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BEd last year papers are very hard to find but here we have given more than 100 practice sets and last year examination sample question papers of B.Ed program for all the major universities and institutions providing B-Ed course for distance and regular.
Here you can find semester 1, 2, 3, 4, 5, 6 and 1st, 2nd and final year B.Ed question papers and get distinction marks in the B.Ed examination. If you are looking to get higher marks in bed exam then I would recommend you that you should practice all these sample and previous year b. Ed papers which are in both Hindi and English. We have given a list of all sample and model practice test BEd papers for all general, reappear, improvement B-Ed exams.
These are the latest B.Ed (bachelor of education) question papers of 2018 and 2019. Also, we have given a separate post for MDU, CRSU , and KUK Last Year B. Ed question papers. In these Bed previous year papers, all the important questions for 2019 and 2020 Bed exams which are generally asked has been given. If you have got a very short time to prepare for B.Ed exams, then just go through all these sample B.Ed question papers. And also share these B.Ed question papers . The list of all B.Ed question papers of 2014, 2015, 2016, 2017, 2018 and 2019, 2020, 2021 examination is given below
B.Ed Question Papers Download PDF FREE
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yes dear.. thanks
Plz tell me ye paper 1 2 3 q h...
Hi dear.. These all are sample and Model papers of B.Ed.. Which will give you a lot of help in the coming exams.. ye 1 2 3 ka matlab hai.. sample paper 1, sample paper 2 and sample paper 3 of a single subject..
Ohh..ok thnku
Can u send hindi 1yr ques paper on my mail plzz
Thanks for providing such a great material.
how i download this question papers???
Sabhi years ka question paper hai
Plz provide question papers in hindi
I want question papers of mumbai university
Hum ko samj mai nahi arah hai mera 1 semester prus ka hai b.ed ka hai muje yplan kara dege plz
I complete my b.ed.in 2014,2015 but i could not clear the first paper now i want to give the same please guide me
Hi dear.. you should contact your University or College where you have done your B Ed and ask them If any mercy chance provided.
I am doing bed from CCSU. Kya muje ye papers help krenge. Ccsu k hi previous year k hn ye sbhi? Bed 1st year k sare nhi hn isme like growing up as a learner, philosophical and sociological perspective
Can you please provide 2014 and 2015 question paper of b.ed 1st year
Sir please semester 3&4 ka previous years question papers dijiye n
Thanks for the papers. Just wanted to confirm, if these are previous years papers of UP B.Ed. or any other state
Please send me kuk last year's question papers of pedagogy of science.
Apka koi contact no. Mil sakta hai,
HOW TO DOWNLOAD IT.
hi need help b ed, second year, ICT practical 205-11 creation of sort audiovisual content( not exceeding 5 mins) using webcam or digital camera with video recording facility. Copying and viewing same on a PC.
Similarly do we get question papers for 3rd sem as well ?
The material which have provided is superb but i want practical file of commerce.
Mujhe b.ed ke 1st semester ke previous years ke paper chahia 2013 to 2020 tk
Can I get all for Marathi medium
Where can I download b. Ed 1st year question paper.. Every site gives different previous years question paper
Sir ye question paper ccsu ke h
Kya aap mere mail pe B. Ed 2nd year ka 2017 aur 2019 ka question sub- commorse ka bhej denge
Send me rajasthan university previous years paper
B.ed commerce question papers
Sir.. previous year question papers of 2nd year... pedagogy of geography is not there..! I can't find them PLz post it asap...i need them
Please share ccs university 10 years
Mujhe B.ed k first sem k question paper chahiye 2017_2022 tak
mujhe b.ed 1st semester ka question paper chahiy 2016 - 2022
Can you please provide sndt University previous year question papers
Contact form.
Trump and biden: the national debt.
The national debt is on course to reach a record share of the economy under the next presidential administration, due in part to policies approved by Presidents Trump and Biden during their time in office, including executive actions and legislation passed by Congress.
