I am done. I am unsubscribing from everything. Alright, I'm gonna try to make this one short and sweet. I believe that preferences reflect both our choices in our behavior. Your choice to watch a particular TV show or Netflix series or read a specific book or YouTube video will probably change your behavior in a particular way. Either you're talking about big changes or nano changes, small changes. The way you see the world is going to be different with each piece of content you're adding in on a daily basis. And this is a good thing. This is how you evolve. This is how you improve. But sometimes this can make it really hard for you to discover who you really are without these influences, without these daily inputs. Now you understand that who you are is a complex mix of micro inputs. And we start receiving these inputs today. We are born and then he's only stopped theoretically only when we die. We are constantly allowing in the world and we are also absorbing the world in the same time. As an example, let's say you see a small wounded bird on a grass and your decision to intervene or not, well, change who you are would change a tiny fraction of you. And I believe that in the same fashion this happens in the digital world as well. Your Netflix feed can tell me a lot about yourself. It is not a rule, but it can help. And I remember reading this article in 2018 and there was a statement about Netflix having 30 plus million versions, as each feed is inherently different. If I'm watching comedy TV shows during the weekend and crime TV shows during the week, why Netflix feed will essentially be a mix between comedy and crime? And of course, it's not that simple because you have various kinds of comedy and various kinds of crime. And if you say add in some drama, you can change everything and your preferences and my preferences will get on the record and we will get recommendations based on our initial choice. And these of course will morph and will evolve into something else as we diversify our palette. So here's my idea. I do spend quite some time in the digital space and I believe that we all do. And I'm going very basic here. If you have a phone, you are in a digital space as well. If your phone has internet connection, that's even worse. And of course I'm kidding. But what I'm trying to say is that we are all in the same pit and I do appreciate the company. And what I'm trying right now is a digital reset. And no, this is not a digital detox. I'm not ditching the internet. I'm just resetting it. I view this as a sort of a digital clean slate. And although I'm not gonna be 100% accurate in doing this, what I want to do, I want to tackle the main sources of input that I find destructive and also sort of intervene and get in the way of knowing and learning who am I. So my aim is to have a fresh email inbox, fresh YouTube feed and also a fresh Netflix feed. Although I haven't been watching that much Netflix lately, but I want to see how that goes as well. So hopefully I'm gonna have a clean browsing history note, targeted recommendations coming to my feet. And in theory, I will be free to choose whatever I want to choose to consume in theory. And I know that I'm still going to have to face the stuff that's trending and beat tech is going to try to shove that in my face. And that if you want to go philosophical on this one, you can start asking questions like are we really free? But if you go on this path, the discussion is not going to end. So I chose to do what I can do with what I have where I am. And I still think that this is going to be a cool exercise. And I also think that this is going to be different for everyone. And it's just like highly dependent on the stuff you already have embedded in yourself. So once you have to face a fresh feed and you won't want to click on anything, you will probably start searching for something you already know interests you. And then it can be about reflecting whether or not you are really interested in that particular topic. And by the way, this type of reset can work in your personal life as well. But that is the topic for another video. Thank you for watching and I'll see you in the next one.


Everybody Forrest here ripping four boxes of 2022 Bowman Chrome Baseball Choice Scott F Appreciate you Scott. Good luck, man Low numbers. Come on low numbers red superfactor black Orange gold I don't even I don't even want to know about that shady. I don't even want to know about that. I Truly do not want to know about that Got a purple first Bowman auto Greg Cullen 58 of 250 What's up Lane First woman base auto yasir Mercedes nice hit there Nice yasir Mercedes and on the back of the first box here is a base auto jet JT Schwartz We were talking about Antonio Brown earlier. That's also another person that needs help is first. We're talking about First woman refractor auto Ryan Reckley 14 out of 499 Yeah, Lane it is true. It's for sure true first woman base auto Rosamund Verdugo Padres Crazy how the Patriots can be great with such a great offensive coordinator though and Matt Patricia And base auto Cal Conley Lane's crazy like that Lane's like Batman Lane's Batman actually Purple first Bowman auto Ricardo Cabrera 64 out of 250 That's an awesome hit There we go Scott Congrats on that. I Think that's an ink smear on the left over here. It's like that Really light blue tint there Awesome hit though great prospect and a base auto now Christian Vecchero Fantastic third box There we go That's what we love to see And who's some gold now gold shimmer first-moment auto Greg Cullen 34 out of 50 That's a great box. All right one more Scott first-moment refractor auto nor have Hera 54 out of 499 first-moment auto Alexander Suarez and Last one is a first-moment auto for Benjamin Cowles Benjamin Cowles Thank you again. Scott Congrats on some of those nicer hits. We appreciate it. We'll get those right out to you


