Understanding the key properties of complex systems can help us clarify and deal with many new and existing global challenges, from pandemics to poverty . . . A recent study in Nature Physics found transitions to orderly states such as schooling in fish (all fish swimming in the same direction), can be caused, paradoxically, by randomness, or ‘noise’ feeding back on itself. That is, a misalignment among the fish causes further misalignment, eventually inducing a transition to schooling. Most of us wouldn’t guess that noise can produce predictable behaviour. The result invites us to consider how technology such as contact-tracing apps, although informing us locally, might negatively impact our collective movement. If each of us changes our behaviour to avoid the infected, we might generate a collective pattern we had aimed to avoid higher levels of interaction between the infected and susceptible, or high levels of interaction among the asymptomatic.
Complex systems also suffer from a special vulnerability to events that don’t follow a normal distribution or ‘bell curve’. When events are distributed normally, most outcomes are familiar and don’t seem particularly striking. Height is a good example: it’s pretty unusual for a man to be over 7 feet tall; most adults are between 5 and 6 feet, and there is no known person over 9 feet tall. But in collective settings where contagion shapes behaviour – a run on the banks, a scramble to buy toilet paper – the probability distributions for possible events are often heavy-tailed. There is a much higher probability of extreme events, such as a stock market crash or a massive surge in infections. These events are still unlikely, but they occur more frequently and are larger than would be expected under normal distributions.
What’s more, once a rare but hugely significant ‘tail’ event takes place, this raises the probability of further tail events. We might call them second-order tail events; they include stock market gyrations after a big fall and earthquake aftershocks. The initial probability of second-order tail events is so tiny it’s almost impossible to calculate – but once a first-order tail event occurs, the rules change, and the probability of a second-order tail event increases.
The dynamics of tail events are complicated by the fact that they result from cascades of other unlikely events. When COVID-19 first struck, the stock market suffered stunning losses followed by an equally stunning recovery. Some of these dynamics are potentially attributable to former sports bettors, with no sports to bet on, entering the market as speculators rather than investors. The arrival of these new players might have increased inefficiencies and allowed savvy long-term investors to gain an edge over bettors with different goals. . . .
One reason a first-order tail event can induce further tail events is that it changes the perceived costs of our actions and changes the rules that we play by. This game-change is an example of another key complex systems concept: nonstationarity. A second, canonical example of nonstationarity is adaptation, as illustrated by the arms race involved in the coevolution of hosts and parasites [in which] each has to ‘run’ faster, just to keep up with the novel solutions the other one presents as they battle it out in evolutionary time.
All of the following inferences are supported by the passage EXCEPT that:
Show Hint
- examples like runs on banks and toilet paper scrambles illustrate how contagion can amplify local choices into system-wide cascades that surprise participants and lead to patterns they did not intend to create.
- learning can change the rules that actors face. So, a rare shock can alter payoffs and raise the odds of subsequent large disturbances within the same system, which supports the idea of second-order tail events.
- heavy-tailed events make extreme outcomes more frequent and larger than bell curve expectations. This complicates forecasting and risk management in collective settings shaped by contagion and copying behaviour.
- the text attributes the COVID-19 pandemic rebound in financial markets solely to displaced sports bettors and treats their entry as the overriding cause of the rapid recovery across assets and time horizons.
The Correct Option is D
Approach Solution - 1
To solve this question, we need to identify which inference is not supported by the given passage. This involves checking each option against the information provided in the passage.
- The passage describes how runs on banks and toilet paper scrambles can amplify local choices into system-wide cascades through contagion shapes behavior. This directly supports the first option.
- The passage also explains that learning and adaptation change the rules of the systems and can lead to second-order tail events, supporting the second option.
- The third option is supported by the passage as it discusses how heavy-tailed events deviate from bell curve expectations, affecting extreme outcomes' frequency and size in collective settings.
- The fourth option states that the text attributes the COVID-19 pandemic rebound in financial markets solely to displaced sports bettors. The passage mentions former sports bettors entering markets as speculators but does not claim this was the sole or overriding cause of the financial market rebound during COVID-19. Hence, the fourth option is not supported by the passage.
Therefore, the correct answer is the fourth option, as it incorrectly enlarges the role of displaced sports bettors as the single cause of the pandemic rebound.
Approach Solution -2
Step 1: Understand what the passage actually says about each option.
