[Drömseminarium

Fyra miljarder människor på jorden. Och alla sover, alla drömmer. I varje dröm trängs ansikten och kroppar— de drömda människorna är fler än vi. Men de tar ingen plats. . . Det händer att du somnar på teatern. Mitt under pjäsen sjunker ögonlocken. En kort stunds dubbelexponering: scenen där framme överflyglas av en dröm. Sen finns det ingen scen mer, den är du. Teatern i det ärliga djupet!

5 Translated by Robin Fulton in Tomas Tranströmer (2002): *New Collected poems*, pp. 141–42.

Mysteriet med den överansträngde teaterdirektören! De ständiga nyinstuderingarna. . . Ett sovrum. Det är natt. Den mörka himlen flyter genom rummet. Den bok som någon somnade ifrån är fortfarande uppslagen och ligger skadskjuten på sängkanten. Den sovandes ögon rör sig, de följer den bokstavslösa texten i en annan bok— illuminerad, ålderdomlig, snabb. En hisnande commedia som präntas innanför ögonlockens klostermurar. Ett enda exemplar. Det finns just nu! I morgon är alltsammans utstruket. Mysteriet med det stora slöseriet! Utplåningen. . . Som när turisten hejdas av misstänksamma män i uniform— de öppnar kameran, ruller ut hans film och låter solen döda bilderna: så mörkläggs drömmarna av dagens ljus. Utplånat eller bara osynligt? Det finns ett utom—synhåll—drömmande som alltid pågår. Ljus för andra ögon. En zon där krypande tankar lär sig gå. Ansikten och gestalter omgrupperas. Vi rör oss på en gata, bland människor i solgasset. Men lika många eller fler som vi inte ser finns inne i de mörka byggnader som reser sig på båda sidorna. Ibland går någon av dem fram till fönstret ochkastarenblicknerpåoss.]

The title "Drömseminarium" is informative of the mode of the poem. It tells us that the poem relates to a scientific discourse, and the poem also develops as a third-sided composition whose *exordium* (ll. 1–5), *exemplum* (ll. 6–34) and *peroratio* (ll. 35–46) evoke associations of a scientific statement or lecture. However, if at first glance the poem seems to relate to a scientific discourse, a closer inspection reveals a different picture. Not only are there actually far more fluid boundaries between the parts of the text than indicated by the above classification; a number of elements even undermine a common scientific perspective.

Already at the end of the first part of the poem, a discrepancy becomes clear between that which is scientifically demonstrable and measurable on the one hand, and the more fleeting and metaphysical nature of the dream on the other. This discrepancy reflects that although there are more people in dreams than in reality, they do not occupy space. The significance of the dream cannot be measured using the external standards of the world. Therefore, the examples used in the attempt to capture the essence of the dream also dissociate from a scientific area and relate to art; the theater and the book constitute the starting points of the description of the dream. Art—especially in its modern forms—represents a break with reality; art creates a world of its own, and so do dreams.

In the first example (ll. 6–13), a double exposure is described. While something is happening on a theater stage, for a moment the spectator falls asleep and is carried to another stage. The outer and inner dramas merge, and a new scene takes over: "The theater in the honest depths!" [Teatern i det ärliga djupet!] (l. 11). In the second example (ll. 14–28), the focus is on the difference between an open book in a dark bedroom and the illuminated comedy taking place behind closed eyelids. The latter dichotomy then leads to what we may either call a third example or consider an appendix to the second (ll. 29–34). Again, the dream is compared to a medium of an artistic character, namely the photograph. The example focuses on a situation in which a camera is opened, and the pictures are wiped out by the light. This is compared to what happens to dreams as night changes into day: "så mörkläggs drömmarna av dagens ljus" [so dreams are darkened by the light of the day] (l. 33).

While the example of the theatre related to the evening, and the second example focused on a nightly room, in the third example we move on into the day. The examples thus allude to a traditional time-period of sleep. However, while the first two descriptions end in an almost dethroning summary of the experiences in these remarks: "The mystery of the overworked director!" [Mysteriet med den överansträngde/teaterdirektören!] (ll. 12–13) and "The mystery of great waste!]" [Mysteriet med det stora slöseriet!] (l. 28), the third example remains more open. In the latter no attempt is made at a final averting fictionalization. Instead the question arises: "Annihilated or just invisible?" [Utplånat eller bara osynligt?] (l. 34). The mode of questioning in itself is essentially open, and likewise, the poem proceeds to invite another and more abstract way of reflecting the significance of the dream. The last part of the poem (ll. 35–46) does not address the dream as we recognize it from our own world of experience, i.e., as an activity that occurs for limited periods of time and often during the night. Instead, we move towards layers that transcend normal experience and time.

