bluuebunny/crossref_metadata_2025_split huggingface dataset:
On-chip tunable quantum interference in a lithium niobate-on-insulator photonic integrated circuit
Authors: Maeder Andreas , Finco Giovanni , Kaufmann Fabian , Sabatti Alessandra , Kellner Jost , Chapman Robert J , Grange Rachel 
Published: May 2024

Abstract
Programmable interferometric circuits are at the heart of integrated quantum photonic processors. While the lithium niobate-on-insulator platform has the potential to advance integrated quantum photonics due to its strong nonlinearity and tight mode confinement, the demonstration of reconfigurable two-photon interference has not yet been achieved. Here, we design, fabricate and characterize the building block of such interferometric networks in the form of a 2 × 2 Mach–Zehnder Interferometer. We use a thermo-optic phase shifter to achieve stable performance with a power consumption of

P
π

=
44.4

mW and sub-microsecond switching times. We demonstrate the effectiveness of our device for quantum applications by measuring single-photon routing with up to 34 dB extinction ratio. We show Hong-Ou-Mandel interference with fully tunable visibilities reaching a maximum value of

97.4
±
1.0
%

. As part of large scale quantum photonic circuits, this building block will facilitate reconfigurable and tunable photonic processing units integrated alongside non-classical light sources.
Exploratory data science on supercomputers for quantum mechanical calculations
Authors: Dawson William , Beal Louis , Ratcliff Laura E , Stella Martina , Nakajima Takahito , Genovese Luigi 
Published: May 2024

Abstract
Literate programming—the bringing together of program code and natural language narratives—has become a ubiquitous approach in the realm of data science. This methodology is appealing as well for the domain of Density Functional Theory (DFT) calculations, particularly for interactively developing new methodologies and workflows. However, effective use of literate programming is hampered by old programming paradigms and the difficulties associated with using high performance computing (HPC) resources. Here we present two Python libraries that aim to remove these hurdles. First, we describe the PyBigDFT library, which can be used to setup materials or molecular systems and provides high-level access to the wavelet based BigDFT code. We then present the related remotemanager library, which is able to serialize and execute arbitrary Python functions on remote supercomputers. We show how together these libraries enable transparent access to HPC based DFT calculations and can serve as building blocks for rapid prototyping and data exploration.
Parametric analysis, modeling and optimization of the process parameters in electric discharge machining of aluminium metal matrix composite
Authors: Kumar Harmesh , Wadhwa Amandeep Singh , Akhai Shalom , Kaushik Arishu 
Published: May 2024

Abstract
Optimizing electric discharge machining (EDM) for aluminum/SiCp metal matrix composites poses challenges due to intricate machine parameters and process complexity, impacting process economy and elevating product costs. The research aims to find the optimal combination of process parameters which include pulse on-time, pulse current, duty cycle (%), gap voltage, sensitivity and flushing pressure for EDM of Al/SiCp-MMC using a copper electrode for the selected response factors such as material erosion rate and surface roughness, Ra. The experiments were designed using the central composite design of response surface methodology and an advanced optimization technique known as Teaching–learning-based optimization (TLBO), is applied to find the optimal combination of process parameters to obtain maximum material erosion rate subject to the desired range of surface roughness (SR), Ra. The combination of the high pulse on-time (i.e. 150 μs) and high pulse current (i.e. 12A) results in high material removal rate with deep craters on the machined surface clearly visible in SEM images contrasting the minimized surface roughness at lower values of pulse on-time (50 μs) and the pulse current (4A). Pulse on - time (Ton) is found to be the most significant factor for material erosion rate and surface roughness with percentage contribution of 70.86 and 54.9 respectively for optimization of the response. The regression models were developed at 95% confidence level for material removal rate and surface roughness with R2 value of 0.93 and 0.95 respectively signifying high degree of accuracy in predicting the response. Confirmation tests conducted to check the adequacy of the established models revealed that the percentage error between the predicted and experimental responses is found to be within acceptable levels. Electron discharge machining of the aluminium metal matrix composite at the optimized conditions could provide economical aspect in the aerospace and automobile industry.
Interpolation of environmental data using deep learning and model inference
Authors: Ibebuchi Chibuike Chiedozie , Abu Itohan-Osa 
Published: May 2024