The symphony of dawn stirs the consciousness, and as the world awakens, so too does a new, profound insight into life's vast tapestry. Waking up to a deeper understanding of life is not merely an intellectual realization but an immersive experience that resonates within every fiber of our being. It is akin to seeing a familiar landscape with new eyes, feeling the rush of emotions that were once suppressed, or hearing the whispers of a song that once seemed silent. 1. The layers of reality. Life, at first glance, appears linear. We are born, we age, we endure, we celebrate, and eventually, we fade. Yet, beneath the seemingly straightforward trajectory, there are layers upon layers of deeper meaning. As one begins to kill back these layers, it becomes clear that life is not merely a series of events but an interconnected love of relationships, experiences, and moments of realization. 2. Embracing impermanence. One of the most profound insights that comes from diving deep into the essence of existence is the acknowledgement of impermanence. Everything, from the mightiest mountains to the fleeting thoughts that cross our minds, is in a state of constant change. Recognizing this, we can find a certain liberation in letting go, appreciating moments as they are, and not clinging to a femoral joys or sorrows. 3. The interconnectedness of all things. As the famous adage from the east goes, this is because that is. Nothing exists in isolation. The very air we breathe, the food we eat, and the thoughts we think are all results of countless factors coming together. This intricate dance of causality invites us to see our place in the world, not as mere individuals, but as part of an interconnected whole. 4. The power of now. Past regrets and anxieties about the future can shackle us, preventing us from truly experiencing life. Waking up to the present moment, fully immersing oneself in the now, can be a transformative experience. The present is all there truly is, and within it lies infinite potential. 5. Unvailing purpose and meaning. A deeper understanding of life often brings with it a search for purpose. While life might not come with a manual, within its depths, each individual can carve out a purpose, a meaning that resonates with their core. It might not be grand or world-changing, but it is significant nonetheless. 6. Rediscovering wonder. In our quest for understanding, it's easy to lose the childlike wonder that makes life magical. However, the deeper we go, the more we realize that understanding doesn't mean you miss to find everything. There's beauty in mystery, and there's wonder in both knowing and not knowing. 5. Inclusion. To wake up to a deeper understanding of life is to embrace a journey of continual discovery. It's about merging the inner world with the outer, the heart with the mind, and the soul with the universe. It's an invitation to explore, to question, to marvel, and above all, to live with an awakened heart. From those tentative first steps out of the shadow of fear to the exhilarating embrace of fearlessness, we walk this path together, hand in hand. Join our thriving community and be part of this transformative journey. Together, we're not just facing our fears, we're transcending them. Hit that subscribe button right now and take your place in our community dedicated to growth, support, and ultimate fearlessness. The road from fear to fearlessness begins with a single step. Take that step with us today.


Hi, I'm Zor. Welcome to Nezor Education. I think whatever I'm going to discuss today, basically you should know this from the theory of probabilities course which obviously supposed to be completed before we go to statistics. Still, I am within this foundation of statistics theme and I believe it's quite appropriate to talk about averages as main tool in statistics. Well, this lecture is presented on Unizor.com as part of the course advanced mathematics for high school students. I do suggest you to actually view this from this website rather than from the YouTube or anywhere else because the site contains functionality, it contains notes for every lecture which basically can serve as a textbook. So, I do suggest you to go directly to this website and go to statistics and this is the foundations of statistics part and we're talking about statistical averages here. So, as I was saying, statistical averages are very important tool of statistics and basically in this very short presentation I would like to again remind you why this is the case. Now, I'm saying again because this is actually a repetition of the knowledge which you have from theory of probabilities. Alright, so, what are we talking about? Let's say we have some random variable XE which distribution we don't know and the purpose of statistics is based on some observations of this particular values of this random variable make some judgment about its distribution. Okay, now, what are the main characteristics of distribution? Well, traditionally, people are very much concerned with the mean value, the mathematical expectation of this random variable XE and its variance. Now, variance is basically a measure of how wide the values of this random variable are spread around its mean value. Well, it's not always true because, for instance, if you have a Bernoulli random variable which takes values only 0 and 1 with some probabilities p and 1 minus p, well, then let's