Are workers effective lawmakers? Throughout American history, some politicians and elites have argued that white-collar Americans are more qualified than working-class Americans to govern. To date, however, we know relatively little about the legislative effectiveness of working-class lawmakers. I develop a theory of class-based electoral selection that links class-based discrimination in elections to legislators’ performance in office. I argue that working-class candidates face class-based biases in elections that make it more difficult to emerge and successfully win elective office. As a result, I expect the working-class candidates who do become lawmakers to be equally or more effective than their white-collar colleagues. To test these expectations, I create a data set merging the occupational background of more than 14,000 individual state legislators with their state legislative effectiveness score (SLES). The resulting data set includes more than 50,000 state legislator-term specific observations. Consistent with my expectations, I find that working-class lawmakers do not underperform white-collar lawmakers. Further, I provide evidence that, across various models and specifications, the gap between working-class and white-collar legislators’ effectiveness is negligible.

This study aimed to investigate the association between maternal birth weight (MBW) with preterm delivery (PTD) in the Japanese population. To this end, a total of 78,972 Japanese pregnant women were included in a prospective birth cohort study. Multiple logistic regression and multinominal logistic regression models were applied to investigate the associations of MBW with PTD (delivery from 22 to < 37 weeks of gestation), early PTD (delivery from 22 to < 34 weeks), and late PTD (delivery from 34 to < 37 weeks). The results showed that MBW was inversely associated with PTD, early PTD, and late PTD (p-for-trend < 0.0001, 0.0014, and < 0.0001, respectively). The adjusted odds ratios per each 500 g of MBW decrease were 1.167 (95% confidence interval [CI]: 1.118–1.218) for PTD, 1.174 (95% CI: 1.070–1.287) for early PTD and 1.151 (95% CI: 1.098–1.206) for late PTD. The effect size of the association of MBW with early PTD was similar to that with late PTD. This study demonstrated for the first time an association of a low MBW with PTD, early PTD, and late PTD in a Japanese nationwide cohort.

Path loss prediction (PLP) is an important feature of wireless communications because it allows a receiver to anticipate the signal strength that will be received from a transmitter at a given distance. The PLP is done by using machine learning models that take into account numerous aspects such as the frequency of the signal, the surroundings, and the type of antenna. Various machine learning methods are used to anticipate path loss propagation but it is difficult to predict path loss in unknown propagation conditions. In existing models rely on incomplete or outdated data, which can affect the accuracy and reliability of predictions and they do not take into account the effects of environmental factors, such as terrain, foliage, and weather conditions, on path loss. Furthermore, existing models are not robust enough to handle the real-world variability and uncertainty, leading to significant errors in predictions. To tackle this issue, a novel ultrahigh frequency (UHF) PLP based on K-nearest neighbors (KNNs) is developed for predicting and optimizing the path loss for UHF. In this proposed model, a KNN-based PLP has been used to predict the path loss in the UHF. This technique is used for high-accuracy PLP through KNN forecast route loss by determining the K-nearest data points to a particular test point based on a distance metric. Moreover, the existing models were not able to optimize path loss due to complex and large-scale machine learning models. Therefore, the stochastic gradient descent technique has been used to minimize the objective function, which is often a measure of the difference between the model’s predictions and the actual output that will fine-tune the parameters of the KNN model, by measuring the similarity between data points. This model is implemented using Python to make it a lot more convenient.

Algeria’s micro-satellite, Alsat-1b, was successfully launched into a 680 km low Earth orbit onboard a PSLV-C35 rocket from Sriharikota, South India, on September 26, 2016. The spacecraft was conceived, built and launched as part of an 18-month technology transfer programme between Algeria’s Algerian Space Agency (ASAL) and the United Kingdom’s Surrey Satellite Technology Limited (SSTL). This document details the Power Conditioning and Distribution Module’s (PCM-PDM) design and performance in orbit, critical component of a satellite electrical power system, responsible for converting, regulating and distributing power to various subsystems and payloads. The PCM-PDM developed and produced by SSTL was subjected to rigorous testing simulating harsh space conditions to assess its performance. The results of this comprehensive analysis indicate that the module can effectively withstand extreme environmental factors and function optimally in challenging settings. The analysis focused on the PCM-PDM’s ability to provide reliable and efficient power conditioning and distribution to the satellite, including its load management capabilities, overcurrent protection, protection against undervoltage and critical mode operations. The results of the performance analysis showed that the PCM-PDM met the required specifications and demonstrated reliable and efficient operation in different modes of the satellite’s mission. The study highlights the importance of careful design and rigorous testing of the PCM-PDM to ensure the reliable and efficient operation of the satellite and its payloads.