While it is important to understand the fiscal impact of the promises candidates make on the campaign trail – particularly because they reflect the candidates’ own policy preferences and are not impacted by unexpected external events or the actions of Congress – the fact that both leading candidates have served as President also allows for a comparison of their actual fiscal records. This analysis focuses on the estimated ten-year debt impact of policies approved by Presidents Trump and Biden around the time of enactment. 1 In this analysis, we find:
In companion analyses, we will show:
Tax Cuts & Jobs Act | +$1.9 trillion | Partisan |
Bipartisan Budget Acts of 2018 & 2019 | +$2.1 trillion | Bipartisan |
ACA Tax Delays & Repeals | +$539 billion | Bipartisan |
Health Executive Actions | +$456 billion | Partisan (Executive Action) |
Other Legislation | +$310 billion | Bipartisan |
New & Increased Tariffs | -$443 billion | Partisan (Executive Action) |
CARES Act | +$1.9 trillion | Bipartisan |
Response & Relief Act | +$983 billion | Bipartisan |
Other COVID Relief | +$756 billion | Bipartisan* |
| ||
Appropriations for FY 2022 & 2023 | +$1.4 trillion | Bipartisan |
Honoring Our PACT Act | +$520 billion | Bipartisan |
Bipartisan Infrastructure Law | +$439 billion | Bipartisan |
Other Legislation | +$422 billion | Bipartisan |
Student Debt Actions | +$620 billion | Partisan (Executive Action) |
Other Executive Actions | +$548 billion | Partisan (Executive Action) |
Fiscal Responsibility Act | -$1.5 trillion | Bipartisan |
Inflation Reduction Act | -$252 billion | Partisan |
Deficit-Reducing Executive Actions | -$129 billion | Partisan (Executive Action) |
American Rescue Plan Act | +$2.1 trillion | Partisan |
|
Note: bipartisan indicates legislation passed with votes from both political parties in either chamber of Congress. *Includes $23 billion of executive actions in the form of student debt payment pauses.
During his four-year term in office, President Trump approved $8.4 trillion of new ten-year borrowing above prior law, or $4.8 trillion when excluding the bipartisan COVID relief bills and COVID-related executive actions. Looking at all legislation and executive actions with meaningful fiscal impact, the full amount of approved ten-year borrowing includes $8.8 trillion of deficit-increasing laws and actions offset by $443 billion of deficit-reducing actions. 2
These estimates are based on scores of legislation and executive actions rather than retrospective estimates. Scores are generally made on a conventional basis, though the Tax Cuts and Jobs Act (TCJA) is scored dynamically. The actual debt impact of the policies was likely somewhat higher than these scores. In particular, the TCJA likely reduced revenue more than projected and saved less from repealing the individual health care mandate penalty, 3 while the Employee Retention Credit was likely far more expensive than originally estimated.
Sources: CRFB estimates based on CBO and OMB projections.
The major actions approved by President Trump (and ten-year impact with interest) include:
Over his first three years and five months in office, President Biden has approved $4.3 trillion of new ten-year borrowing, or $2.2 trillion when excluding the American Rescue Plan Act. This includes $6.2 trillion of deficit-increasing legislation and actions, offset by $1.9 trillion of legislation and actions scored as reducing the deficit.
These estimates are based on scores of legislation and executive actions rather than retrospective estimates and do not include preliminary rules, unexecuted “side deals,” or actions ruled illegal by the Supreme Court. Updated scores and in-process actions would increase the total. For example, an updated estimate would likely wipe away the $252 billion of scored savings from the Inflation Reduction Act, 4 the informal FRA side deals would reduce its savings by about $500 billion , and the new student debt cancellation plan could cost $250 to $750 billion .
The major actions approved by President Biden so far (and ten-year impact with interest) include:
The next presidential term will present significant fiscal challenges. While past performance is not necessarily indicative of future actions, it is helpful to examine the fiscal performance from each President’s time in office for clues as to how they plan to confront these challenges or how high of a priority fiscal responsibility will be on their agendas.
Both candidates approved substantial amounts of new borrowing in their first term. President Trump approved $8.4 trillion in borrowing over a decade, while President Biden has approved $4.3 trillion so far in his first three years and five months in office. Of course, accountability also rests with Congress as a co-equal branch of government, which passed legislation constituting the majority of the fiscal impact under both presidents.