just make it even simpler. Let's say it's 1 half and 1 half. Then the mean value will be 1 half. But this Bernoulli's random variable will never take the value of 1 half. But it's not always correct to say that the values of random variable are concentrated around its mean value and the variance basically describes how tightly it is concentrated around mean value. In this case, it's not true, basically. But these are rare cases. In much more often occurring cases in real statistics, situation is really like I was just saying that there is some mean value and the values of the random variable are concentrated around this mean value and the variance is the degree of this concentration. If the variance is very big, then it's spread around wider. If the variance is very small, then the values are concentrated closer to the mean. And this is very important because let's consider you have a very wide variance. And then you have one single value of this random variable. Does it tell you anything about what is the mean value, where the values are supposed to be concentrated around? Well, in case of a very big variance, this is not really a valid point. You cannot say that the value which you have obtained, observing the random variable, signifies anything about the value of the mean of this random variable. However, if it's really concentrated around this mean, if the variance is small, then it does make sense to take any particular value which you have observed as some kind of a reasonable evaluation of the mean value. So again, the values which you observe are supposed to signify something about the mean value. And the variance of the values which you have observed, let's call it a sample variance, signifies how close your evaluation actually is. Now, with this, some kind of introduction, let's talk about a very concrete example. So you have a random variable, the distribution of which you do not know, but you are interested to know the mean value and the variance, or not the real values, but at least the approximation of these values. So how can that be arranged? Well, obviously you conduct experiments and you have some values. You have n experiments and you have n values of this random variable. Well, if you just look at these variables, at these values and do nothing, it might actually tell you something about the very, I would say, not very precise, let's put it this way, not very precise evaluation of the value of the mean value and the variance of this particular random variable. You really need to do some calculations to do it more mathematically, so to speak. So I'm going to introduce you to these calculations, which are very simple, and then we will spend some time discussing why this particular calculation is very important. So obviously we all know that the best way to approximate the mean value of this random variable, c, if you have n of its observed value, is a arithmetic average of these values. Let's call it x with a bar on the top. And the statement which people usually do is, okay, the average of these values is this and that signifies basically relatively precisely or whatever the measurement of this precision is, that this probably would be very close to the mean value of c. Well, question is why? And that's what I'm going to discuss right now. Now, instead of considering n experiments with one random variable c, let's consider that these experiments are independent from each other, and this is a reasonable assumption. And also let's consider that conditions of the experiment are not changing. So these x1, x2, xn are actually values of certain random variables, c1, c2, et cetera, cn, which are independent of each other, and because conditions of the experiment are exactly the same, the distribution of these is exactly the same as this one. So the distribution of these, which means all the characteristics of distribution, in particular, you can talk about mean value, you can variance, et cetera. So each one of these random variables is exact copy of c, and they are independent of each other. So what do we have? We have x1 as one particular value of c1. x2 is a particular value of c2, and xn is a particular value of cn. Now, what is this? Well, let's make another random variable c with a bar on the top, which is average of all these and random variables. So I can actually say that this is one single value of this random variable. Right? Right. Now, why is it better to consider one value, this one, of this random variable rather than an independent value of this variable? Here is why. Let's just examine this particular random variable, xc with a bar, the average of xc. So first of all, let's talk about its mathematical expectation. Let me just call it eta, so I don't have all these bars, numbers, et cetera. Okay? Now, what is this? Well, back to theory of probabilities, we know that mathematical expectation of sum of random variables equals to sum of their mathematical expectations. So basically this is, and obviously the factor can be extracted out, so it will be 1 over n, and I will have expectation of c1, et cetera, plus expectation of cn. Okay? Now, as I was saying before, c1, c2, cn are exact copy of c. They are independent random variables, but their distribution is exactly the same, which means their mean values is exactly the same as the mean value of c. So that's equal to 1 over n, and here I have n expectations of c, right? Which means expectation of c. So what's important is that mathematical expectation of the average of these n independent and identically distributed random variables, c1, cn, is exactly the same as the expectation of our original random