Having referred to states of dreaming that relate to the rhythms of the human being and the day, the poem moves towards a perception of the dream as an activity that is constantly taking place behind the visible world. It refers to the subconscious in the description of "a kind of out-of-sight dreaming/that newer stops" [ett utom–synshåll–drömmande/som alltid pågår] (ll. 35–36). A particularly interesting metaphor is: "A zone where creeping thoughts learn to walk" [En zon där krypande tankar lär sig gå] (verse 37). In this metaphor, the subconscious is depicted as the playpen of thoughts, and we start to imagine that behind the thoughts of which we are aware, others are slowly growing up before reaching us. However, many indications suggest that the poem does not remain in this parallelization between the dream and the subconscious. Rather, it moves towards even deeper layers. The poem takes the form of a set of Chinese boxes in which every new form of the dream is hiding yet another and more profound version of the nature of dream life.

Staffan Bergsten and Niklas Schiöler agree that the final image of the poem reveals a dimension that transcends both Freud's notions of the unconscious and Jung's psychology of archetypes (Bergsten 1989, p. 139; Schiöler 1999, p. 182). When the final image repeats the initial image of the poem, this therefore has a deeper resonance. The dreamed people are not just those who actually occupy our dreams and those who we therefore see, in some sense. They are also people who, while remaining unseen in the dark, see us (ll. 41–46). What was initially factual information converging with a scientific discourse is ultimately transformed into a metaphysical statement of a rather indeterminate nature. However, trying to explain the components of the image, which is the interpretative method proposed by Espmark, Bergsten and Schiöler, is not the only option. It is also an option to focus on the poem's form.

As the final picture clearly relates to the beginning of the poem, the poem itself resembles the figure of the palimpsest, which it also thematizes in its many double exposures. What happens over the course of the poem is that a world reappears that had otherwise been erased. The people who no longer pass the road in sunlight—which can be understood as an expression of the real and conscious—have therefore not disappeared completely. They have only moved to a more darkened side of existence. The poem represents a holistic perception of life where that which has disappeared is still present on another level.6 It seems to suggest that as our dreams illuminate inner worlds that exist in parallel with the external reality, a space for a larger history that exceeds our usual anchoring in time and space also exists. What seems to have disappeared is still going on, even without us to witness it. Thus, in Tomas Tranströmer's surreal universe, the dream is not just a guide to the inner world of man. It also points to the existence of worlds unfolding in parallel with and beyond what is immediately given, and in that way transcends the Surrealist position.


*3.1. Summary*

Our methods were designed to address two objectives. The first objective was to determine which would be more accurate, ET predictions from a watershed model calibrated to streamgage (ETwm) or ET predictions from a watershed model of the same area calibrated to ETrs product (rather than streamgage). We did this by comparing the ET accuracy of two models: (1) MODIS MOD16, (2) SWAT calibrated to streamgage. Model accuracies were evaluated relative to ET observations at three eddy-covariance flux towers (Figure 1). If ETrs is more accurate than ETwm, then it follows that calibrating the watershed model to that remote-sensing ET product could potentially improve the watershed model's ET accuracy over that of a purely stream-based calibration approach. Conversely, if ETrs is less accurate than ETwm, then calibrating the watershed model to those ETrs would only degrade the watershed model's ET accuracy relative to a stream-based calibration approach. ET observations and simulations were considered on a monthly basis during water years 2009–2018, with a water year defined to extend from October 1 through September 30. For metrics of ET model accuracy, we used the Nash-Sutcliffe efficiency (NSE) [47] which equals the fraction of variance in observations explained by a model, and model percent-bias in average ET (PBIAS) [48]. We also evaluated how well the two models producing ETrs and ETwm captured the relationship between average ET and elevation (1160–2700 m). Metrics of NSE and PBIAS were reported for the period of all water years during 2009–2018, water years with annual precipitation below the 2001–2019 median of 803 mm ("dry years") based on PRISM AN81d product [34,35], and water years with annual precipitation at or above that median.

