,19 |
|
|
2.000,00 |
R$ 14,40 |
|
|||
Other |
4,60 |
47,85 |
7,60 |
no set value |
R$ 0,00 |
|
|||
PET |
5,17 |
|
|
360,00 |
R$ 24,61 |
|
|||
Ferrous metal |
5,51 |
200,00 |
R$ 13,67 |
|
|||||
Thin plastic |
5,54 |
200,00 |
R$ 13,67 |
|
|||||
Reject |
8,47 |
no set value |
R$ 0,00 |
|
|||||
Hard plastic |
8,59 |
260,00 |
R$ 17,77 |
|
|||||
Newspaper |
9,97 |
50,00 |
R$ 3,42 |
|
|||||
White paper |
12,93 |
28,07 |
18,89 |
400,00 |
R$ 56,13 |
|
|||
Glass |
15,14 |
|
|
200,00 |
R$ 28,07 |
|
|||
Cardboard |
22,65 |
22,65 |
22,65 |
180,00 |
R$ 40,77 |
|
|||
|
|
|
Total amount due to the sale of
materials |
R$ 262,92 |
|
||||
From this survey, the new groups to
be formed are:
·
First group: copper and similar with aluminium;
·
Second group: PET, ferrous metal wastes, hard plastic,
thin plastic, newspaper and others;
·
Third group: paper and glass;
·
Fourth group: cardboard (which got an own group).
For
illustrative purposes, the result of materials commercialization per tonne,
with previous separation and use of arithmetic average, was R$ 234.36. Using
analysis of variance - ANOVA the result was R$ 262.92, similar to the first,
which is the real result. In other words, by the mean collection in a ton, the
scavenger, using the proposed method, would commercialize the materials with
12.1% mean difference value between the proposed (ANOVA) and the usual sales,
in other words, from actual average (samples), with sorting and weighing each
item.
Below
are listed some advantages from implementation of bulk weighing method, namely:
(i) Due to the time saving in not having to wait to separate the materials, the
collectors can return to the section to carry out new collections, (ii) Since
the warehouse would be strategically located near the collection site, the
travel time would be reduced, because the
pickers would not need to move long distances to sell the materials, (iii) If
they organize themselves in cooperatives, the values in materials
commercialization may be higher, due to wholesale, (iv) If there are values
leftovers of trade due to errors in the estimates, these may be divided between
them at the end of each month.
The
study is an initial step for the process optimization and recyclable materials
receipt from the bulk weighing. This resulted in the streamlining of materials
weighing, and commercialization by scavengers, in other words, is a more
efficient and faster way than conventional methods.
ANOVA
test (F-ratio = 4.24, p-value = 0.0015) shows the materials that have more
differences in the quantities are the cardboard and glass. This means the
scavenger could deliver all materials mixed, with the exception of cardboard
and glass, then to be weighed and sold without significant losses for both
scavenger and receiver.
On
the other hand, as recommended by the results of the ANOVA, the recyclable
materials should be regrouped into five groups. So can be commercialized in a
homogeneous way between each group. This procedure would greatly facilitate the
process as a whole because it would not be necessary to separate item by item.
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