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Information revolutions and information transitions: counting, sealing, writing in Iran 10,000–300 BC
Get PDFIn this paper, we present a comprehensive analysis of counting, sealing, and writing practices in ancient Iran, spanning approximately 9000 years from the Neolithic to the Iron Age. The survival of clay (and occasionally stone or metal) media for administration in early Iran provides direct evidence for the development of bureaucratic practices. These materials reveal how such practices were situated within a broad range of socio-political, cultural, and environmental circumstances.
Through systematic review and statistical analysis of the surviving material residues of Iranian bureaucracy, we identify distinctive deep-time diachronic trends and patterns. Our findings examine the ways in which Iranian societies exhibited a more hesitant and episodic engagement with sealing and writing compared to their Mesopotamian neighbours.We consider how these differences may be contingent on the inherent fragility of the agricultural systems that underpinned Iranian societies from the Neolithic onwards. This research underscores the interconnectedness of environmental factors, social organization, and technological development in ancient Iran. By understanding the interplay of these factors, we gain valuable insights into the formation and evolution of Iranian societies over millennia
The potential of machine learning to predict melting response time of phase change materials in triplex-tube latent thermal energy storage systems
Get PDFAccurate prediction of the melting response time is vital for optimizing thermal energy storage systems, which play a key role in addressing the temporal mismatch between thermal energy demand and supply in the built environment. This study aims to quantitatively predict the melting response time of a novel triplex-tube thermal energy storage system incorporating phase change materials and Y-shaped fins to enhance heat transfer. A numerical model based on the enthalpy-porosity method was developed to simulate the melting process, resulting in a dataset comprising 60 cases with melting response times ranging from 15 to 45 min under varying design and operational conditions. The key parameters investigated include fin angle (10°–30°), fin width (5–15 mm), and heat transfer fluid temperature (60 °C–80 °C). Prior to model development, variable independence was validated to ensure robust predictions. Four machine learning algorithms—polynomial regression, support vector regression, random forest regression, and extreme gradient boosting (XGBoost)—were employed, with hyperparameter optimization performed using a Bayesian approach. The XGBoost model demonstrated superior predictive capability, achieving an accuracy of 92 %. Feature importance analysis revealed that fin width and heat transfer fluid temperature were the dominant factors, contributing 51 % and 47 % to the prediction variance, respectively, whereas fin angle had a marginal influence of 2 %. This work provides a novel application of machine learning techniques to the design and optimization of thermal energy storage systems, offering valuable insights into improving their melting performance and operational efficiency
Effect of protein source and a pasture-based diet on beef performance and methane emissions
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Exposure-based smart ventilation and occupancy control for optimizing ventilation energy consumption and long-range airborne transmission of COVID-19 in school environments
Get PDFMechanical ventilation is an effective measure to control indoor long-range airborne transmission of COVID-19, but it often leads to substantial energy expenditure. This study introduces a novel exposure-based smart ventilation and occupancy control strategy to reduce infection risk and save energy in school environments that are typically characterized by fixed occupants and long exposure time. This exposure-based approach allows the quanta concentration to vary over time rather than keeping it constantly below certain thresholds. This enables us to: 1) adjust ventilation and occupant schedule to facilitate passive cooling/heating potential in response to outdoor weather conditions; 2) consider the interaction between ventilation and occupant schedule to maximize their benefits in reducing infection risk and energy consumption. Taking a typical classroom as a base case, ventilation and occupant schedule are optimized individually and jointly through Genetic Algorithm, to control infection risk, minimize energy consumption, maintain thermal comfort, and promise sufficient schooling time. Our results show that the most energy-efficient strategy is the concurrent optimization of both occupant schedule and ventilation, achieving an up to ~60% energy reduction compared to traditional constant ventilation methods. Solely optimizing occupant schedule is the least energy-efficient strategy, yielding an energy reduction ratio (over base case) only half of the most efficient strategy. Our study reveals the possibility of optimizing occupant schedule and ventilation to balance building energy consumption and transmission control. The viability of these control strategies has been proven across various climate zones and seasons in China, highlighting their broad applicability
TNE emerging conversations: embrace the rant
