达涅利

We consider a complex real-world problem in slab yard management that deals with block relocation and slab stack shuffling in a single problem. For this integrated problem, we designed a two-level metaheuristic approach with a local search procedure that works at the level of the slab selections and uses an inner greedy heuristic for deciding relocations and retrievals. We tested our solution approach on a novel dataset using an actual yard layout and a simulation tool to set its initial configuration. Our search method successfully obtained high-quality solutions, even for large instances involving over 2000 slabs. To assess the performance of our search method compared to state-of-the-art ones, we adapted it to a simpler formulation from recent literature and tested it on public benchmarks. Our method proved as good as the best existing ones in most available instances and consistently outperformed them on the largest ones.

Conser Duetto technology is a revolutionary process that facilitates the production of biodegradable plastic intermediates from maleic anhydride. This Technology represents a really promising process to produce intermediates which are becoming key chemicals for the development of biodegradable plastics. In detail, the innovative and interesting aspect of the Duetto technology is the co-production of butanediol (BDO) and dimethyl succinate (DMS), which are the mean feedstocks for downstream biodegradable polymers plant such as PBS. The origin of this technology starts from the consolidated experience and full knowhow of Conser in the BDO process, optimized through several R&D activities developed on the most critical part of the technology (mainly hydrogenation section), consultants support and deepen literature investigation. The result is the finalization of a new process where the hydrogenation process of diesters of the maleic anhydride occurs in mixed liquid/vapor phase allowing the separation of the DMS through a simples phases separation, differently from other available process, based on the hydrogenation step in vapor phase where the separation of DMS is more complicated. Conser Duetto is a new and improved technology with the aim to simplify the industrial process of manufacturing the raw materials of the PBS products and to decreasing their production cost to make PBS comparable to the other biodegradable polymer, not only in term of characteristics (mechanical, compostability, processability) but also in term of cost. In that sense, Conser Duetto technology, together with the innovative idea to produce PBS by trans-esterification by using DMS as raw material instead of esterification by using Succinic Acid, can represent a real game changer for the PBS industry and can be easily adaptable to the production of BDO and DMS starting from a fossil feedstock (C4 fractions such as butane) or from a bio based feeding (bio succinic acid). The adoption of Conser Duetto technology is in line with global environmental protection efforts and the growing demand for non-invasive and eco-friendly. As regulations tighten and bans on nonbiodegradable plastics become more widespread, technologies like Conser Duetto are poised to play a crucial role in the transition to sustainable materials and reducing the accumulation of plastic waste even starting from a fossil feedstock (C4 fractions such as butane). Conser Duetto technology represents an innovative solution to co-produce butanediol and dimethyl succinate as feedstock for the synthesis of PBS. Proposed process is optimized in terms of capital and operating expense by maximizing energy efficiency and recovery. These attributes make it a valuable solution for industries seeking sustainable production methods, particularly in disposable packaging, as well as in the agricultural sector for mulch films. Key principles of the technology are covered by a patent: EP 4188903.