Some of this borrowing was clearly justified, particularly in the early parts of the COVID-19 pandemic when joblessness was rising rapidly and large parts of the economy were effectively shut down. However, funding classified as COVID relief explains less than half of the borrowing authorized by either President, and arguably, a meaningful portion of this COVID relief was either extraneous, excessive, poorly targeted, or otherwise unnecessary. 5
In supplemental analyses, we will compare a number of other aspects of the candidates’ fiscal records.
During the next presidential term, the national debt is projected to reach a record share of the economy, interest costs are slated to surge, the debt limit will re-emerge, discretionary spending caps and major tax cuts are scheduled to expire, and major trust funds will be hurtling toward insolvency.
Adding trillions more to the national debt will only worsen these challenges, just as both Presidents Trump and Biden did during their terms along with lawmakers in Congress. The country would be better served if the candidates put forward and stuck to plans to reduce the national debt, secure the trust funds, and put the budget on a sustainable long-term path.
This analysis estimates the additional borrowing approved by Presidents Trump and Biden through tax and spending changes passed by Congress or contained in executive actions from their administrations. It does not estimate the amount of debt that accumulated over their terms, which partially reflects actions taken prior to their time in office and does not account for the fiscal impact of the actions approved by the President but incurred outside of his four-year term. We will publish changes in debt during their terms in a supplemental analysis.
Our analysis incorporates all major pieces of legislation and executive actions – those with more than $10 billion of ten-year budget impact – approved by Presidents Trump and Biden. Estimates rely on ten-year budget scores, as under standard convention. In order to rely on official scores wherever possible, however, all estimates are based on the ten-year budget window at the time of enactment – meaning different policies cover different time frames and thus are not purely additive or comparable.
In general, estimates rely on official estimates from the Congressional Budget Office (CBO) and Joint Committee on Taxation (JCT) presented prospectively. When such scores are not available or not comprehensive, we may use estimates from the Office of Management and Budget, the regulatory agencies, or our own estimates.
Estimates are not updated to incorporate data and results made available well after implementation; no legislation signed by either President Trump or President Biden has been re-estimated in full to incorporate observed costs or effects, and partial updates would bias the overall numbers. However, possible differences between initial scores and actual costs, including from the TCJA, the IRA, and COVID relief, are discussed throughout this paper.
Estimates incorporate impact on interest costs, which we calculate using the most recent CBO debt service tool at the time of enactment, unless interest impact is included in the estimate. Estimates are generally based on conventional scoring, but in the case of the Tax Cuts and Jobs Act, we incorporate macroeconomic impacts as estimated by CBO shortly after enactment.
All estimates are in nominal dollars at the time of approval, which means deficit impact from earlier budget windows generally represent a larger share of GDP per dollar due to higher price levels and output over time.
Finally, the estimates are based on the policies as written and do not try to correct for arbitrary cliffs, side agreements, or other budget gimmicks that may create a misleading picture of the intended fiscal impact of the policy.
1 Our estimates compare ten-year estimates of each action before implementation, generally using prospective scores of policies and adding them together despite being over different windows. Although this is not a perfect apples-to-apples comparison for a variety of reasons, it allows us to rely on official numbers and continue to compare over time. See the methodology section for a more detailed explanation.
2 Many pieces of legislation with fiscal impact include tax and spending changes that both add to and reduce projected deficits. The $8.8 trillion figure is based on the net deficit impact of deficit-increasing bills, rather than the gross deficit increases within those bills. For example, the $1.9 trillion impact of the TCJA represents the combination of tax cuts, base broadening, lower spending as a result of repealing the individual mandate penalty, interest, and dynamic effects on revenue and spending.
3 The larger deficit impact from the TCJA is due to a combination of a larger nominal tax base, lower health savings from individual mandate repeal, the unexpected use of a SALT cap workaround, reduced revenue collection from the limit on pass-through losses, higher revenue loss related to bonus depreciation, and other factors.
4 Due to higher prices and output, greater demand for subsidized activities, and laxer-than-expected regulations, the IRA’s energy provisions are now expected to have a fiscal impact of $660 billion – about two-thirds more than the original estimate of roughly $400 billion. This excludes the effects of the Administration’s vehicle emissions rule, which we’ve scored separately. At the same time, revenue collection under the IRA is also likely to be higher in light of higher-than-projected nominal corporate profits , greater expected voluntary tax compliance , and less-than-expected responsiveness to the buyback tax. Overall, we believe a re-estimate of the IRA would be roughly budget neutral. The emissions rule approved by President Biden would increase deficits by about $170 billion – mainly by further increasing the fiscal impact of the IRA tax credits – and is included in our tally of his executive actions.