variable. Well, this is good. Now, question is, is this single value which we have obtained observing this particular random variable, is it close to my mean value? So this is basically described by the variance, but here is the most important difference between c and n. Let's say sigma square is variance of c. What is variance of eta? Well, again, since we know from the series of probabilities that the variance of a sum of independent, now here is important property of independence. That's where it's playing, actually. In mathematical expectation it was not important, but with variance it is important. So sum of independent random variables, the variance of this sum is equal to sum of the variances. And if you remember, variance is basically the average of deviation of the mean squared, which means that this number n can be brought out in square. And here I have sum of variances, variance c1, plus, etc., plus variance of cn. Equals to, they are all independent and identically distributed as c, which means their variance is exactly the same as c, which means it's n times sigma squared divided by n squared, which means sigma squared divided by n. And this is the most important property of the averaging. The variance of the average of n independent identically distributed random variables is n times smaller than the variance of the original random variable. Now, what does it mean? Well, it means that this value is much closer to the mean value of eta than any of these guys to the mean value of this, which is the same as mean value of eta, which is whatever I call mu. Which means this is a better evaluation, a better estimate of the mean value of eta, which is exactly the same as mean value of this, than each one of these guys. And that's the reason why we are using this averaging. If you have n observations and you average them out, then the resulting average will be much closer evaluation of the mean value than any of these considered separately. Yeah, that's why average plays such an important role. Now, what also is important is that as n is increasing, my variance is decreasing, which means the values are tighter and tighter concentrated around my mean value. That's number one. The second very important reason, which is much less trivial, is that I was talking about so-called central limit theorem in the theory of probability scores. Now, it basically says that the sum of random variables in some way resembles the normal distribution. And the more components you have in this sum, the closer the distribution of the sum is to a normal distribution. So, I can actually consider the variable eta to be almost normally distributed. And normally distributed random variable, you remember this bell curve, right? This is mathematical expectation. And if you have a square root of the variance, in this case, it's sigma divided by square root of n. Then something like minus 2... it's mu minus 2 sigma divided by square root of n. And this would be mu plus 2 sigma divided by square root of n, right? So, this is double 2 sigma divided by square root of n. It's double standard deviation. Now, we know that the probability to be here, to be around the mean value mu, is something like 95% approximately. So, right now, what I can say that knowing this gap and knowing, again, approximately, because I cannot really know it exactly, I know approximately, and I also know approximately mu, which is this one, I can say that the concentration of all the values of this random variable are within our approximation of mu minus whatever approximation of my standard deviation, or plus with a certain two-level of 95%. So, now we are actually getting something very tangible. We can calculate this one and the greater n is, as we know, the tighter this value is to the mathematical expectation of sigma. It's a much better evaluation of my mu in this case. The greater the n is. Also, using these values, x1, etc., xn, I can always evaluate my sigma by basically using something which is called a sample variance. Now, sample variance is a mathematical expectation of square of deviation of the random variable from its mean. Now, I don't have random variable. I have n of its values. I don't have mean. I have an estimation of mean, but I can still make the same calculations, which means x1 minus x2 plus, etc., plus xn minus average value divided by n. So, this is my average square deviation of the values from average value. So, these are not old values my random variable takes. And this is not exactly my mean value for this. However, it's a good estimate. And in some other lecture, I would provide basically some calculations how good this estimate is. But it's an estimate, which you can use instead of sigma square. Now, this you can use instead of mu. So, you have basically all components. And that's what allows you to evaluate what exactly the distribution of... See, maybe not the entire distribution, but at least its mean and variance are. And where we can expect the values of this random variable to be. All right. So, basically that's it. I just wanted to make some, I would say, statistical foundation of using averages before going into any more detailed statistical researches, et cetera. Average, again, my point is that the averages in statistics play extremely important role. And I was just trying to give you the foundation why. The reason why they're playing such an important role. This is basically why. Everything is concentrated here. And this end in denominator. That the more data you have, the more precisely you can evaluate your mean value of this guy. All right. That's it for today. Thank you very much and good luck.