Option (1): Supported.
The passage explicitly uses runs on banks and toilet paper buying to illustrate contagion-driven cascades that produce extreme, unintended system-wide behaviour.
Hence, this inference is supported.
Option (2): Supported.
The passage discusses no stationarity — how a first-order tail event changes the rules of the system, altering perceived costs and raising the probability of a second-order tail event.
This matches the inference stated.
Option (3): Supported.
The passage stresses that heavy-tailed distributions produce more frequent and larger extreme outcomes than normal distributions, especially in contagion-driven systems.
This is directly stated and therefore supported.
Option (4): Not supported (EXCEPT).
The passage gives the example that former sports bettors might have contributed to market inefficiencies and movements during the COVID–19 rebound.
It does not claim:
that they were the sole cause, nor
that their entry was the overriding cause of market recovery.
The authors clearly treat this factor as one potential contributor, not the decisive explanation.
Thus, Option (4) states something the passage does not support and is therefore the correct answer to an EXCEPT question.
Which one of the options below best summarises the passage?
Show Hint
- The passage explains how social outcomes generally follow normal distributions. So, extreme events are negligible, and policy should stabilise averages rather than learn from large shocks in fast-changing collective settings.
- The passage explains how noise can create order, then shows why complex systems with contagion are vulnerable to heavy-tailed cascades. It also explains why early shocks change rules through nonstationarity with a market illustration during the COVID-19 disruption.
- The passage explains how speculative entrants always produce inefficiency after health shocks. Therefore, long-term investors invariably profit when new participants push prices away from fundamentals under pandemic conditions and comparable crises.
- The passage explains how nonstationarity works in evolutionary biology and rejects applications in markets or public health because adaptation is exclusive to parasite-host systems and cannot arise in technology-mediated social dynamics.
The Correct Option is B
Approach Solution - 1
The question requires us to identify the best summary of the provided passage. To determine the correct option, we will carefully analyze each part of the passage and compare it with the given options.
The passage discusses how understanding complex systems can illuminate global challenges. It particularly focuses on how noise can paradoxically create order in such systems. It mentions the example of fish schooling to illustrate how randomness can lead to predictable patterns. The text also highlights the vulnerability of complex systems to events that do not follow a normal distribution, such as stock market crashes and pandemics, which have 'heavy-tailed' distributions where extreme events are more probable.
Additionally, the passage explains that once a first-order 'tail event' occurs, it increases the likelihood of further tail events. This idea is expanded with the example of the COVID-19 pandemic and its impact on the stock market, where the entry of new, speculative players created inefficiencies. It concludes by discussing the concept of nonstationarity, meaning changes in conditions can alter rules, similar to evolutionary adaptations.
We will now analyze the given options:
- Option 1: This option discusses social outcomes following normal distributions and suggests that policy should stabilize averages. The passage, however, highlights how complex systems can deviate from normal distributions, particularly in contagion contexts. Thus, this option does not capture the essence of the passage.
- Option 2: This option accurately captures the main ideas in the passage. It mentions how noise can create order, the vulnerability of complex systems to 'heavy-tailed' cascades, and how early shocks alter rules through nonstationarity. It also references the market illustration during COVID-19, aligning well with the passage’s content.
- Option 3: This option focuses on speculative entrants and their impact post-health shocks, with a claim about long-term investors. While the passage does mention market inefficiencies and new entrants during COVID-19, the essence of the passage lies more broadly on complex system dynamics and nonstationarity, which this option misses.
- Option 4: This option claims nonstationarity is mainly applicable to biological systems and rejects its application to markets or public health, contradicting the passage's explanation of rule changes in markets due to nonstationarity during COVID-19. This does not align well with the passage’s discussion.
After evaluating all options, Option 2 is the most accurate summary of the passage as it comprehensively encompasses all the key concepts discussed, including the role of randomness, the nature of heavy-tailed events, and the influence of nonstationarity with real-world examples.
Approach Solution -2
Step 1: Identify the major themes of the passage.
The passage covers three core ideas:
Noise (randomness) in complex systems can surprisingly create orderly collective behaviour.
Complex systems with contagion dynamics are prone to heavy-tailed cascades and extreme events.
Nonstationarity explains how early shocks change the rules of the system, illustrated with stock-market behaviour during COVID-19.