5 In a previous analysis, we estimated that $500 to 650 billion of COVID relief was extraneous – unrelated to the pandemic or subsequent economic fallout – including $300 to $335 billion enacted under President Trump and $200 to $315 billion under President Biden. These prior estimates are not perfectly comparable to estimates in this paper but give a sense of scale. In additional analyses, we estimated that the American Rescue plan likely significantly overshot the output gap it was aiming to close while providing excessive relief to a number of sectors. There were also excesses and lack of targeting in earlier COVID relief packages, including as it related to stimulus checks , the additional $600 of weekly unemployment benefits , and the Paycheck Protection Program.
Sixteen Nobel Prize -winning economists signed a joint letter Tuesday warning of what they see as economic risks if former President Donald Trump were to serve a second term, including reheated inflation.
“While each of us has different views on the particulars of various economic policies, we all agree that Joe Biden’s economic agenda is vastly superior to Donald Trump’s,” the economists wrote. Axios was first to report the letter.
“There is rightly a worry that Donald Trump will reignite this inflation, with his fiscally irresponsible budgets,” wrote the group of politically progressive academics.
Trump has so far proposed making his first-term tax cuts permanent, imposing universal tariffs on all imports, with a China-specific tariff rate between 60% and 100%, and pressuring the independent Federal Reserve Board to cut interest rates.
Economists and Wall Street analysts alike have predicted that any or all of those proposals could reinflate prices, which remain vulnerable despite cooling slightly in recent months.
Joseph Stiglitz, who won the Nobel Prize in 2001, led the effort to publish Tuesday’s letter. His co-signers include George Akerlof, Sir Angus Deaton, Claudia Goldin, Sir Oliver Hart, Eric Maskin, Daniel McFadden, Paul Milgrom, Roger Myerson, Edmund Phelps, Paul Romer, Alvin Roth, William Sharpe, Robert Shiller, Christopher Sims and Robert Wilson.
“Nonpartisan researchers, including at Evercore, Allianz, Oxford Economics, and the Peterson Institute, predict that if Donald Trump successfully enacts his agenda, it will increase inflation,” the economists wrote.
Stiglitz said he felt compelled to initiate the letter based on a flurry of recent polling in which voters said they trusted Trump over Biden to manage the U.S. economy.
“A lot of people think Trump would be better for the economy than Biden,” Stiglitz told CNBC in an interview. “I thought it would be important for Americans to know that at least a group of credible economists differs very strongly.”
The timing of Tuesday’s letter was notable, coming just days before Trump and Biden are scheduled to face off in the first presidential debate of the general election. The Atlanta debate hosted by CNN is expected to dedicate significant time to the economy and specifically, inflation.
The Trump campaign staunchly rejected the Nobel economists’ position.
“The American people don’t need worthless out of touch Nobel peace prize winners to tell them which president put more money in their pockets,” Trump campaign spokesperson Karoline Leavitt said in a statement to CNBC.
Under Trump, the December year-over-year Consumer Price Index fell during three of his four years in office.
The Biden campaign seized the opportunity to tout the letter on Tuesday: “Top economists, Nobel Prize winners, and business leaders all know America can’t afford Trump’s dangerous economic agenda.”
The Nobel laureates’ letter contained a distinct political perspective, as well as an economic one.
Many of these economists signed a similar September 2021 letter expressing support for President Joe Biden’s Build Back Better package. Critics at the time argued that the massive spending packages would drive up inflation.
At the time, Stiglitz observed that some people “invoked fears of inflation as a reason to not undertake” the Build Back Better investments. “This view is short-sighted,“he said in a press release.
This time around, Stiglitz and his co-signers took a more cautious approach to inflation, after the U.S. economy has spent that last year recovering from 2023′s scorching inflation spike.
The higher prices were partly due to pandemic-era supply chain snarls, which left the global trade system unable to meet the pent up demand of American consumers.
But this demand was itself the result of a U.S. economy that weathered the pandemic better than many had anticipated it would — thanks to generous government subsidies like the expanded Child Tax Credit and the Paycheck Protection Program.
