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Peer support occurs when people provide knowledge, experience, emotional, social or practical help to each other. It commonly refers to an initiative consisting of trained supporters (although it can be provided by peers without training), and can take a number of forms such as peer mentoring, reflective listening (reflecting content and/or feelings), or counseling. Peer support is also used to refer to initiatives where colleagues, members of self-help organizations and others meet, in person or online, as equals to give each other connection and support on a reciprocal basis. Peer support is distinct from other forms of social support in that the source of support is a peer, a person who is similar in fundamental ways to the recipient of the support; their relationship is one of equality. A peer is in a position to offer support by virtue of relevant experience: he or she has "been there, done that" and can relate to others who are now in a similar situation. Trained peer support workers such as peer support specialists and peer counselors receive special training and are required to obtain Continuing Education Units, like clinical staff. Some other trained peer support workers may also be law-enforcement personnel and firefighters as well as emergency medical responders The social peer support also offers an online system of distributed expertise, interactivity, social distance and control, which may promote disclosure of personal problems (Paterson, Brewer, & Leeseberg, 2013). Peer support has been shown to be effective in substance use and related behaviour, treatment engagement, and ameliorating risk behaviours associated with HIV and hepatitis C, and empowering people with mental illness and improving their quality of life. Its effectiveness is believed to derive from a variety of psychosocial processes first described by Mark Salzer and colleagues in 2002: social support, experiential knowledge, social learning theory, social comparison theory, the helper-therapy principle, and self-determination theory.
[2]Paolo Prandoni, [3]LCAV, EPFL
In [1]:
import matplotlib.pyplot as plt
import numpy as np
import scipy.signal as sp
import seaborn as sns
sns.set()
In [2]:
plt.rcParams["figure.figsize"] = (14,4)
The basic reproduction number[4]¶
The propagation mechanism of an epidemic such as the one caused by
SARS-CoV-2 virus can be roughly modeled, at least in its inital phase,
as a process in which each infected individ [2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will design and use filters to extract specific
audio frequencies from a music file.
In [1]:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import IPython
import scipy.signal as sp
from scipy.io import wavfile
infringment...)
In [2]:
IPython.display.Audio(s, rate=SF)
Out[2]:
Your browser does not support the audio element.
[2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will investigate the effect of phase on the
perceptual quality of a sound. It is often said that the human ear is
commercial-grade audio equipment takes place in the magnitude domain
only.
In [1]:
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import IPython
from scipy.io import wavfile
In [2]:
plt.rcParams["figure.fig [2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will use the adaptive LMS filter to estimate the
impulse response of a reverberating room.
A typical use case is handsfree telephony: since the received signal,
amplified and played by the speaker, is picked up by the microphone, we
need to eliminate it from the signal that is transmitted back in order
to avoid a feedback loop. The signal picked up by the microph [2]Paolo Prandoni, [3]LCAV, EPFL
The Karplus-Strong algorithm is a simple method to generate synthetic
sounds with arbitrary pitch. In this notebook we will explore a few
variations of the method to illustrate some basic notions of
discrete-time signal processing.
In [1]:
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import IPython
In [2]:
plt.rcParams["figure.figsize"]