For an elliptic curve E defined over a number field K and $L/K$ a Galois extension, we study the possibilities of the Galois group Gal$(L/K)$, when the Mordell–Weil rank of $E(L)$ increases from that of $E(K)$ by a small amount (namely 1, 2, and 3). In relation with the vanishing of corresponding L-functions at $s=1$, we prove several elliptic analogues of classical theorems related to Artin’s holomorphy conjecture. We then apply these to study the analytic minimal subfield, first introduced by Akbary and Murty, for the case when order of vanishing is 2. We also investigate how the order of vanishing changes as rank increases by 1 and vice versa, generalizing a theorem of Kolyvagin.

Classic Teotihuacan's mural tradition evidences a Great Goddess and a Storm God in a cult of rain and fertility, yet their identity and relationship is problematic. This article reads the mural iconography as a myth of passage where the Great Goddess transited through portals uniting the planes of the cosmos at the boundary between the dry and rainy seasons to transform into the Storm God. Slate and pyrite mirrors and murals are analyzed as sacred artifacts with agency to invoke passage. The species of animals and plants symbolizing portals are identified to decode their symbolism of passage as symbolic transformations.

The Great Goddess transited from the underworld to the sea, entered mountain caves, and transformed her head-summit into a primordial cloud. The goddess created the axis mundi through her sacrifice, integrating the plants used for the manufacture of the Mesoamerican rubber olli. Mediated by the metamorphic powers of butterflies and olli, the goddess transformed greenstone into sacred water to become the Storm God. He commanded his helpers from his cave dwelling to produce rain and fertility clouds. Ruler-priests and warriors used mirrors to access the axis mundi and to transform into Storm God avatars with powers over rain and fertility.

Identifying racial disparities in policy and politics is a pressing area of research within the United States. Where early work made use of identifying potentially noisy correlations between county or precinct demographics and election outcomes, the advent of Bayesian Improved Surname Geocoding (BISG) vastly improved estimation of race by employing voter lists. Machine Learning (ML)-modified BISG in turn offers accuracy gains over the static – and potentially outdated – surname dictionaries present in traditional BISG. However, the extent to which ML might substantively alter the policy and political implications of redistricting is unclear given its improvements in voter race estimation. Therefore, we ascertain the potential gains of ML-modified BISG in improving the estimation of race for the purpose of redistricting majority-minority districts. We evaluate an ML-modified BISG program against traditional BISG estimates in correctly estimating the race of voters for creating majority-minority congressional districts within North Carolina and Georgia, and in state assembly districts in Wisconsin. Our results demonstrate that ML-modified BISG offers substantive gains over traditional BISG, especially in diverse political geographic units. Further, we find meaningful improvements in accuracy when estimating majority-minority district racial composition. We conclude with recommendations on when and how to use the two methods, in addition how to ensure transparency and confidence in BISG-related research.

This special issue brings together a diverse set of cases from Asia with the aim of decentring established historical narratives about science diplomacy. With a critical perspective bringing together the bodies of literature in the fields of the History of Science, Technology and Medicine (STM) and critical Asian Studies, we argue that these cases foreground a geopolitical history with multiple forms of sovereignty – often contested ones – and a range of political institutions and actors that enables us to revisit science diplomacy as a means for understanding the relationship between science and international affairs. In doing so, the articles in this issue consciously eschew the normative ‘centring’ of superpowers or Western imperial powers as the primary actors, focusing instead on the agency and subjectivity of actors within Asia, many of whom were prominent in their respective local contexts. Additionally, we argue that the cases presented here, which examine issues from across science, technology, medicine and the environment, collectively demonstrate the further need for the ‘science’ in ‘science diplomacy’ to be interpreted more broadly, incorporating as it does many aspects of human engagement with the material world.

No country in Southeast Asia is as close to China as Cambodia is at present. Under Hun Sen's leadership, Cambodia has actively participated in the Belt and Road Initiative and repeatedly blocked ASEAN's statements on the South China Sea (SCS). How can we better understand Cambodia's embrace of China? We argue that Hun Sen chose to embrace China due to the convergence of challenges posed by Cambodia's domestic opposition forces and international democratic pressures. The more severe the domestic political challenges, the more Hun Sen and his ruling party need China's support. Since Hun Sen remains the most powerful figure in Cambodia despite his recent resignation as prime minister, whether Cambodia's dependence on China can be altered depends on the ability of the West to modify its approach and attitude toward Hun Sen, his successor, and their domestic opponents. Nevertheless, regardless of how the future unfolds, domestic politics is likely to play an important role in Cambodia's foreign alignments in the foreseeable future.