Get PDFThis paper explores the extent to which Transnational Education (TNE) both deconstructs and reconstructs EAP thinking and practices. In our conference symposium, we used the acronym RANT to discuss our TNE challenges across four interrelated themes: Reconstructing Identity; Assessment; (K)Nowledge sharing and Transitions. Writing the paper gave us scope for reflection and space to consider the positive aspects of TNE as well as the cyclical nature of ranting. As a result, our RANT developed a more measured, reflective tone, which led to a revised version: Reflect, Assess, Negotiate, and Transform. The paper comprises 5 vignettes exploring challenges affecting EAP teacher identity, assessment, knowledge sharing, power relations, and equity within our various TNE and EMI contexts
Present and future interannual variability in wildfire occurrence: a large ensemble application to the United States
Get PDFRealistic projections of future wildfires need to account for both the stochastic nature of climate and the randomness of individual fire events. Here we adopt a probabilistic approach to predict current and future fire probabilities using a large ensemble of 1,600 modelled years representing different stochastic realisations of the climate during a modern reference period (2000–2009) and a future characterised by an additional 2°C global warming. This allows us to characterise the distribution of fire years for the contiguous United States, including extreme years when the number of fires or the length of the fire season exceeded those seen in the short observational record. We show that spread in the distribution of fire years in the reference period is higher in areas with a high mean number of fires, but that there is variation in this relationship with regions of proportionally higher variability in the Great Plains and southwestern United States. The principal drivers of variability in simulated fire years are related either to interannual variability in fuel production or atmospheric moisture controls on fuel drying, but there are distinct geographic patterns in which each of these is the dominant control. The ensemble also shows considerable spread in fire season length, with regions such as the southwestern United States being vulnerable to very long fire seasons in extreme fire years. The mean number of fires increases with an additional 2°C warming, but the spread of the distribution increases even more across three quarters of the contiguous United States. Warming has a strong effect on the likelihood of less fire-prone regions of the northern United States to experience extreme fire years. It also has a strong amplifying effect on annual fire occurrence and fire season length in already fire-prone regions of the western United States. The area in which fuel availability is the dominant control on fire occurrence increases substantially with warming. These analyses demonstrate the importance of taking account of the stochasticity of both climate and fire in characterising wildfire regimes, and the utility of large climate ensembles for making projections of the likelihood of extreme years or extreme fire seasons under future climate change
Regional concentration of FDI and sustainable economic development
Get PDFForeign direct investment (FDI) plays a vital role in fostering sustainable economic development, particularly in emerging and post-conflict economies. Yet, the benefits of FDI inflows depend not only on the size of investment but also on how evenly it is distributed across regions. In the Kurdistan Region of Iraq (KRI), FDI inflows have grown considerably over the past two decades, remaining heavily concentrated, with 93% of total investment absorbed by the capital city, Erbil, and only 7% distributed across the remaining governorates. This study investigates the determinants of geographic imbalances in FDI inflows within the KRI. Drawing on a unique firm-level dataset from 2007 to 2021 and employing a negative binomial logit model, the results reveal that superior infrastructure, greater market accessibility, proximity to international borders, airport connectivity, and digital network penetration are significant drivers of FDI concentration. We suggest that such spatial inequality poses significant risks to inclusive and sustainable growth, threatening to entrench regional disparities and reduce resilience to economic and local political disruptions in the long term. To mitigate these issues, we recommend a regionally differentiated policy framework that includes targeted investment incentives tailored to local comparative advantages, strategic infrastructure upgrades in underdeveloped areas, strengthened investor protections, streamlined regulatory processes, and the establishment of investment promotion agencies (IPAs) to enhance investor engagement and aftercare. By diagnosing the causes of FDI concentration and offering actionable strategies, this study provides evidence-based insights for fostering balanced, inclusive, and sustainable economic development in the KRI and other post-conflict regions confronting similar challenges
Climate change and agriculture in Pakistan: impacts and adaptation strategies
Get PDFThis thesis presents three self-contained essays, each addressing a salient
aspect of climate change impact and adaptation on Pakistan’s agricultural
sector. The first essay estimates how rising temperatures and anomalous rainfall
patterns affect agricultural output, particularly focusing on wheat yields over
time. The second essay explores the input side, analysing how changes in land
allocation serves as an adaptation strategy in response to past temperature
shocks amid government support. The final essay explores how agricultural
households respond to past temperature shocks through off-farm labour participation, showing income diversification as a key adaptation strategy in the face
of climate change.