The second objective of this study was to compare and contrast ET from flux towers and models in a way that identifies seasonal conditions associated with model strengths and weaknesses. We started this out with an examination of monthly time series plots. Next, we compared and contrasted ET "seasonality", defined as the set of monthly ET averages during the calendar year. Lastly, we examined relationships between monthly ET and weather variables of air temperature and vapor pressure deficit (Section 3.2), variables which influence atmospheric water demand and are also used to limit canopy conductance in the ETrs model (Section 3.4).

#### *3.2. Weather Data*

Weather data for watershed modeling and examination of ET-weather relationships were obtained from daily 2.5-arcminute PRISM AN81d product [34,35,49] and GridMET product [50]. Air temperature and vapor pressure deficit were computed from PRISM values of minimum air temperature, maximum air temperature, and dewpoint temperature, along with the equation for saturation vapor pressure in Murray [51]. Downward solar radiation and wind speed were obtained from GridMET. Daily weather time series

were assembled for each subbasin of the watershed (N = 47; Figure 1, lower right) by downsampling the gridded weather data to approximately 250-m resolution, masking the downsampled data to subbasin boundaries, and computing spatial averages (Supplement section S1). These weather time series were input to ArcSWAT to force spatial elements of the watershed model referred to as Hydrologic Response Units (HRUs) (Section 3.5). The weather data used for the examination of ET-weather relationships were taken from the model HRUs nearest to the flux towers as shown in Figure 1.

#### *3.3. Flux Tower Observations of ET*

The ET observations used in this study were collected at three flux towers (Figure 1) situated along an environmental gradient ranging from rain-dominated Ponderosa pine at 1160 m to snow-dominated Lodgepole pine at 2700 m [28] (Table 1). The observations were collected during the day at 30-minute intervals using the eddy covariance method [52], at a height of 5–10 m above the tallest trees [28]. We first obtained the 30-minute ET observations and "Flexible Filler" processing script (Matlab) from the Goulden Lab [45]. Using the Flexible Filler script, we filtered out 30-minute data during calm atmospheric conditions and filled the resulting gaps using the regression approach in Goulden et al. [28,52]. The filtered, gap-filled data were then aggregated to monthly values, requiring at least 50% data availability for each month. Dates of data availability slightly differed for each flux tower, as shown in Table 1.

**Table 1.** Site characteristics of eddy covariance flux towers providing ET observations for this study [28]. These sites are mapped in Figure 1. Water years of data used for this study are listed at right. Years with partial data availability, indicated with asterisk, provided less than 11 out of 12 months' worth of data.

#### *3.4. Remote Sensing of ET*

The ETrs product used in this study was the 8-day, 0.25-arcminute global MOD16A2 product from MODIS sensors onboard the Terra and Aqua satellites [11,12,53]. The model behind this product uses a modifed Penman-Monteith approach adapted from Cleugh et al. [6] to predict evaporation from wet and dry soil, evaporation from wet canopy, and transpiration from dry canopy [12,54]. The model operates at a daily time step using meteorology from NASA's Global Modeling and Assimilation Office (GMAO) reanalysis dataset (1.0 × 1.25◦ resolution), 8-day composites of absorbed photosynthetically active radiation (FPAR) and leaf area index (LAI), and 16-day composites of albedo. Limitations on ET associated with water availability and stomatal physiology (e.g., Jarvis [55]) are modeled in the MOD16A2 product using canopy conductance correction factors consisting of linear functions of vapor pressure deficit and minimum air temperature [11,12,54]. These functions are parameterized by biome-specific look-up tables organized by land cover classification (Table 3.2 of Running et al. [54]).

There was some uncertainty as to how ET in individual MODIS cells, each approximately 500-m across, would correspond to flux tower observations which collect fluxes from areas (footprints) typically measuring 100–2000 m across [56]. For the comparisons to ET from SWAT and flux towers, and in consideration of plausible intra-footprint variability in MODIS data (see Supplement Figure S3), we decided to obtain the MODIS ET data from the single MODIS cells containing the flux tower locations (Figure 1). This decision followed from the results in Supplement Figure S3 showing that MODIS intra-footprint

variability tends to be substantially less than same-cell differences between MODIS and flux tower. We filtered out any MOD16A2 data having QA/QC flags not of "good quality" and not free of "significant" cloud cover, then aggregated it to monthly values using time-weighted averaging and requiring at least 50% data availability for each month.