In Mukti Lakhi Mangharam’s book, Freedom Inc.: Gendered Capitalism in New Indian Literature and Culture, she identifies “Freedom Inc.” as a neoliberal celebration of individual empowerment that contrasts with the multiple ways people have imagined freedom in a longer history of Indian literature and philosophy, which are much more open to collective empowerment and political transformation. This critique is certainly valid, but where in it is there the space for “bad” subjects, erotic desires, or for men and women who disobey, who flaunt rules and whose visions of freedom exceed those framed by respectable behavior or collective uplift? This article gives a few examples of what those alternative freedoms would look like, suggesting that in addition to fundamental rights, Indians might need the freedom to be naughty as well.

A scruffy piece of paper covered in notes and dated sketches of snowflake segments has been found caught between the pages of a later book in Whitby Museum’s Scoresby archive. The paper had been cut and folded to secure it round the ship Esk’s logbook. Close examination shows pencil drawing beneath the 22 ink sketches, which can be linked to entries for May 1817 in the logbook and matched to completed snowflakes from William Scoresby Junior’s 1820 book An Account of the Arctic Regions. This is almost certainly the first indication of Scoresby’s process for drawing snowflakes at sea.

The paper also contains jottings on many topics that Scoresby was considering including in his book. Comparing these with the published work, his later fact checking was clearly meticulous.

Propositional temporal logic over the real number time flow is finitely axiomatisable, but its first-order counterpart is not recursively axiomatisable. We study the logic that combines the propositional axiomatisation with the usual axioms for first-order logic with identity, and develop an alternative “admissible” semantics for it, showing that it is strongly complete for admissible models over the reals. By contrast there is no recursive axiomatisation of the first-order temporal logic of admissible models whose time flow is the integers, or any scattered linear ordering.

In the application of rotorcraft atmospheric environment detection, to reflect the distribution of atmospheric pollutants more realistically and completely, the sampling points must be spread throughout the entire three-dimensional space, and the cooperation of multiple unmanned aerial vehicles (multi-UAVs) can ensure real-time performance and increase operational efficiency. In view of the problem of coordinated detection by multi-UAVs, the region division and global coverage path planning of the stereo space to be detected are studied. A whale optimization algorithm based on the simulated annealing-whale optimization algorithm (SA-WOA) is proposed, which introduces adaptive weights with the Levy flight mechanism, improves the metropolis criterion, and introduces an adaptive tempering mechanism in the SA stage. Path smoothing is subsequently performed with the help of nonuniform rational B-spline (NURBS) curves. The comparison of algorithms using the eil76 dataset shows that the path length planned by the SA-WOA algorithm in this paper is 10.15% shorter than that of the WOA algorithm, 13.25% shorter than the SA planning result, and only 0.95% difference from the optimal path length in the dataset. From the perspective of planning time, its speed is similar to WOA, with a relative speed increase of 27.15% compared to SA, proving that the algorithm proposed in this paper has good planning performance. A hardware system platform is designed and built, and environmental gas measurement experiments were conducted. The experimental results indicate that the multi-UAV collaborative environment detection task planning method proposed in this paper has certain practical value in the field of atmospheric environment detection.

Let $\mathcal{V}$ and $\mathcal{U}$ be the point sets of two independent homogeneous Poisson processes on $\mathbb{R}^d$. A graph $\mathcal{G}_\mathcal{V}$ with vertex set $\mathcal{V}$ is constructed by first connecting pairs of points (v, u) with $v\in\mathcal{V}$ and $u\in\mathcal{U}$ independently with probability $g(v-u)$, where g is a non-increasing radial function, and then connecting two points $v_1,v_2\in\mathcal{V}$ if and only if they have a joint neighbor $u\in\mathcal{U}$. This gives rise to a random intersection graph on $\mathbb{R}^d$. Local properties of the graph, including the degree distribution, are investigated and quantified in terms of the intensities of the underlying Poisson processes and the function g. Furthermore, the percolation properties of the graph are characterized and shown to differ depending on whether g has bounded or unbounded support.