Pakistan Science News API

{
    "totalArticles": 24538,
    "articles": [
        {
            "id": "2640582767e78fcb7054221c0546c8a3",
            "title": "Can meteorites be recovered from Cape Cod Bay? Harvard professor compares search to a ‘fishing expedition’",
            "description": "A surprising discovery showed that the sonic boom off the coast of Massachusetts has triggered a viral sensation online. A meteor mainly exploded over Cape Cod Bay after breaking the sound barrier,...",
            "content": "A surprising discovery showed that the sonic boom off the coast of Massachusetts has triggered a viral sensation online. A meteor mainly exploded over Cape Cod Bay after breaking the sound barrier, creating a boom that could be heard and felt from se... [1487 chars]",
            "url": "https://www.thenews.com.pk/latest/1404607-can-meteorites-be-recovered-from-cape-cod-bay-harvard-professor-compares-search-to-a-fishing-expedition",
            "image": "https://www.thenews.com.pk/assets/uploads/2026-06-03/1404607_121224_updates.jpg",
            "publishedAt": "2026-06-03T07:12:00Z",
            "lang": "en",
            "source": {
                "id": "d6d8d1da5b3ea3eb10f02262522a0d6d",
                "name": "The News International",
                "url": "https://www.thenews.com.pk"
            }
        },
        {
            "id": "428b618e9333101c0b3f674b1dd28bd8",
            "title": "Biophysical mechanisms underlying the generation and maintenance of rule-learning engram",
            "description": "Training rodents in a particularly difficult olfactory-discrimination task results with acquisition of high-skill to perform the task superbly, termed ‘rule-learning’. We show that rule-learning occurs abruptly, in a “light-bulb moment”. Using whole-cell patch-clamp recordings from the piriform cortex (PC) of Fos2A-iCreER/TRAP2 mice, we target activated-neurons, expressing immediate early genes (IEG). We notice, from the onset of training, IEG-positive neurons from trained animals display enhanced intrinsic excitability. Subsequently, synaptic excitation and inhibition are enhanced in these neurons, in a coordinated, cell-wide process. Additionally, in parallel, we detect the density of IEG-expressing neurons sharply declines. Double labeling with TRAP and c-Fos reveal that nearly two-thirds of the rule-memory cell ensemble neurons are activated from the beginning of training. Silencing TRAP-expressing neurons using inhibitory DREADD leads to a complete loss of rule memory. Hence, we propose that rule learning occurs at a discrete moment and is developed through a gradual process that stabilizes the memory of the rule. Rule-learning of complex tasks occurs abruptly in a \"light-bulb moment\". The memory is developed in a gradual process in which synaptic connectivity between the most intrinsically excitable neurons is enhanced to stabilize the neuronal network.",
            "content": "We thank Dr. Boris Shklyar and his team, Bioimaging Unit, University of Haifa, for the training and extensive help for microscopy and analysis of imaging data. We appreciate a valuable service from Dr. Sharon Tal (Ex- Head of Histology Unit) and Dr. ... [1326 chars]",
            "url": "https://www.nature.com/articles/s42003-026-10243-7?error=cookies_not_supported&code=0260a3e5-c16a-4581-b4d9-8cb8cc254950",
            "image": "https://www.nature.com/static/images/favicons/nature/favicon-48x48-b52890008c.png",
            "publishedAt": "2026-06-03T02:23:15Z",
            "lang": "en",
            "source": {
                "id": "7abf0df285fbe93cdccffcc7c4088737",
                "name": "Nature",
                "url": "https://www.nature.com"
            }
        },
        {
            "id": "e826182c2195e6c2ed7684827e7880e3",
            "title": "Comparing implicit boundary and hierarchical plurigaussian simulation for modeling geological domains using hard and soft data",
            "description": "The delineation of geological domains is a crucial step in mineral resource evaluation, as it directly influences the accuracy of grade models. Instead of a single geological interpretation, geostatistical simulation generates multiple scenarios that reproduce the spatial variability and can be used to assess uncertainty in the spatial layout of the geological domains. This study compares two established geostatistical simulation frameworks–Implicit Boundary Simulation (IBS) and Hierarchical Plurigaussian Simulation (HPGS)–and proposes practical, rigorous pathways to incorporate interpreted geological models as soft data. In IBS, the interpreted model enters as an auxiliary signed–distance covariate which is co-simulated with the down-the-hole signed distance derived from sampling data. In HPGS, the interpreted model informs local domain proportions through a moving window that controls local truncation thresholds. Both methods were applied to a porphyry copper deposit in northern Chile for modeling five mineralization zones under pronounced data scarcity. One hundred conditional realizations were generated for each approach and probability maps, most-probable domain maps, and match–mismatch tables against the interpreted model and drilling data were computed. The results demonstrated that, while both approaches benefited from incorporating soft data, HPGS yielded results that are more consistent with the interpreted model, particularly for mineralization zones exhibiting small-scale variability.",
            "content": "The delineation of geological domains is a crucial step in mineral resource evaluation, as it directly influences the accuracy of grade models. Instead of a single geological interpretation, geostatistical simulation generates multiple scenarios that... [2170 chars]",
            "url": "https://www.nature.com/articles/s41598-026-55669-5?error=cookies_not_supported&code=0904d036-464e-4802-a476-d572a8bd408b",
            "image": "https://www.nature.com/static/images/favicons/nature/favicon-48x48-b52890008c.png",
            "publishedAt": "2026-06-03T00:29:15Z",
            "lang": "en",
            "source": {
                "id": "7abf0df285fbe93cdccffcc7c4088737",
                "name": "Nature",
                "url": "https://www.nature.com"
            }
        }
    ]
}