#### *3.5. Watershed Modeling of ET*

We modeled ET in the upper Kings River using the Soil & Water Assessment Tool (SWAT) version 2012, with ArcSWAT version 2012 for model construction. SWAT dates back to the late 1970s for research into land management impacts on water, sediment, nutrients, and pesticides [57–59]. It has been widely used to simulate hydrologic fluxes in snowinfluenced watersheds such as this study area [60–65]. In SWAT, the water conservation equation is solved at a daily time step in HRUs, each of which is a numerical 1-D element ("bucket") of homogeneous land cover, soil, and slope. Each HRU exchanges water/energy with the atmosphere (including ET) and delivers runoff directly to the stream reach within enclosing subbasin (subbasins shown in Figure 1, lower right). We selected the Penman-Monteith option for potential ET; actual ET was computed based on potential ET and water availability in soil and underlying aquifer [66].

To construct the watershed model, we first built a "base model" in ArcSWAT using the parameters and input datasets for elevation, soil, land cover, meteorology, and snow cover detailed in Supplement section S1. We then initialized the base model with LAI and biomass from the end of a 30-year spin-up forced by dynamic steady-state weather (Supplement section S2), forming the "plant spin-up" model representing mature forest conditions at the start of simulations. Next, we applied a calibration procedure to the plant spin-up model as follows. First, we used a global sensitivity analysis (GSA) to identify the most influential parameters of the plant spin-up model to estimate via calibration. Using the Sobol method of GSA [67], we identified the influential parameters (N = 12) accounting for 99% of the variance in model streamflow error (Supplement section S3). Next, we calibrated the plant spin-up model by estimating values of influential parameters that minimized model errors relative to 2003–2010 monthly, full-natural streamflow at the watershed outlet [36], as described in Supplement section S4. We used for calibration the Sequential Uncertainty Fitting algorithm (SUFI-2) calibration and uncertainty tool of the SWAT-CUP software package [68–70]. Lastly, we validated the calibrated model to 2011–2019 monthly, full-natural streamflow using the parameter ranges obtained from calibration (Supplement Table S6). Simulations for calibration and validation were spun up to a total of 13 years of weather data, consisting of 10 years of dynamic steady-state weather (for aquifer equilibration) followed by three years of real weather (for soil and plant equilibration) (Supplement sections S2 and S4). In terms of model performance, the calibrated and validated models both showed "very good" results (Figure 2) based on criteria in Moriasi et al. [48] and Abbaspour et al. [68]. For the comparisons to flux tower and MODIS, we used monthly ET of the "best" simulation (Figure 2) taken from the HRUs nearest to the flux towers (Figure 1).

**Figure 2.** Monthly stream discharge at Pine Flat Dam from observations versus best simulation of SWAT watershed model. 95% simulation probability also shown, defined at the 2.5– to 97.5–percentile of monthly simulations. Fit statistics are for "best simulation" having the highest objective function, i.e., the Kling-Gupta efficiency (KGE) [71]. NSE = Nash-Sutcliffe efficiency [47], PBIAS = model percent bias [48].


**3. Natural products and drug delivery systems against leishmaniasis: stateof-the-art**

The use of tools and materials at the nanoscale enabled the creation of nanoparticulate formulations such as liposomes, microemulsions, and microcapsules of great interest to the pharmaceutical industry. Drug delivery systems using liposomes are the ones most studied because of their high biocompatibility, ease of preparation, and chemical versatility [22]. Basically, liposomes are microscopic vesicles composed of one or more concentric lipid bilayers separated by aqueous media. Liposomes can encapsulate hydrophilic and lipophilic substan‐ ces; the former stay in the aqueous compartment, whereas the latter are inserted into the membrane. Because liposomes are biodegradable, biocompatible, and non-immunogenic,they are highly versatile forresearch,therapeutic, and analytical applications [23].These vesicles are primarilyconsistedofphospholipids (either syntheticornatural), sterols, andantioxidants [24]. Lipidswithacylindricalshapesuchasphosphatidylcholine,phosphatidylserine,phosphatidyl‐ glycerol, and sphingomyelin, which tend to form a stable bilayer in aqueous solution, are commonly used in liposomal formulations. Phosphatidylcholine is the most employed lipid in liposomal formulation studies due to its great stability against pH or salt concentration variations in the medium [25]. The pharmacokinetic properties of liposomes can be simply modifiedbychangingthechemical compositionofthebilayer components.Moreover,peptides, polysaccharides, or affinity ligands such as antibodies can be incorporated into liposomes [12].