Wheat yield response to climate change: A district-level analysis in
Pakistan
This study examines the impact of daytime and nighttime warming, along
with excess rainfall, on various stages of wheat development—planting, growing, and harvesting—in the province of Khyber Pakhtunkhwa (KP), Pakistan.
We quantify excess heat and rainfall at each developmental stage by comparing
current climate variables (maximum temperature, minimum temperature, and
rainfall) with their respective long-run averages at the district level. Using panel
data methods, we analyse the effects of these climate conditions on wheat yields
across districts in KP from 2000 to 2019.
The findings indicate that wheat is highly sensitive to high temperatures in
KP province. Excess heat affects wheat yields negatively across all the districts.
The impact is particularly severe in hotter districts, adversely affecting both
the growing and harvesting stages. While, excess rainfall during the planting
stage benefits wheat yields, while rainfall at later stages has a negative impact,
potentially delaying the ripening of wheat. Moreover, the results also show that
districts adjust their input choices amid hot climate. Irrigation emerges as a
crucial strategy for mitigating the negative effects of high temperatures across
all districts. In contrast, fertiliser application does not appear to be an effective
adaptation strategy during hot climate conditions. This study concludes that
wheat is highly sensitive to high temperatures in the province, necessitating
improved adaptive practices to safeguard yields.
Adaptation to extreme temperature: Evidence from land allocation
in agricultural sector of Pakistan
This chapter investigates the impact of past temperature shocks on different
land-use types—total agricultural land, other cropland, and wheat land—in
Khyber Pakhtunkhwa, Pakistan, over the period 1981 to 2019. Using a log-linear
regression model, it estimates how land allocation responds to past temperature
shocks and examines whether these effects vary across the climatic regions. The
analysis is framed within the context of a government policy supporting wheat
production. This policy refers to the government’s Minimum Support Price
(MSP) for wheat, which aims to encourage wheat production by guaranteeing
farmers a fixed price for their crop. The study compares two sub-periods:
1981–2006, characterised by relatively low government support for wheat
production, and 2007–2019, when support was relatively higher. The findings
show that during the low support period, land allocated to wheat declined in the
aftermath of temperature shocks, resulting in a contraction of total cultivated
land across the province. The effects, however, vary across climatic regions.
During the low support period, southern districts employed resilience-building
strategies by shifting to heat-resilient crops. This adaptive response resulted
in an expansion of total cultivated land. While, other regions experienced
reductions in both the share of land allocated to wheat and total agricultural
land. Their limited capacity to transition to alternative crops constrained their
responses, forcing them to focus on minimising potential losses from climatic
risks. During the high support period (2007–2019), the findings suggests that
government support has prevented a decline in the land allocated to wheat.
The results show no evidence of a reduction in wheat land across the province,
instead, an increase was observed, particularly in the southern and northern
regions. In these regions, land allocation towards government-supported wheat
increased in response to previous year’s temperature shocks, often at the expense
of other crops. In particular, the northern region, which is poorer and more
resource-constrained, shifted away from growing heat-resistant crops and instead
devoted more land to wheat cultivation. While the government support provides
a sense of security in the face of climatic risks, it may also inadvertently increase
reliance on a vulnerable crop.
Extreme temperature, labour supply, and subsistence farming: Evidence from Pakistan
This chapter focuses on how off-farm labour response have changed among agricultural households over the the past two decades (2001-2018). Utilising survey
data from about 21200 agricultural households across 107 districts and high-resolution gridded temperature and rainfall data over time, our analysis indicates
changes in off-farm labour responses among agricultural households in the aftermath of temperature shocks. We find no significant impact of one-year lagged
temperature shock on off-farm labour participation over the first decade (2001-
2011) and a positive association between a lagged-year temperature shock and
off-farm labour supply in the second decade (last two survey years 2015 and
2018). We, empirically examine three potential mechanisms underlying observed
responses in off-farm labour supply. We show that the increase reliance on off-farm labour is not driven by 1) worsening of temperature shocks over time, nor
by 2) learning from repeated exposure, but can be linked to 3) improvements
in local development conditions. This chapter highlights that local development
conditions have significantly improved and derive off-farm responses among agricultural households, which partly explains the recent increase in the off-farm
labour supply response