Since then, Stiglitz said, Biden has helmed a successful effort to cool those inflation peaks.
“Inflation has been brought down, actually, remarkably quickly,” he said. “I would say it’s because of Biden.”
New research on how to identify investments that produce delayed but real profits — not just those that produce short-term accounting profits.
In a well-functioning capital market, profits should be the sole criterion for firm survival; that is, firms reporting losses should disappear. Of late, however, loss-making firms are highly sought after by investors — often more than some profitable firms. Unicorns, or startups with valuations exceeding a billion dollars, are examples of such loss-making firms. What has changed over time? When and why did losses lose their meaning? The authors’ series of new research papers provide some answers, guiding managers to make the right investments: those that produce delayed but real profits — not just those that produce short-term accounting profits but decimate shareholder wealth in long run.
In 1979, psychologists Daniel Kahneman and Amos Tversky famously posited that losses loom larger than gains in human decision-making. For example, a dollar of loss affects our behavior more than a dollar of profits . Likewise, when a firm announces losses, its stock price declines more dramatically than it increases for the same dollar amount of profits. Investors abandon and lenders tend to stop financing loss-making firms , which then start restructuring their business lines and laying off employees. Some firms go even further, conducting M&A transactions without substance and “managing earnings” to report profits instead of a loss.
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When my husband and I decided to upgrade to a king-sized bed, we did tons of research on mattresses. We labored over the decision for weeks, read hundreds of reviews, and toured dozens of showrooms before landing on a Sealy Posturepedic Hybrid Mattress. As a couple, it's been our most expensive purchase to date, at $2,499, which was much more than we intended to spend. But the splurge felt worth it, and since purchasing it, I've no longer woken up when my husband moves around.
Because we went over budget, we decided to be frugal when it came to a bed frame. We chose a stylish but cheap upholstered frame online and ignored negative reviews thinking, how bad could it be?
Pretty bad. It squeaked at the slightest movement, felt flimsy, and was labor-intensive to build. After a few months, it was proving detrimental to our sleep, so we decided to look for something well-made that would last for years. I began researching high-quality bed frames online and started seeing ads for Thuma on Instagram.
Each bed is crafted from solid, repurposed wood. No MDF or veneers are used and all the pieces interlock, requiring just two hand-tightened screws.
I was intrigued by Thuma's claim that it could be built in just minutes (the former frame took hours, not including the resulting bickering), with interlocking solid wood made from Japanese joinery techniques and no need for tools or hardware. The rounded corners were designed to protect shins, and the bed's cushioned slots and "pillow board" (a low, padded headboard) aided in noise reduction.
Everything about it seemed thoughtful, and 17,000 online reviews, averaging 4.9 out of 5 stars, raved about the quality of craftsmanship and functional style. In addition, Thuma offers a 100-night return policy and a lifetime warranty.
We decided to try the bed frame for these reasons, as well as the fact that it had the exact minimalist, midcentury-modern look we wanted. Plus, the low-profile platform eliminated the need for a box spring and still offered 9-inch clearance for storage underneath.
The company sent me a free review unit to test out, and after sleeping on it for four months before I moved into a different space, I can say that I love the frame just as much as my mattress. It was so simple to build, is beautifully made, and doesn't make a squeak. I've never slept better.
That's not to say I wasn't skeptical. A claim of assembly in "five-ish" minutes without tools seemed too good to be true. Could a couple really build a bed together with no fighting at all?
Our first impression was strong. As an apartment dweller, I appreciated that the bed arrived in three boxes, designed to fit up stairwells and through hallways.
Inside were the frame pieces, slats, pillow board, and legs with pre-applied cork-padded bottoms for floor protection and cushioning. The copy was clever, and a small smile during any type of furniture assembly goes a long way.
I decided to time how long it took to build the bed. I spent about 15 minutes just getting everything out of the boxes and arranged in order of assembly, which is what the instructions said to do.
Significant minutes could have been shaved off had each frame bar been labeled like the legs were. This would have helped us know if we were laying the pieces out correctly. Instead, we spent a lot of time second-guessing ourselves.
I would suggest opening the boxes in another room if you're short on space. We opened everything in the room where we would be building and spent extra time moving around our mess.