Phospholipid-based liposomes are usually used to change the pharmacokinetics profile of severaldrugs,eithernaturalorsyntheticones.Naturalproductssuchascrudeextracts,fractions, or isolated phytocompounds have been incorporated into different colloidal carriers, includ‐ ingliposomes,withpromisingresults.As expectedinthe incorporationof syntheticdrugs,lipid formulations enhance the solubility and bioavailability of extracts and bioactive compounds derived from plants. Additional benefits of phytoformulations include: (i) protection from toxicity; (ii) enhanced pharmacological activity; (iii) enhanced stability; (iv) increased reten‐ tion time; and (v) protection from physical and chemical degradation [26,22]. The ability of colloidal carriers to improve tissue macrophages distribution may have an impact on *Leishma‐ nia* infection. The tendency of nanoformulations, especially liposomes, to be captured by the mononuclearphagocyte systemmaybe anadditional advantage inthe treatmentofleishmania‐ sis. In fact, intraperitoneal and intravenous administration of liposomes proved to be a good biodistribution system for drugs in the treatment of VL, because it increased drug accumula‐ tioninmacrophage-richtissues suchas liver andspleen,thus reducing the toxicity levelto other tissues and organs [27].

Since ancient times, products from plant, mineral, and animal sources have been used in traditional medicine to fight many human diseases. In fact, for centuries traditional medicine has been the only health care system available for the prevention and treatment of several diseases in different cultures. Currently, the practice of traditional medicine still has a great impact on the health of people who have no access to modern health care practices. In fact, an estimated 80% of people living in developing countries rely almost completely on traditional medicinal practices to meet their primary medication needs [28-30]. Thus, the use of natural products as medicines has attracted the interest of research laboratories around the world seeking new bioactive molecules. Among the most studied natural products, plants are a valuable source of compounds with antileishmanial activity. Active compounds derived from plant extracts have been described by several laboratories worldwide [31-34]. The antileishma‐ nial activity of several crude extracts and fractions derived from plants has been attributed to compounds belonging to diverse chemical groups, including phenolic compounds (e.g., chalcones, flavonols, aurones, lignans, coumarins, quinines, tannins), terpenoids (monoter‐ penes, sesquiterpenes, diterpenoids, triterpenes), and alkaloids (indole alkaloids, isoquino‐ line alkaloids, quinoline alkaloids)[35-37].In fact, phytoscience may be an importanttool in the search for novel antileishmanial agents with fewer side effects and lower potential costs. Secondary metabolites isolated from plant extracts or essential oils can be used in several different ways for the development of drugs. Nanoformulation-based delivery systems are a promising approach to developing novel antileishmanial agents.