A correct summary must incorporate all three ideas.
Step 2: Evaluate each option.
Option (1): Incorrect.
This contradicts the passage. The passage explicitly argues that complex systems do not follow normal distributions and that extreme events are important, not negligible.
Option (2): Correct.
This option accurately reflects:
the surprising emergence of order from noise,
the vulnerability of contagion-driven systems to heavy-tailed events,
the idea of nonstationarity and how early shocks change rules,
the COVID-19 market example used in the passage.
It is the only option that captures the full scope of the passage.
Option (3): Incorrect.
This overstates the passage. The text says speculative entrants might have contributed to market movements; it emphatically does not say that speculative entrants always cause inefficiency or that long-term investors always profit.
Option (4): Incorrect.
This misrepresents the passage entirely. The passage does not reject applying nonstationarity to markets or public health; in fact, it explicitly applies it to those contexts. The parasite–host example is merely an analogy.
Thus, the best summary is Option (2).
Which one of the following observations would most strengthen the passage’s claim that a first-order tail event raises the probability of further tail events in complex systems?
Show Hint
- In epidemic networks, initial super-spreading episodes are isolated spikes after which outbreak sizes match the baseline distribution from independent contact models across comparable cities with no rise in the frequency or size of later extreme clusters.
- River discharge records show water levels fit a normal distribution with thin tails that match laboratory data, regardless of storms or floods.
- After a major equity crash, researchers find dense clusters of large daily moves for several weeks, with extreme days occurring far more often than in normal circumstances for assets with customarily low volatility profiles.
- Following large earthquakes, regional seismic activity returns to baseline within hours with no aftershock sequence once data are adjusted for reporting effects, which suggests independence across events rather than any elevation in subsequent tail probabilities.
The Correct Option is C
Approach Solution - 1
The question is about identifying which observation most supports the passage's assertion that in complex systems, a first-order tail event increases the probability of subsequent tail events. Let us analyze each option to determine which one aligns with this claim.
- Option 1:
In epidemic networks, initial super-spreading episodes are isolated spikes after which outbreak sizes match the baseline distribution from independent contact models across comparable cities with no rise in the frequency or size of later extreme clusters.
This option indicates that after an initial spike, subsequent events do not suggest an increased probability of further extreme events. Hence, it does not support the claim. - Option 2:
River discharge records show water levels fit a normal distribution with thin tails that match laboratory data, regardless of storms or floods.
This option describes a normal distribution where extreme events are rare, and it does not demonstrate cascades of extreme events as expected in complex systems. Therefore, it does not support the claim. - Option 3:
After a major equity crash, researchers find dense clusters of large daily moves for several weeks, with extreme days occurring far more often than in normal circumstances for assets with customarily low volatility profiles.
This option illustrates a scenario where a major event leads to numerous subsequent extreme events, aligning with the passage's argument that a first-order tail event raises the probability of further tail events. Thus, it supports the claim effectively. - Option 4:
Following large earthquakes, regional seismic activity returns to baseline within hours with no aftershock sequence once data are adjusted for reporting effects, which suggests independence across events rather than any elevation in subsequent tail probabilities.
This option suggests that subsequent events are independent of the first-order event, indicating no increased probability of further tail events. Hence, it does not support the claim.
Therefore, the correct answer is Option 3:
After a major equity crash, researchers find dense clusters of large daily moves for several weeks, with extreme days occurring far more often than in normal circumstances for assets with customarily low volatility profiles.
This option supports the passage's assertion by illustrating that after a first-order tail event (equity crash), there is an increased probability and occurrence of further tail events.
Approach Solution -2
Step 1: Recall the passage’s claim.
The passage states that:
A first-order tail event (a large, rare shock)
raises the probability of second-order tail events,
meaning that after the initial shock, extreme events become more frequent.
Thus, we must choose the option showing clusters of extreme events after an initial extreme event.
Step 2: Evaluate each option.
Option (1): Weakens the claim.
Says tail events remain isolated with no increase afterward — the opposite of what we want.
Option (2): Irrelevant.
Describes a normal distribution with thin tails; nothing about successive extreme events.
Option (3): Strongly supports the claim.
After a major stock market crash, there are:
dense clusters of large daily moves,
extreme events appearing far more often,
a sustained period of elevated tail risk.
This directly confirms that a first-order tail event increases the probability of further tail events.
