Ruppin Academic Center (Hebrew: הַמֶרְכָּז הַאָקָדֶמִי רוּפִּין), also known as Ruppin College, is a college in Israel, which has the status of an institutional settlement. It was established in 1949, is named after Arthur Ruppin, and is located near the moshav Kfar Monash, and within the Hefer Valley Regional Council area. In 2015, it had 4,500 students, whilst the village had a population of 307 in 2019.
This article examines the enduring impact of the 1948 Palestine-Israel War through the conceptual lenses of hauntology and intergenerational transmission. It focuses on the legacy of Netiva Ben-Yehuda, a Palmach veteran who challenged the prevailing Zionist myth of purity of arms by documenting her participation in war atrocities. While the state-sanctioned narrative celebrated the war as a semi-mythical resurrection, Ben-Yehuda’s public testimonies revealed the ghosts of massacres and executions. Drawing on Jacques Derrida’s theory of spectrality, the study explores how these suppressed truths seeped into the lives of Ben-Yehuda’s descendants. Through qualitative interviews with her daughter and grandsons, the article traces the manifestation of these ghosts across three generations. Findings suggest that for the second generation, the trauma manifested as an embodied presence of the war and the mother’s untreated PTSD, shaping a childhood lived in the shadow of a momentous event. For the third generation, these ghosts triggered historical inquiries and public political dissent, reflecting a refusal to conform to social codes of silence. The article also refers to the work of Mahmoud Darwish on Palestinian ghosts who roam the landscape and haunt the living Israelis. The encounters between the dead and the living highlight the interconnectedness of Palestinian and Jewish-Zionist narratives. By centering the voices of the perpetrator’s descendants alongside the haunting presence of the victims, the study demonstrates how the unresolved injustices of 1948 continue to demand accountability. The ghosts of 1948 bind the two societies together, challenging the national silence surrounding the Nakba.
Artificial intelligence (AI) is increasingly run on high-density computing infrastructure, yet its environmental footprint is still assessed mainly through electricity use and associated greenhouse-gas emissions. A critical, less visible dimension is water: AI infrastructure consumes freshwater through evaporative cooling, indirect water use in electricity generation, and water-intensive semiconductor manufacturing. Projections suggest AI's global water footprint could reach 4.2-6.6 billion cubic meters annually by 2027. Many data centers are located in water-stressed regions. While technologies, including cold-climate siting, natural water body cooling, waterless designs, and waste heat recovery, can reduce on-site demand, their deployment remains limited. This work introduces "digital water sobriety" as a governance framework linking evaluation of which AI applications justify freshwater consumption, water conscious siting, and mandatory facility-level water use transparency. Achieving water-sustainable AI demands not merely technological optimization but fundamental policy reform integrating water constraints into computational infrastructure planning.
Kehle and Unger have recently shown that, under suitable conditions, a massless charged classical scalar field can produce an extremal black hole in finite time. This result appears to violate the third law of thermodynamics (TLT), since extremal black holes have zero temperature. However, because the TLT is intrinsically a quantum principle, a self-consistent analysis of this problem must account for quantum effects. In particular, we point out that the electric field of the system may spontaneously polarize the vacuum, thereby creating massless charged pairs that will discharge the black hole. This mechanism guarantees the quantum validity of the TLT in the regime |eQ|≥ħ/2 (here Q,e denote, respectively, the electric charges of the black hole and the scalar field). This leaves open the question of what happens for lower values of |eQ|/ħ. Recently, Schneider derived a classical bound showing that extremal black holes cannot be formed à la Kehle-Unger in the small-charge regime |eQ|≤ħ/3. His analysis leaves open the possibility that a stronger bound may exist. We conjecture here that this bound can indeed be strengthened such that classical considerations would prevent extremal (zero-temperature) charged Reissner-Nordström black holes from forming dynamically in the regime |eQ|<ħ/2, where quantum polarization effects are too weak to preserve the validity of the TLT.
This longitudinal study examines the relationship between prewar status-quo bias (SQB) and emotional measurements taken during the Isarel-Hamas War. A sample of 1,053 Israeli participants (ages 25–66; 50
Suspension feeding, in which organisms filter particles from the water for nutrition, is a widespread and ecologically critical feeding strategy in aquatic ecosystems. And yet, the principles governing particle capture remain unresolved. Mucus-based particle capture is widespread, and classical models typically describe it as a size-dependent sieve-like mesh of mucous nanofibres. Here, we show that for small particles, surface physico-chemistry, not size alone, strongly influences capture. Using polystyrene microspheres with tailored amphiphilic polymer coatings, we found that steric repulsion altered particle mobility within the mucous filter, reducing capture efficiency for submicrometre beads, while larger particles were retained regardless of coating. Cryogenic scanning electron microscopy imaging revealed that, contrary to prevailing models, the ascidian mucous filter is an approximately 5 µm thick continuous sheet rather than a nanofibre mesh. These findings call for a revision of suspension-feeding models to incorporate colloid-mucus interactions and bulk transport phenomena. Beyond advancing our understanding of plankton ecology, this work provides principles for the design of synthetic filtration systems that couple high efficiency with self-cleaning.