**3. Natural products and drug delivery systems against leishmaniasis: state-**

The use of tools and materials at the nanoscale enabled the creation of nanoparticulate formulations such as liposomes, microemulsions, and microcapsules of great interest to the pharmaceutical industry. Drug delivery systems using liposomes are the ones most studied because of their high biocompatibility, ease of preparation, and chemical versatility [22]. Basically, liposomes are microscopic vesicles composed of one or more concentric lipid bilayers separated by aqueous media. Liposomes can encapsulate hydrophilic and lipophilic substan‐ ces; the former stay in the aqueous compartment, whereas the latter are inserted into the membrane. Because liposomes are biodegradable, biocompatible, and non-immunogenic,they are highly versatile forresearch,therapeutic, and analytical applications [23].These vesicles are primarilyconsistedofphospholipids (either syntheticornatural), sterols, andantioxidants [24]. Lipidswithacylindricalshapesuchasphosphatidylcholine,phosphatidylserine,phosphatidyl‐ glycerol, and sphingomyelin, which tend to form a stable bilayer in aqueous solution, are commonly used in liposomal formulations. Phosphatidylcholine is the most employed lipid in liposomal formulation studies due to its great stability against pH or salt concentration variations in the medium [25]. The pharmacokinetic properties of liposomes can be simply modifiedbychangingthechemical compositionofthebilayer components.Moreover,peptides, polysaccharides, or affinity ligands such as antibodies can be incorporated into liposomes [12]. Phospholipid-based liposomes are usually used to change the pharmacokinetics profile of severaldrugs,eithernaturalorsyntheticones.Naturalproductssuchascrudeextracts,fractions, or isolated phytocompounds have been incorporated into different colloidal carriers, includ‐ ingliposomes,withpromisingresults.As expectedinthe incorporationof syntheticdrugs,lipid formulations enhance the solubility and bioavailability of extracts and bioactive compounds derived from plants. Additional benefits of phytoformulations include: (i) protection from toxicity; (ii) enhanced pharmacological activity; (iii) enhanced stability; (iv) increased reten‐ tion time; and (v) protection from physical and chemical degradation [26,22]. The ability of colloidal carriers to improve tissue macrophages distribution may have an impact on *Leishma‐ nia* infection. The tendency of nanoformulations, especially liposomes, to be captured by the mononuclearphagocyte systemmaybe anadditional advantage inthe treatmentofleishmania‐ sis. In fact, intraperitoneal and intravenous administration of liposomes proved to be a good biodistribution system for drugs in the treatment of VL, because it increased drug accumula‐ tioninmacrophage-richtissues suchas liver andspleen,thus reducing the toxicity levelto other

Since ancient times, products from plant, mineral, and animal sources have been used in traditional medicine to fight many human diseases. In fact, for centuries traditional medicine has been the only health care system available for the prevention and treatment of several diseases in different cultures. Currently, the practice of traditional medicine still has a great impact on the health of people who have no access to modern health care practices. In fact, an estimated 80% of people living in developing countries rely almost completely on traditional medicinal practices to meet their primary medication needs [28-30]. Thus, the use of natural products as medicines has attracted the interest of research laboratories around the world

**of-the-art**

354 Leishmaniasis - Trends in Epidemiology, Diagnosis and Treatment

tissues and organs [27].

**Table 1.** Natural sources of active substances used in nanoformulations against *Leishmania*.

Table 1 lists the natural sources used in nanoformulations to improve the bioavailability of antileishmanial drugs, thus increasing their expected therapeutic efficacy. However, the botanical species used for isolation of the active constituent have not been described in some formulations such as those containing asiaticoside and acaciaside [38], whereas others have a plant origin but were purchased commercially [39]. It should be noted that the most studied species listed in Table 1 are native to developing countries, where the popular use of medici‐ nal plants is widespread.


**4. Discussion**

The present study aimed to explain how the COVID-19 restrictions impacted on the sleep through an analysis of the mediational role of mindfulness and distress. Our results showed that the lockdown resulted in a general decrease in mindfulness (with an increase in observing and a decrease in non-judging), an increase in depression and distress, and an increase in sleep problems. Our first model fully supported our hypothesis that the effect of lockdown on sleep depended on mindfulness and distress. In particular, the model showed that lockdown decreased mindfulness, mindfulness decreased distress, and distress increased sleep problems. Furthermore, indirect pathways showed that mindfulness fully mediated the relationship between lockdown and distress, mindfulness and distress fully mediated the relationship between lockdown and sleep, and distress fully mediated the relationship between mindfulness and sleep. The second model supported the hypothesis that acceptance played the main role in the beneficial effects of mindfulness on sleep. In particular, it showed that: lockdown reduced non-judging; both acceptance facets (i.e., nonjudging and non-reacting) decreased anxiety; non-reacting reduced depression; anxiety increased both components of the sleep-wake cycle. The only significant influence of the monitoring factor (i.e., observing) was an increase in sleep problems (which were also decreased by non-judging). Furthermore, indirect effects confirmed both the pivotal role of acceptance (and specifically of non-judging) in the beneficial outcomes of mindfulness and the mediated nature of the effect of lockdown on sleep: non-judging fully mediated the relationship between lockdown and anxiety, anxiety mediated the relationship between non-judging and problems in sleep (partially) and wake (fully), and non-judging and anxiety fully mediated the relationship between lockdown and both sleep and wake problems.