We were immediately impressed once the frame was in place and ready to put together. Each bar locked into the adjacent one through the leg without any screws, drilling, or hardware. It really did take just minutes to put the base together. The wood was solid and smooth, and the bed felt sturdy and well-crafted.
Two hand-tightened screws then went in on each end; no screwdriver was necessary. A word of warning: The screws came in an unlabeled box, and we almost accidentally threw them away.
Next came the slats, which locked into place and were cushioned and lined with eco-friendly felt made from recycled plastics for durability and sound reduction. They, too, felt solid, unlike our rickety previous model.
From the time we laid out all the materials to this point, exactly 15 minutes went by. It took about 10 more minutes to place the mattress back on top, make the bed, and position the pillow board, bringing our total assembly time to half an hour. While that's a generous interpretation of "five-ish," it was still very quick.
The Thuma bed frame is made of upcycled with a protective scratch-resistant finish and is available in four finishes: natural, walnut, espresso, and gray. The pillow board comes in four neutral colors too and is made of 100% polyester pebbled linen-weave or boucle with tapered foam filling. The covers are also sold separately, so you can swap colors when the mood strikes. They're also washable for easy cleaning. Since I initially tried the bed, Thuma has introduced additional headboard and cushion options and developed add-ons like an under-bed storage drawer.
The pillow board sits comfortably on the back of the frame between the mattress and the wall and is not attached to the bed in any way. It's an interesting alternative to a more traditional headboard, and it also reduces noise, thanks to the padding. The low profile can be covered by pillows or kept visible as a design accent.
My husband and I like the look of a headboard and didn't want that lost behind our pillows. Even while visible, Thuma's pillow board still sits quite low and doesn't feature prominently. We've tried positioning it higher, which works as a temporary fix, but one side still falls occasionally. The wooden headboard configuration does sit four inches higher, however.
Ultimately, I found the Thuma bed frame to be well-crafted and thoughtfully designed. It's solid, eco-friendly, and beautiful.
Since putting it together, we've taken it apart and reassembled it again while moving apartments, and it was just as seamless and easy. It's been over two years, and the frame has held up very well.
Starting at $795 for just the base and stretching up to $2,395 with a headboard and cushion (the pillowboard configuration I tried is $1,395), it's certainly an expensive investment and a high-end alternative to its more affordable competitors.
But I'm confident it's a piece of furniture we'll have for many years to come, which, as I've learned, you can't always guarantee.
You can purchase logo and accolade licensing to this story here . Disclosure: Written and researched by the Insider Reviews team. We highlight products and services you might find interesting. If you buy them, we may get a small share of the revenue from the sale from our partners. We may receive products free of charge from manufacturers to test. This does not drive our decision as to whether or not a product is featured or recommended. We operate independently from our advertising team. We welcome your feedback. Email us at [email protected] .
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Title: emt: a novel transformer for generalized cross-subject eeg emotion recognition.
Abstract: Integrating prior knowledge of neurophysiology into neural network architecture enhances the performance of emotion decoding. While numerous techniques emphasize learning spatial and short-term temporal patterns, there has been limited emphasis on capturing the vital long-term contextual information associated with emotional cognitive processes. In order to address this discrepancy, we introduce a novel transformer model called emotion transformer (EmT). EmT is designed to excel in both generalized cross-subject EEG emotion classification and regression tasks. In EmT, EEG signals are transformed into a temporal graph format, creating a sequence of EEG feature graphs using a temporal graph construction module (TGC). A novel residual multi-view pyramid GCN module (RMPG) is then proposed to learn dynamic graph representations for each EEG feature graph within the series, and the learned representations of each graph are fused into one token. Furthermore, we design a temporal contextual transformer module (TCT) with two types of token mixers to learn the temporal contextual information. Finally, the task-specific output module (TSO) generates the desired outputs. Experiments on four publicly available datasets show that EmT achieves higher results than the baseline methods for both EEG emotion classification and regression tasks. The code is available at this https URL .
Comments: | 11 pages, 5 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible |
Subjects: | Machine Learning (cs.LG); Signal Processing (eess.SP) |
Cite as: | [cs.LG] |
(or [cs.LG] for this version) | |
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Mr. Bowman’s win in 2020 seemed to herald an ascendant progressive movement. In 2024, the center is regaining power.