Option (4): Weakens the claim.
Says seismic activity returns to baseline with no aftershocks — contradicting the idea of second-order tail events.
Thus the best answer is Option (3).
The passage suggests that contact-tracing apps could inadvertently raise risky interactions by altering local behaviour. Which one of the assumptions below is most necessary for that suggestion to hold?
Show Hint
- Most users uninstall apps within a week, which leaves only highly exposed individuals participating. This neutralises any systematic bias in routing decisions and prevents any predictable change in aggregate contact patterns.
- Individuals base movement choices partly on observed infections and on the behaviour of others. So, local responses interact, which turns many small adjustments into large scale patterns that can frustrate the intended aim of risk reduction.
- App alerts always include precise location to within one metre and deliver real time updates for all users, which ensures that the data feed is perfectly accurate regardless of privacy settings, power limits, or network conditions.
- Urban networks have uniform traffic conditions at all hours, which allows perfectly predictable routing independent of personal choices, social signals, or crowd reactions and, therefore, makes interdependence negligible in city movement decisions.
The Correct Option is B
Approach Solution - 1
To solve this problem, we need to determine which assumption is most crucial for the suggestion that contact-tracing apps could inadvertently increase risky interactions by affecting local behavior.
The passage highlights the complexity of systems and how small individual changes can collectively contribute to larger patterns. Particularly, it focuses on how technological interventions like contact-tracing apps can have unintended effects on group behavior.
The suggested phenomenon relates to the idea that individual behaviors influenced by these apps may inadvertently cause an increase in risky interactions, which is certainly not the intended purpose of these apps.
Now, let’s consider the provided options:
- The first option discusses users uninstalling apps, leading to only highly exposed individuals using them. However, this largely focuses on individual participation rather than explaining how behavior changes could collectively influence aggregate contact patterns.
- The second option posits that individuals base their movement decisions partly on observed infections and the behavior of others, leading to interaction of local responses. This can lead to small adjustments transforming into broader patterns, potentially frustrating the aim of risk reduction. This option directly reflects the passage's discussion of how changes in individual behavior might unpredictably affect collective patterns.
- The third option ensures precise app accuracy, which does not directly tie into behavior changes, but rather the technical precision of data, hence it's less relevant to the suggested behavioral consequences.
- The fourth option describes uniform traffic conditions independent of personal choice or social response, which doesn't align with the idea of behavior-based interaction alterations.
Given the context, the assumption that is most crucial is the second option. It aligns with the passage's emphasis on complex system dynamics where local, behavior-driven interactions can inadvertently lead to larger, unintended consequences, such as increased risky interactions.
Conclusion: The assumption that "Individuals base movement choices partly on observed infections and on the behavior of others. So, local responses interact, which turns many small adjustments into large scale patterns that can frustrate the intended aim of risk reduction." is the most necessary for the suggestion in the passage to hold.
Approach Solution -2
Step 1: Recall the passage’s claim. & nbsp;
The passage argues that contact-tracing apps, though designed to help individuals avoid risk, could inadvertently create collective patterns that increase risky interactions.
This can only happen if:
- Individual behavioural changes interact, and
- Small local adjustments cascade into large-scale patterns.
This is the hallmark of a complex system with interdependent behaviour.
Step 2: Identify the assumption required for this mechanism to work.
Option (2) states exactly this assumption:
\(\textit{Individuals change behaviour based on infection data and the behaviour of others, and these interactions scale up.}\)
Without this interdependence, individual actions would stay local, and no large-scale unintended pattern could emerge — which the passage says can happen.
Thus, (2) is the necessary assumption.
Why the others are wrong:
- Option (1): Talks about uninstalling; irrelevant to behavioural cascades.
- Option (3): Assumes perfect accuracy of apps; the passage never requires this.
- Option (4): Assumes uniform traffic and no interdependence — this contradicts the very idea needed for the unintended collective pattern.
Conclusion:
Therefore, the assumption most necessary for the passage’s argument is Option (2).
Top Questions on Reading Comprehension
- Shown below are letters ‘e’ taken from four popular logos, arranged in a sequence. Which of the options is the correct sequence?
- UCEED - 2026
- English Language Comprehension
- Reading Comprehension
- Shown below are four options, each showing consecutive frames representing the movement of a pendulum of an old-style wall clock for an animation movie. Which is the correct option?