Several lines of research support the view that the effects of lockdown on sleep depend on the mediating role of mindfulness and distress. First, mindfulness is negatively correlated to stress [11,31] and mindfulness interventions have positive effects on stress and stress-related disorders [32]. Second, stress is well-known to have a deleterious effect on sleep [33], which is in accordance with the stress diathesis model of insomnia, according to which sleep problems depend mainly on stressful events and stress-induced cognitive intrusions [15]. Third, the mediational role of stress and stress-related disturbances in the link between mindfulness and sleep is supported by several cross-sectional studies [14,34] and is also in accordance with the meta-cognitive model of insomnia [16]: according to this model mindfulness can improve insomnia by reducing the distress produced by sleeprelated worries, which are the main causes of the secondary arousal that contributes to insomnia. Furthermore, Simione et al. [14] have proposed that mindfulness could act on insomnia also by reducing primary arousal through a reduction of the impact of stressful events. Finally, a recent work involving two studies (one in Wuhan, China, and the other in the United Kingdom) demonstrated the protective role of mindfulness in the relationship between COVID-19-related stressors and decreases in sleep duration [13].

As far as mindfulness facets are concerned, the monitoring and acceptance components of mindfulness behaved in an opposite way: while non-judging decreased during lockdown, observing increased, and while acceptance facets (non-judging and non-reacting) jointly had beneficial direct and indirect effects on all distress and sleep variables, the monitoring facet (observing) had a deleterious effect only on sleep problems. The differential effect of lockdown on the two relevant mindfulness facets seems logical. It is reasonable that during the lockdown people tended to be more vigilant with respect to themselves and the surroundings due to the threat of illness, which might explain the higher observing scores. The same heightened perceived risk might also explain the decrease in non-judging, as the judgement of one's thoughts and behaviors was considered to be important (and socially reinforced) for protecting one's safety. Even the effects of these changes in mindfulness aspects on distress and sleep make sense given the pandemic context. Indeed, while these changes might be the result of trying to preserve one's health, they had a detrimental effect on one's well-being: they led to more anxiety (e.g., noticing more things to be worried about, worrying more about the health and well-being of oneself and loved ones), which in turn detrimentally impacted sleep.

Beyond being understandable given the very peculiar pandemic context, these results are also consistent with previous research. For example, acceptance has been associated with many beneficial outcomes including lower stress, anxiety, and depression [35], while a recent meta-analysis showed that observing correlates with a few psychological symptoms, including anxiety [18]. Consistently with the current results, in Simione et al. [20], sleep problems were the only outcomes (apart from general distress) that were predicted by the

observing facet. According to the influential MAT theory of mindfulness, monitoring alone tends to increase affective reactivity, which can lead to both more psychological symptoms and a greater level of well-being, while acceptance moderates the effect of monitoring in a such way that together they lead to increased psychological well-being [19]. However, on the basis of both their own data and the available literature, Simione et al. [20] showed that these hypotheses were not well-supported, as monitoring was related to only a few psychological outcomes (mainly negative) while acceptance only rarely moderated monitoring, and, even when it did, it protected against the negative effects of monitoring rather than leading to the best psychological outcomes. For these reasons, the authors proposed an alternative hypothesis according to which acceptance alone is mainly responsible for the benefits of mindfulness, whereas monitoring plays only an ancillary role in developing acceptance, while sometimes providing negative consequences. Even though in the present study we could not test for the interaction between acceptance and monitoring due to our small sample size, our results seem to support this alternative hypothesis, as monitoring (observing) played a very limited deleterious role, while acceptance facets (non-reacting and especially non-judging) were the main drivers of change.

Shallcross et al. [36] proposed that mindfulness improves sleep through the mechanisms of experiential awareness, attentional control, and acceptance, which collectively target all the processes that contribute to sleep disturbance: rumination, primary arousal, secondary arousal, sleep monitoring/selective attention and effort, and distorted perceptions regarding sleep impairment. According to this view, acceptance works only on the last three factors, while the first two are targeted only by experiential awareness and attentional control. However, in our data acceptance alone was responsible for the benefits of mindfulness on sleep, in particular through a mediated effect on anxiety. Indeed, while experiential awareness and attentional control without acceptance may even be detrimental in case the current state is unpleasant and unwanted (e.g., stressful thoughts and lack of sleep), thus increasing rumination and primary arousal, acceptance has been associated with less worry and rumination [37], and with less stress and fewer stress-related disturbances [35]. Hence, it is likely that acceptance alone could act on all the processes that contribute to sleep problems.