By Jesse McKinley and Nicholas Fandos
Representative Jamaal Bowman’s upset win in a 2020 Democratic primary in the New York suburbs was heralded by the left as proof of its electoral ascent in American politics.
Four years later, Mr. Bowman’s decisive loss on Tuesday will soon brand him with a more ignominious distinction: the first member of the House’s left-leaning “Squad” to be ousted from office.
The congressman was weighed down by a unique collection of baggage, including a guilty plea to a misdemeanor for pulling a House fire alarm last year. And he faced record-shattering spending by political groups furious over his criticism of Israel.
But his defeat in one of the nation’s most closely watched primaries drove home an unmistakable reality: Even at a moment when the war in Gaza has re-energized progressive activism, many of the left’s candidates are no longer gaining ground in major races, and in some cases they have started losing it.
In party primaries and special elections from Oregon to New Jersey , moderates seemed to be regaining their footing, often by explicitly positioning themselves to the right of their Democratic opponents on immigration, foreign policy and public safety. President Biden has also tacked rightward on key issues like immigration.
And in Missouri, another member of the “Squad,” Representative Cori Bush, is in danger of losing an August primary, where many of the same forces that helped defeat Mr. Bowman are already at play.
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Migrations of the intertropical convergence zone (ITCZ) have significant impacts on tropical climate and society. Here we examine the ITCZ migration caused by CO 2 increase using climate model simulations. During the first one to two decades, we find a northward ITCZ displacement primarily related to an anomalous southward atmospheric cross-equatorial energy transport. Over the next hundreds or thousands of years, the ITCZ moves south. This long-term migration is linked to delayed surface warming and reduced ocean heat uptake in the Southern Ocean, which alters the interhemispheric asymmetry of ocean heat uptake and creates a northward atmospheric cross-equatorial energy transport anomaly. The southward ITCZ shift, however, is reduced by changes in the net energy input to the atmosphere at the equator by about two-fifths. Our findings highlight the importance of Southern Ocean heat uptake to long-term ITCZ evolution by showing that the (quasi-)equilibrium ITCZ response is opposite to the transient ITCZ response.
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Data availability.
CMIP5 model data are available at https://esgf-node.llnl.gov/projects/cmip5/ . CMIP6 model data are available at https://esgf-node.llnl.gov/projects/cmip6/ . LongRunMIP data are available at https://www.longrunmip.org . The processed variables to generate Figs. 1 – 6 are available via Zenodo at https://zenodo.org/records/11075601 (ref. 57 ) in the form of netcdf files.
Figures 1 – 6 were generated using NCL v.6.5.0 (ref. 56 ). The codes to generate Figs. 1 – 6 are available via Zenodo at https://zenodo.org/records/11075601 (ref. 57 ) in the form of NCL files.
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This study was supported by the US National Science Foundation (NSF OCE-2123422, AGS-2053121 and AGS-2237743) awarded to W.L. who was also supported by the UC Regents Faculty Development Award. C.L. was supported by the Clusters of Excellence CLICCS (EXC2037), University of Hamburg, funded by the German Research Foundation (DFG). M.R. was supported by NSF AGS-2233673.
Authors and affiliations.
Department of Earth Sciences and Planetary Sciences, University of California Riverside, Riverside, CA, USA
Wei Liu, Shouwei Li & Antony P. Thomas
Max Planck Institute for Meteorology, Hamburg, Germany
Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA
Maria Rugenstein
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W.L. conceived the study and wrote the original draft of the paper. S.L. and A.P.T. performed the analysis. C.L. and M.R. provided the data. All authors contributed to interpreting the results and made substantial improvements to the paper.
Correspondence to Wei Liu .
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The authors declare no competing interests.
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Extended data fig. 1 maps of toa radiation changes due to radiative feedback..
( a-c ) Maps of TOA radiation changes (relative to preindustrial times, in units of W/m 2 ) due to the cloud feedback in the CO 2 quadrupling simulations for the multimodel means of (a) CMIP5/6 and (b) LongRunMIP models over years 1–20, and (c) LongRunMIP models for the difference between years 981–1000 and years 1–20. ( d-f ) Same as (a-c) but for the water vapor feedback. ( g-i ) Same as (a-c) but for the albedo feedback. ( j-l ) Same as (a-c) but for the temperature feedback. The base map is from NCAR Command Language map outline databases.