- UCEED - 2026
- English Language Comprehension
- Reading Comprehension
- Acrucial moderating factor in how people experience comparisons is self-esteem. Individuals with high self-esteem are more likely to interpret upward comparison as informative rather than threatening. They are more resilient in the face of others’ success and more likely to believe they can reach their own goals. In contrast, people with low self-esteem are more prone to interpret comparison as judgment, reinforcing negative self-views and triggering feelings of inadequacy.
This dynamic creates a self-reinforcing loop. People with high self-esteem are less vulnerable to upward comparison, which intensifies those doubts. Those with a secure sense of self are more likely to use comparison as a learning tool. The same external stimulus—a colleague’s achievements, a friend’s popularity—can have radically different effects depending on internal stability.
Self-esteem also influences how people choose their comparison targets. Research has found that individuals often engage in “selective comparison,” seeking out those who confirm their existing beliefs about themselves. This can become a subtle form of self-sabotage. Someone who feels unworthy may subconsciously seek out targets that reinforce that sense, perpetuating a narrative of inferiority. One of the most promising antidotes to social comparison is temporal comparison—evaluating oneself not against others, but against one’s own past. This method has been shown to increase motivation and satisfaction, especially when individuals can see concrete progress. Temporal comparison activates the same reward circuits as social comparison but avoids the threat systems associated with social ranking. It also reinforces agency: individuals focus on what they can control and improve rather than what others control. In therapeutic and coaching settings, temporal comparison is used to help clients build self-efficacy and track growth over time.
Moreover, people who focus on self-improvement rather than social dominance are less likely to fall into cycles of envy or self-pity. They can still use others as inspiration, but they do so without attaching their self-worth to the outcome. This is not to say they never compare—but that they focus on learning, rather than judgment. The most skilful approach to comparison may lie in eliminating it, but in reframing it as feedback. When we interpret comparison as information rather than a verdict, we can ask, “What can I learn from this?” This shift turns comparison into a growth tool. Teachers mentor their students, not as rivals. Psychologists emphasize that the key variable here is mindset.
A fixed mindset sees comparison as a threat. If someone else is better, it means we are worse. A growth mindset sees comparison as a map. If someone else has reached a certain level, it means the path exists. This reframing is not just a cognitive trick. It changes the emotional tone of comparison, making it more likely to inspire than to wound. Reframing also requires emotional regulation—the ability to notice an initial pang of envy or shame without reacting impulsively. With practice, individuals can learn to pause, reflect, and reinterpret their emotional responses. Over time, this builds resilience and self-trust, allowing comparison to become a learning tool rather than a cage.- XAT - 2026
- Verbal and Logical Ability
- Reading Comprehension
When people who are talking don’t share the same culture, knowledge, values, and assumptions, mutual understanding can be especially difficult. Such understanding is possible through the negotiation of meaning. To negotiate meaning with someone, you have to become aware of and respect both the differences in your backgrounds and when these differences are important. You need enough diversity of cultural and personal experience to be aware that divergent world views exist and what they might be like. You also need the flexibility in world view, and a generous tolerance for mistakes, as well as a talent for finding the right metaphor to communicate the relevant parts of unshared experiences or to highlight the shared experiences while demphasizing the others. Metaphorical imagination is a crucial skill in creating rapport and in communicating the nature of unshared experience. This skill consists, in large measure, of the ability to bend your world view and adjust the way you categorize your experiences. Problems of mutual understanding are not exotic; they arise in all extended conversations where understanding is important.
When it really counts, meaning is almost never communicated according to the CONDUIT metaphor, that is, where one person transmits a fixed, clear proposition to another by means of expressions in a common language, where both parties have all the relevant common knowledge, assumptions, values, etc. When the chips are down, meaning is negotiated: you slowly figure out what you have in common, what it is safe to talk about, how you can communicate unshared experience or create a shared vision. With enough flexibility in bending your world view and with luck and charity, you may achieve some mutual understanding.