How Lifestyle Brands Use Curated Picks to Boost Engagement on Fridays Brands always act like Shopify's "three-step" collection thing is a piece of cake: make a Collection, tag some stuff, put fresh banners on your homepage—done. But no, that's just what you see if you stare at the docs for five seconds. Real life? Way more chaos. Once you throw in actual teams—designers want their say, inventory can't keep up (or doesn't trust marketing), and marketing just wants anything up by Friday—it falls apart pretty quickly. Okay, try to draw this out as an actual flowchart for something like those 'Friday Picks' lifestyle collections everyone's obsessed with. What actually happens: Three totally different directions. First: manual collections. Small shop territory or anyone who really cares about nitpicking every single product—you hand-pick and arrange it all yourself. Total control over how it looks but yeah, a nightmare to maintain if your catalog gets shuffled every week or promo SKUs fly in last minute (retailers doing weekly sales overseas have complained about this burnout before). Second route is automating it: Shopify lets you use up to 60 rules, like "color equals black" plus "tagged Fall25." Honestly great if you've got hundreds or thousands of products and they're labeled right—the machine does all the grouping for you so updates are way less work. The catch? As soon as someone flubs the tags or skips an update in inventory… weird random stuff starts showing up ("ghost products"), and fixing that can waste even more time than if you'd done it all by hand. Then there's option three, which I think most brands want but barely talk about: go hybrid! You set rough rules for the bulk—basics handled automatically—but still go in manually to highlight big-deal hero items at the top. This seems kind of necessary if you're trying to balance Western visual-style curation vibes with East Asia's value-driven bundle culture—one side likes beautiful layouts; the other wants super clear deals front-and-center. Actual numbers say something interesting too: brands who stick with full manual selection see higher engagement on those Instagrammable campaigns because everything pops visually; massive stores switching to pure automation have cut update labor by nearly 70% when dealing with five hundred-plus SKUs (saw that from Prisync last year). Of course there's still pain—manual means schedule crunches ruin people's Fridays when promos change late, and automation means being haunted by off-brand products sneaking into prime slots unless your data hygiene is rock solid. So honestly, picking one path isn't realistic—it depends mostly on how often you need to refresh collections (weekly drops vs once-a-quarter updates?), how giant your catalog is, whether your marketing team is huge or basically one person multitasking across Slack channels, and honestly where in the world your audience actually spends money (are they looking for style stories or best-price-first?). There really isn't a perfect setup—for anyone hoping Friday feature launches will finally go smooth this time… well, good luck without some blending and backup plans built in. Friday mobile numbers... just, wow. I saw Salesforce and Experian saying 70% plus of all retail orders are from people on their phones now. $195 billion a year, on mobile. That's almost hard to believe—no, it's not a mistake. Phones aren't just "important"—they basically took over. Like, those Friday Picks blocks? Higher click-throughs and more conversions than desktop bits. People just poke at stuff more when it's right in the feed on their phones; honestly, it's kind of about how you line up the visuals there. Okay but yeah—not everything is shiny here. If you keep pushing out those same curated banners every week, folks get tired pretty quick... they call it 'curated fatigue' (which sounds weird but makes sense). Even though online sales jumped 10.2% during last year's Black Friday through Cyber Monday (yup: Salesforce again), brands that kept recycling those copy-paste grids without any tweaks or personality? Returns actually went down as weeks rolled on. Some of the bigger lifestyle names switched things up—a bunch of limited-time offers, little interactive buttons or whatever, shifting which products got the spotlight every Friday instead of sticking to old picks—and turns out, that kept people interested way longer. Kind of funny how one change like that helps Friday survive promo overload when every other brand is blasting deals left and right. So, working with 2 or maybe 3 US fashion micro-influencers… yeah, that's actually doable for a regular four-week run if you manage to keep everything kind of humming quietly in the background. Not just hoping things fall into place though—you need some actual structure here, like ways to work together without it blowing up your inbox. Honestly, otherwise this whole thing turns into a mess so fast. First bit: picking people. Don't overthink it too much—look for folks in that 10k up to like 150k follower range. But numbers are weird… I mean, not everyone with followers gets real interaction on their posts. I'd say glance at their last few pieces and see if they're sitting somewhere between that 1.2% and, what was it, right—8.5% engagement thing (usually Instagram's own analytics show this; sometimes rate cards help but... sometimes). If you spot anyone under two percent? Just swap them out early—don't wait until after signatures and paperwork 'cause honestly it's probably not going up later. Next thing: Be dead clear about what you want content-wise right from the start. Send them whatever banners or layout examples you already have (plain email is fine), note down specs—for sure keep everything sized for phones (stretching those desktop ones makes it look awkward). Jot out a brand keywords cheat-sheet too; otherwise they go off-brand real quick. And deadlines… ugh. Make sure there's a hard line before contracts so there aren't any weird last-minute excuses later. Tell them to shoot over rough drafts three days before posting—it sounds harsh but really? Anyone late here probably will trip things up down the road and ruin your timeline. Once they're onboarded just toss all the basics into one Google Sheet—nothing fancy, just assets listed by name plus due dates for every checkpoint/step along the way… try slapping KPI columns (engagement rate, swipe-ups—or tap-throughs? I always mix these terms) right at the top where both sides can check Monday mornings instead of guessing how things went over the weekend or worse, never following up at all. If something looks weird by week two—a sudden drop in numbers or if quality's off—it's way better to get everyone on a group chat fast rather than ignoring it until month-end recaps start finger-pointing time. One more bit—the approvals headache: Only let one person do internal review each round alongside influencer tweaks so you're not stuck in forever loops ("Can we change this font?" "Wait maybe try this filter?"…) It saves so much time mentally if you don't bounce files back and forth all week. Wrap-up picks should be posted using tools friendly for phones—not those clunky desktop dashboards that nobody checks anyway—and scheduled properly so stuff doesn't get lost in some inbox hell when everyone bails for the weekend. The real test? Assets have to actually look right inside Insta Stories previews before pressing "publish." Doesn't matter if everything is "ready" elsewhere—if it breaks in preview mode then nope…it's not done yet and needs another pass through 'cause followers definitely notice when brands phone it in nowadays. You know, people always imagine you just slap up the Friday story picks, walk away, and then—bam—everything clicks. Nope, that's definitely not it. The magic part? It's really all about these behind-the-scenes moves that almost nobody actually bothers with. Like, first thing that jumps out to me: don't wait around forever for someone's sign-off. You need someone glued to that campaign dashboard on Fridays—literally just refreshing every 15 minutes as numbers trickle in. Not… whatever, lost in some Slack channel at six in the evening when everything already went down. Oh! And if you catch some bad headline or boring frame showing up mid-afternoon? Don't overthink it, just yank it or shuffle its spot right away—not flawless maybe but so much better than letting a dud soak up views until everybody complains on Monday. Here's something else I run into a lot: prepping mini versions of stuff ahead of time (the fancy folks call them "micro-iterations" but honestly it's just backup plans). Like before launch day hits, have different banners or little CTA tweaks ready so when your initial two hours of data totally tanks expectations—you can switch gears instantly. Picture this scene: two teammates staring at their screens side-by-side arguing if blue or orange wins more taps in real time… makes things weirdly fun too. At the end of the day it saves everyone from that "wait for next week" slog and keeps things zippy. Oh and speaking of popups—man, people get sick of those fast if you blast them after lunch. That spring we tried cutting push notifications from three little barrages down to just one ping right at 1pm sharp; turned out average mobile session length shot way up even though total pushes got cut by half. Wild how much difference tiny changes like that make when folks aren't annoyed to death. Last bit that keeps biting teams: backend visibility versus wild guessing games. So much better to take a couple minutes in the middle of shift and peek at Shopify Analytics or Google reports—you can kill off weak tags or reorder junky product rows while it still matters instead of sweating bullets over stale numbers later on Friday night or whenever managers start demanding "updates." Forget expensive dashboards; half the battle is just making sure anyone can drop a quick