My presents are going to deal with what I regard to be the contribution, y f Hero ddod that you may not regard it as such a sensory archaeology to central Mediterranean prehistory. My aim in this presentation is certainly to challenge but also to encourage central Mediterranean prehistory Sut yw'r gweithio'r dweud ddiogelol o'r gweld o'i hyfforddol? Rwy'n gweithio'r ddiogelol o'r ddiogelol o'r ddiogelol, os yw'n gweithio'r ddiogelol o'r ddiogelol o'r ddiogelol o'r ddiogelol ar hyn o'r pethau mynedd, o'r medytrowniol yn y pryd o'r hefyd, ac mae'r ddweud i'r holl yn rhanio'r ddiogelol o'i effaith yn ei ddysgu'r ddiogelol o'r ddiogelol. Y ddiogelol o'r ddiogelol, Be gydrodd ar sefylliant cwy changing ac eich argynwys yn eich debyg a'r ddarparu hefyd, y hall gyrfa ddeicol, lle ddweud a'r ddaw i'w ddweud i ddweud eich ddweud a'r ddweud ac eich graif am y cael iechyd, eich wrth gwrs, ein dweud, ac yn ddiwych gan ganddochau hwn, yn..] rhai cymdeithasg yn y cyfnodwch yn eich gyrwch. Second, in sensory studies we can foreground the senses, both as an object of study and as a means of study, so we can study through our senses as well. Thirdly, sensory studies have an emphasis on the socio-cultural formation of the senses we shouldn't take for granted in others. So, turning to sensory archaeology, this may seem risky and experimental. Certainly the difficulties of sensory studies can't be underestimated. However, hope is offered by an increasingly explicit range of research methods now being brought into the service of sensory archaeology. These include critique of previous academic traditions and studies that have denied the senses, as they were in a lot of history of multisarchaeology, which is primarily visual. Reflexivity, reflecting upon our own practices. Incorporation of thinking about sensoriality into existing research methods so we don't have to throw the baby out with the bathwater. Ethnographic insights and analogies. Direct bodily experience. You go into those rocket tombs with your body, pushing with your feet sometimes, your hands. Experimentation and reconstruction. Imagination and artistic creativity. Do you dare? Do you dare even aim to evoke possible past sensory experiences rather than I suggest? We don't need to produce exact reproductions of past sensory experience, but to evoke. Finally, empathy. Do you have any empathy with the people who you are studying? For example, do you relate your own experiences of death and loss to archaeologists of death and burial? From the perspective of sensory studies, a basic distinction might be drawn between two different representations of life in the central Mediterranean region. For archaeologists, there's a long established scholarly tradition of primarily visual engagement with Mediterranean prehistory. A way of seeing characterised by a central concern with many of the themes we've heard today. Narratives about the sea and early boats and sailors, navigation shipwrecks and so on, island colonisation, the list goes on as it's there. This way of seeing can be contrasted, certainly in the contemporary world, to people's more full-bodied experiences of the Mediterranean today.  Summer sun and romantic sunsets, luxury yachts and all the rest of it, but also of course wildfires, violent political conflicts and boatloads of desperate migrants. The gap between these ways of seeing and ways of sensing should encourage us, I would argue, to produce new embodied narratives of the human past. So, I now want to take stock of current thinking on sensory central Mediterranean prehistory by looking at a series of overlapping themes that extend across a variety of scales. Actually, the themes we've been talking about this morning and a few more thrown in as well. So, to start with, let's say, landscapes and seascapes and their perception and experience, sensory approaches have contributed to landscape archaeology through their consideration of people's perceptions and experiences of central Mediterranean landscapes. For example, Matthew Fitzjom has questioned the visual bias inherent in GIS applications used to examine the perception of space in Mediterranean landscape archaeology, emphasising instead the importance of memories of the past and experiences of the everyday and making sense of landscapes and places in the mountains of Sicily. Partly informed by critiques like this, a number of studies have also focused on the phenomenological or experiential dimensions of central Mediterranean landscapes. For example, in thinking about the early Neolithic maritime colonisation of the Maltese islands we've been hearing about by small groups of farmers in southern Sicily, I've considered not only the logistical aspects of their sea crossings, but I've also imagined the intense multi-sensory experience of voyagers, especially in terms of the techniques of the body that it took and upon which their lives depended to actually get to the Maltese islands. A third example is provided by Sue Hamilton, Mike Seager Thomas and Ruth Whitehouse, who have characterised different sensory environments and experiences around Grotta Scalloria, the Neolithic ritual cave in southeast Italy. They have contrasted journeying through open ground on the Tavoliere plain and then through wooded ground on the lower slopes of the Gargano uplands through the confined area of the Swallow Hall and then in through the dark, cramped and humid cave interior. Dwelling is another theme. We haven't touched upon it so much, but let's talk about settlements there. Sensory archaeology has also begun to contribute to studies of settlement forms and processes in central Mediterranean prehistory by considering past embodied experience of dwelling in these physical and social environments. For example, again, Sue Hamilton and Ruth Whitehouse have undertaken phenomenological experiments in and around the Neolithic ditch settlements on the Tavoliere plain in southeast Italy, which have revealed that the distances over which it would have been possible for their inhabitants to register sounds and vision across them would have varied according to the size and landscape setting of the site. I've also considered how people ordered and experienced dwelling places in prehistoric mortar trying to compare and contrast what it might have felt like for