Communication theories based on the CONDUIT metaphor turn from the pathetic to the evil when they are applied indiscriminately on a large scale, say, in government surveillance or computerized files. There, what is most crucial for real understanding is almost never included, and it is assumed that the words in the file have meaning in themselves—disembodied, objective, understandable meaning. When a society lives by the CONDUITmetaphor on a large scale, misunderstanding, persecution, and much worse are the likely products.- XAT - 2026
- Verbal and Logical Ability
- Reading Comprehension
Later, I realized that reviewing the history of nuclear physics served another purpose as well: It gave the lie to the naive belief that the physicists could have come together when nuclear fission was discovered (in Nazi Germany!) and agreed to keep the discovery a secret, thereby sparing humanity such a burden. No. Given the development of nuclear physics up to 1938, development that physicists throughout the world pursued in all innocence of any intention of finding the engine of a new weapon of mass destruction—only one of them, the remarkable Hungarian physicist Leo Szilard, took that possibility seriously—the discovery of nuclear fission was inevitable. To stop it, you would have had to stop physics. If German scientists hadn’t made the discovery when they did, French, American, Russian, Italian, or Danish scientists would have done so, almost certainly within days or weeks. They were all working at the same cutting edge, trying to understand the strange results of a simple experiment bombarding uranium with neutrons. Here was no Faustian bargain, as movie directors and other naifs still find it intellectually challenging to imagine. Here was no evil machinery that the noble scientists might hide from the problems and the generals. To the contrary, there was a high insight into how the world works, an energetic reaction, older than the earth, that science had finally devised the instruments and arrangements to coart forth. “Make it seem inevitable,” Louis Pasteur used to advise his students when they prepared to write up their discoveries. But it was. To wish that it might have been ignored or suppressed is barbarous. “Knowledge,” Niels Bohr once noted, “is itself the basis for civilization.” You cannot have the one without the other; the one depends upon the other. Nor can you have only benevolent knowledge; the scientific method doesn’t filter for benevolence. Knowledge has consequences, not always intended, not always comfortable, but always welcome. The earth revolves around the sun, not the sun around the earth. “It is a profound and necessary truth,” Robert Oppenheimer would say, “that the deep things in science are not found because they are useful; they are found because it was possible to find them.”
...Bohr proposed once that the goal of science is not universal truth. Rather, he argued, the modest but relentless goal of science is “the gradual removal of prejudices.” The discovery that the earth revolves around the sun has gradually removed the prejudice that the earth is the center of the universe. The discovery of microbes is gradually removing the prejudice that disease is a punishment from God. The discovery of evolution is gradually removing the prejudice that Homo sapiens is a separate and special creation.- XAT - 2026
- Verbal and Logical Ability
- Reading Comprehension
Questions Asked in CAT exam
- The passage given below is followed by four summaries. Choose the option that best captures the essence of the passage.
In the dynamic realm of creativity, artists often find themselves at the crossroads between drawing inspiration from diverse cultures and inadvertently crossing into the territory of cultural appropriation. Inspiration is the lifeblood of creativity, driving artists to create works that resonate across borders. In a globalized era of the modern world, artists draw from a vast array of cultural influences. When approached respectfully, inspiration becomes a bridge, fostering understanding and appreciation of cultural diversity. However, the line between inspiration and cultural appropriation can be thin and easily blurred.
Cultural appropriation occurs when elements from a particular culture are borrowed without proper understanding, respect, or acknowledgment. This leads to the commodification of sacred symbols, the reinforcement of stereotypes, and the erasure of the cultural context from which these elements originated. It is essential to recognize that the impact of cultural appropriation extends beyond the realm of artistic expression, influencing societal perceptions and perpetuating power imbalances.- CAT - 2025
- Para Summary
- The number of distinct integers $n$ for which $\log_{\left(\frac14\right)}(n^2 - 7n + 11)>0$ is:
- CAT - 2025
- Linear Inequalities
- In the set of consecutive odd numbers $\{1, 3, 5, \ldots, 57\}$, there is a number $k$ such that the sum of all the elements less than $k$ is equal to the sum of all the elements greater than $k$. Then, $k$ equals?
- CAT - 2025
- Number Systems
- The number of distinct pairs of integers $(x, y)$ satisfying the inequalities $x>y \ge 3$ and $x + y<14$ is:
- CAT - 2025
- Number Systems
For any natural number $k$, let $a_k = 3^k$. The smallest natural number $m$ for which \[ (a_1)^1 \times (a_2)^2 \times \dots \times (a_{20})^{20} \;<\; a_{21} \times a_{22} \times \dots \times a_{20+m} \] is:
- CAT - 2025
- Linear Inequalities