Maps of changes (relative to preindustrial times, in units of W/m 2 ) in the net ( a ) TOA radiation and ( b ) surface energy flux in the CO 2 quadrupling simulation for the multimodel mean of CMIP5/6 models over years 1–20. The base map is from NCAR Command Language map outline databases.
(a,b) Maps of (a) surface (shortwave plus longwave radiation energy flux and (b) surface turbulent (sensible plus latent) heat flux changes (relative to preindustrial times, in units of W/m 2 ) in the CO 2 quadrupling simulation for the multimodel mean of CMIP5/6 models over years 1–20. (c,d) Same as (a,b) but for LongRunMIP models. (e,f) Same as (c,d) but for years 981–1000. ( g,h ) Same as (c,d) but for the differences between years 981–1000 and years 1–20. The base map is from NCAR Command Language map outline databases.
Changes (relative to preindustrial times, multimodel mean, MMM, dot; intermodel spread, one standard derivation (1 SD) among models, bars) in the atmospheric cross-equatorial energy transport (purple) and interhemispheric asymmetry (Southern minus Northern Hemisphere, Methods ) of the net TOA radiation (red), net surface energy flux (blue), surface turbulent heat flux (sensible plus latent, turquoise blue), and surface radiation energy flux (shortwave plus longwave, brown) in the CO 2 quadrupling simulation by LongRunMIP_sub models over years 1–20 and years 3981–4000, and for the difference between the two periods (years 3981–4000 minus years 1–20).
(a,b) Maps of changes (relative to preindustrial times, in units of W/m 2 ) in the net (a) TOA radiation and (b) surface energy flux in the CO 2 quadrupling simulation for the multimodel mean of LongRunMIP_sub models over years 1–20. (c,d) Same as (a,b) but for years 3981–4000. (e,f) The differences between the two periods for the net (e) TOA radiation and (f) surface energy flux (years 3981–4000 minus years 1–20). (g,h) Same as (e,f) but for surface (shortwave plus longwave) radiation energy flux and surface turbulent (sensible plus latent) heat flux. The base map is from NCAR Command Language map outline databases.
SST changes (relative to preindustrial times, in units of K) in the CO 2 quadrupling simulation for the multimodel mean of LongRunMIP_sub models over (a) years 1–20 and (b) years 3981–4000, respectively. (c) Same as (a) but for the difference between years 3981–4000 and years 1–20. The base map is from NCAR Command Language map outline databases.
(a) Changes (relative to preindustrial times) in AMOC strength (multimodel mean, black; intermodel spread, one standard derivation among models, grey) in the CO 2 quadrupling simulation by LongRunMIP models except ECHAM5-MPIOM. The AMOC strength is defined as the maximum in the meridional overturning stream function below 500 m in the North Atlantic. The first 20-year average of AMOC strength is plotted at year 10 in the form of multimodel mean (MMM, dot) ± one standard deviation (1 SD) among models (bars). (b) Same as (a) but for surface energy fluxes integrated over 30°N–65°N (multimodel mean, red; intermodel spread, light red), over the Pacific and land areas (multimodel mean, orange; intermodel spread, yellow) and the Atlantic area (multimodel mean, green; intermodel spread, light green) within 30°N–65°N. Note that the first 20-year average of surface energy fluxes integrated over the Pacific and land areas with 30°N–65°N is plotted at year 9 for a clear visualization. (c) Same as (a) but for changes in surface energy fluxes integrated over 30°N–65°N (multimodel mean, red; intermodel spread, one standard derivation among models, light red), 30°S–65°S (multimodel mean, blue; intermodel spread, light blue) and the difference (30°S–65°S minus 30°N–65°N, multimodel mean, black; intermodel spread, grey).
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Liu, W., Li, S., Li, C. et al. Contrasting fast and slow intertropical convergence zone migrations linked to delayed Southern Ocean warming. Nat. Clim. Chang. (2024). https://doi.org/10.1038/s41558-024-02034-x
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DOI : https://doi.org/10.1038/s41558-024-02034-x
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