Finally, we showed that the lockdown-related sleep problems depended on a decrease in mindfulness traits, and thus the present research adds evidence to the mounting literature recommending the use of mindfulness-based interventions to treat insomnia and sleep disturbances [12,16,36]. Furthermore, by showing the pivotal role of acceptance (nonjudging) in linking lockdown and sleep problems, our results suggest that it may be interesting to design mindfulness-based interventions that focus particularly on developing acceptance skills so as to test their capacity to prevent sleep problems, particularly in stressful situations.

An important strength of the present study consists in being one of the few studies with "real" pre-lockdown measures of analyzed variables, thus leading to an authentic longitudinal study assessing the impact of the lockdown. Due to the impossibility of foreseeing the advent of the pandemic and the related restrictions, the majority of the previous studies concerning the effects of the pandemic on sleep had to make important compromises, which inevitably limited the reliability. For example, Cellini et al. [3] asked participants to think about the week before any restriction in Italy, which may introduce memory biases in subjects' responses. Similarly, Salfi et al. [4] longitudinally assessed sleep quality, insomnia symptoms, and general distress (anxiety, depression, and stress) in an Italian sample from the first to the second wave of COVID-19 thus comparing similar situations, as the pandemic was continuously present in Italy between the two waves (with different degrees of risk).

However, the present study has its own limitations. First and foremost, the main limit of the present study lies in the small numerosity of the sample which was due to the fact that when the lockdown began, only a small group of participants had compiled the questionnaires. When evaluating model's generalization, one should consider several

factors, including the study design and the strength of path coefficients. Our study uses a longitudinal design, which is far more robust than a cross-sectional one, and our main direct and meditated paths reported medium sized effects (ranging from 0.25 to 0.47). As suggested in [38], to find a reliable medium-sized mediation path in a longitudinal study like our own with bootstrapping coefficients, about 40/50 participants should be sufficient. Moreover, our model could be considered unbiased as we did not face non-convergence and improper solutions problems during model estimation [39]. So, from this point of view, the numerosity of our sample was almost acceptable. However, our two models contained, respectively, 21 and 63 free parameters. Considering the rule of thumb requiring a 10:1 ratio between observations and free parameters [40], the numerosity of our sample was indeed too small. For this reason (and also to get non-identified models for which we could obtain interpretable goodness of fit statistics), we simplified our models by removing all non-significant paths and covariates, as testing both models while removing the covariates did not alter significantly any of the considered paths. In this way, we obtained two models whose paths were supported both by the literature and by the previous 'full' models. These 'simplified' models had, respectively, six and 12 free parameters, and both demonstrated good fit indexes. This makes the numerosity of our observation (78) adequate for the first model, while a bit too low for the second model, which consequently should be considered with more caution. Anyway, we think that the limitation due to the small sample was counterbalanced by the possibility of giving a real picture of the effects of lockdown restrictions on the assessed variables. Furthermore, the fact that our results confirmed both our hypotheses, which were based on the previous literature, suggests that the study power was enough for detecting at least the main true effects. Another limit of the present work depends on the measurement tool used for assessing mindfulness. Even if the FFMQ is the most widely used tool adopted for measuring mindfulness, the acceptance dimension is defined by two distinct measures (non-judging and non-reacting), which could be a source of confusion. Future research should confirm the role of acceptance in protecting from sleep problems using another mindfulness tool such as the Philadelphia Mindfulness Scale (PHLMS [41]), as this includes only one scale for acceptance and one for awareness (which can be considered as a measure of attention monitoring). Finally, our study used only self-report questionnaires, which could limit the reliability and validity of our findings due to well-known problems related to self-report measures, such as limited introspective abilities, problems of interpretation, and response biases such as social desirability. Future studies could improve this aspect by also adopting more objective measures of the assessed variables. From this point of view, the development of behavioral measures of mindfulness represents an important challenge for future research [42].


**2.2.4 Particle size distribution by LASER diffraction spectrometry**

The particle size distribution of agglomerates and particles of sintered powder was determined by a laser diffraction spectrometer Cilas, model 1180. The detection range of this equipment is between 0.04 and 2500 μm.