The left ventricle (LV) ejection fraction (EF) alone is no longer sufficient to define LV function in aortic stenosis. New echocardiografic parameters such as Global Longitudinal Strain (GLS) and Myocardial Work (MW) can provide informations on early LV dysfunction compared to EF in patients wiht severe aortic stenosis. MW is the GLS with included afertload, using cuff blood pressure as a surrogate for LV systolic pressure (LVSP) which do not represent the real intraventricular pressure in this setting. The study aims how MW varies when to LV systolic pressure is added the mean aortic transvalvular gradient in patients with true severe aortic stenonsis and severe paradoxical aortic stenosis, having the same EF and GLS. 54 patients with true severe aortic stenosis were compared to 24 patients with severe paradoxical aortic stenosis. In addition to LVEF and GLS, the 4 parameters of the MW were calculated and compared between the two groups: Global Work Index (GWI), Global Constructive Work (GCW), Global Waste Work (GWW) and global work efficiency (GWE). Then to the MW parameters, mean transaortic gradient has been added, determining new 4 parameters: GWIMGAo, GCWMGAo, GWWMGAo, GWEMGAo. True severe aortic stenosis and severe paradoxical aortic stenosis have normal LVEF (61,26 ± 1,38% vs 59,09 ± 1,93%, p=ns, respectively), reduced GLS (-15,6 ± 0,48% vs -15,21 ± 0,70%, p=ns), aortic area index (AVAi 0,38 ± 0,01cm2/m2 vs 0,45 ± 0,01cm2/m2, p=0.001). GWIMGAo and GCWMGAo are worst in patients with true severe aortic stenosis (2388,66 ± 103,07mmHg% vs 1999,87 ± 137,25mmHg%, p=0,030; 3010,54 ± 104,55mmHg% vs 2496,75 ± 146,23mmHg%, p=0.006). The two groups have same LVEF and same reduced GLS, but from the MW point of view, true severe aortic demonstrate higher MW. MW variables could be and additional tool for the startification of severe aortic stenosis in terms of patient outcome.

Echocardiography is a useful tool for evaluation of organ damage and ejection fraction (EF) is the parameter for the evaluation of cardiac function. New parameters such as Global Longitudinal Strain (GLS) and Myocardial Work (MW) seem to be more sensitive in left ventricular (LV) dysfunction detection. The study investigates whether parameters of LV function such as GLS and MW are more sensitive in detecting LV impairment in patients with hypertension compared with healthy controls, than traditional parameters. Clinical and a comprehensive echocardiographic data of 40 patients with hypertension were analyzed in comparison with 10 normal subjects. In addition to LVEF and S’ on TDI, GLS and MW (Global Work Index (GWI), Global Constructive Work (GCW), Global Wasted Work (GWW) and Global Work Efficiency (GWE), were determined and compared with healthy controls after adjustment for confounders. Hypertensives and controls have normal LVEF(61,9% ± 0,77% vs 62,7% ± 0,15% respectively) and S' on TDI (9,4 cm/s ± 3,21 cm/s vs 10,5 cm/s ± 2,1 cm/s respectively),normal LV mass index. GLS and LV MW GWE in hypertensive patients were reduced (-18,5% ± 0,4% vs -20,8% ± 0,7% respectively with p<0,000; 91,4 mmHg% ± 0,6 mmHg% vs 96,2 mmHg% ± 1,2 mmHg% respectively with p<0,000), while LV MW GWW (221,4 mmHg% ± 22,3 mmHg% vs 80 mmHg% ± 43,4 mmHg% respectively with p<0,000, GCW (2557,6 mmHg% ± 75,5 mmHg% vs 2361,5 mmHg% ± 147,2 mmHg% respectively with p<0,000 and GWI (2018,6 mmHg% ± 56,6 mmHg% vs 1977 mmHg% ± 110,3 mmHg% respectively with p<0,000) increased in comparison to controls. Despite a normal ejection fraction, novel echocardiographic parameters such as LV GLS and LV MW GWE are early reduced in hypertensive patients, while LV MW GWW, GCW and GWI early increased compared to healthy controls.