different members of society to dwell within the walled villages and how the walled enclosures and houses on the one hand of Neolithic Scalloria and on the other hand of Bronze Age Borgin Nadur, trying to breathe, therefore, into these old plans and sequences of structures excavated these sites, trying to breathe into those new life and new understandings. Turning to rituals, the archaeology of ritual in the central Mediterranean region has defined very ritual practices and performances at particular places and times and discussed their social implications. Experiential and sensory perspectives have successfully taken this thinking one step further, focusing on some distinct architectural spaces. Underground sites tend to be relatively well preserved and therefore offer good opportunities to consider in the present as well as past experiences of their space and materiality. For example, Ruth again has characterised Neolithic cult caves such as Grotta di Porta Badesco and Grotta Scalloria as relatively inaccessible, spatially zoned, cool, humid and dark, resonant environments elaborated with cast formations and symbolic installations that lent them an awe-inspiring sense of otherness and liminality. Features that were exploited by ritual leaders to have a discomforting and highly emotional impact on younger male initiates made to move through these spaces to acquire successive levels of secret religious knowledge. For my own part, I've built on this kind of thinking in my Seulu caves project in Sardinia where, for example, I've examined how particular effects of light and of darkness in ritual caves might have been actively used and experienced by later prehistoric people. Above ground as well, in prehistoric monumental buildings in the region, we're turning from what these monuments might have looked like to what they might have felt like, particularly through theatrical performances, for example, through the Maltese so-called temples. Turning to food and drink and other substances, sensory studies are now taking archaeological thinking about the social significance of food and drink one step further by emphasising people's ability to exploit the powerful sensory dimensions of consumption. For example, John Robb has touched on the social significance of the colour-flavour world of Neolithic cuisine in Italy, contrasting green-gathered vegetables and fruits, brown-cooked meat and grains, and red-wark and cooked meat. The archaeology of death and burial is becoming ever more sophisticated, as you know, and sensory archaeology has a part to play here in raising our awareness of the sensorially and emotionally charged encounters between the bodies of the living and the dead, particularly during mortuary rituals. This is expressed well by Caroline Malone and Simon Starrart in their thick descriptions of the funerary procession in the Shara circular towards the end of their excavation reports, their excavation volume. Turning to materials, cultural materials that we've heard a lot about this morning, artefact studies, of course, occupy a central place in central Mediterranean prehistoric archaeology. Sensory studies have a part to play here, combined with detailed materials science analyses, by looking at the multi-sensory properties of these cultural materials. I say that visual culture studies are a step in the right direction with the highlighting of the attractive appearance of special materials. So, for example, John Robb and others have described blood red ochre, translucent black obsidian, and so on. But these descriptions still prioritise visual experiences. So, going one step further, a few central Mediterranean prehistorians have begun to write more sensitively about the materiality, production and consumption of later prehistoric artefacts. For example, Susanna Harris reminds us of the multi-sensory dimensions of the alpine of iceman's clothing. It's now widely accepted that miniature prehistoric figurines would require interpretation in terms of themes such as materiality, manufacture and so on. And it's recognised that they can appeal to the senses, particularly of sight and touch, and that they were subject to manipulation in performative context. So, Isabella Gregory and Caroline Malone, for example, have reconsidered the large corpus of multi-use temple culture figurines in terms of their aesthetics and their related sensory dimensions. So then, here's my argument. What then do sensory approaches bring to our studies? I want to argue that they highlight biases and limitations and gaps in traditional archaeological methods, including interpretations the way we write and illustrate as well. I think they bring together an extent recent thinking, archaeological thinking about the body, phenomenology, memory, emotion and the senses. They encourage us to produce new full-bodied narratives of past people, people who actually we've only had implied this morning rather than referred to directly in so many of our presentations. People and their material remains, and they direct us to play closer attention to the sensory properties, practices, experiences and perceptions inherent in a range of archaeologically visible human behaviours. So for later prehistory, where I mainly work in the central Mediterranean region, these approaches reveal people participating in everyday and seasonal routines of dwelling and mobility interspersed by rituals performed at special places and times, involving a multitude of embodied practices and sensuous materials. This anthropological perspective is complemented by a uniquely archaeological one in which local dynamics and long-term transformations can be identified, provoked by different categories of people redefining themselves cooperatively and competitively across competing sensory domains. For central to conclude then, for central Mediterranean prehistory, there remains plenty of scope to put into practice new sensory studies. An undertaking who's apparently risky and experimental nature is mitigated by incorporating sensoriality into the full range of existing archaeological methods that we already use. I encourage you then to take up this challenge and in the process enrich our understandings of what it felt like to live in the prehistoric societies of the central Mediterranean. Thank you.