Abstract
The temporal resolution of environmental data sets plays a major role in the granularity of the information that can be derived from the data. In most cases, it is required that different data sets have a common temporal resolution to enable their consistent evaluations and applications in making informed decisions. This study leverages deep learning with long short-term memory (LSTM) neural networks and model inference to enhance the temporal resolution of climate datasets, specifically temperature, and precipitation, from daily to sub-daily scales. We trained our model to learn the relationship between daily and sub-daily data, subsequently applying this knowledge to increase the resolution of a separate dataset with a coarser (daily) temporal resolution. Our findings reveal a high degree of accuracy for temperature predictions, evidenced by a correlation of 0.99 and a mean absolute error of 0.21 °C, between the actual and predicted sub-daily values. In contrast, the approach was less effective for precipitation, achieving an explained variance of only 37%, compared to 98% for temperature. Further, besides the sub-daily interpolation of the climate data sets, we adapted our approach to increase the resolution of the Normalized difference vegetation index of Landsat (from 16 d to 5 d interval) using the LSTM model pre-trained from the Sentinel 2 Normalized difference vegetation index—that exists at a relatively higher temporal resolution. The explained variance between the predicted Landsat and Sentinel 2 data is 70% with a mean absolute error of 0.03. These results suggest that our method is particularly suitable for environmental datasets with less pronounced short-term variability, offering a promising tool for improving the resolution and utility of the data.
Autoencoders for discovering manifold dimension and coordinates in data from complex dynamical systems
Authors: Zeng Kevin , De Jesús Carlos E Pérez , Fox Andrew J , Graham Michael D 
Published: May 2024

Abstract
While many phenomena in physics and engineering are formally high-dimensional, their long-time dynamics often live on a lower-dimensional manifold. The present work introduces an autoencoder framework that combines implicit regularization with internal linear layers and L
2 regularization (weight decay) to automatically estimate the underlying dimensionality of a data set, produce an orthogonal manifold coordinate system, and provide the mapping functions between the ambient space and manifold space, allowing for out-of-sample projections. We validate our framework’s ability to estimate the manifold dimension for a series of datasets from dynamical systems of varying complexities and compare to other state-of-the-art estimators. We analyze the training dynamics of the network to glean insight into the mechanism of low-rank learning and find that collectively each of the implicit regularizing layers compound the low-rank representation and even self-correct during training. Analysis of gradient descent dynamics for this architecture in the linear case reveals the role of the internal linear layers in leading to faster decay of a ‘collective weight variable’ incorporating all layers, and the role of weight decay in breaking degeneracies and thus driving convergence along directions in which no decay would occur in its absence. We show that this framework can be naturally extended for applications of state-space modeling and forecasting by generating a data-driven dynamic model of a spatiotemporally chaotic partial differential equation using only the manifold coordinates. Finally, we demonstrate that our framework is robust to hyperparameter choices.
Structural formation yield of GeV centers from implanted Ge in diamond
Authors: Wahl Ulrich , Correia João Guilherme , Costa Ângelo , Lamelas Afonso , Amaral Vítor , Johnston Karl , Magchiels Goele , Tunhuma Shandirai Malven , Vantomme André , Pereira Lino M C 
Published: May 2024

Abstract
In order to study the structural formation yield of germanium-vacancy (GeV) centers from implanted Ge in diamond, we have investigated its lattice location by using the β
− emission channeling technique from the radioactive isotope 75Ge (t
1/2 = 83 min) produced at the ISOLDE/CERN facility. 75Ge was introduced via recoil implantation following 30 keV ion implantation of the precursor isotope 75Ga (126 s) with fluences around 2 × 1012–5 × 1013 cm−2. While for room temperature implantation fractions around 20% were observed in split-vacancy configuration and 45% substitutional Ge, following implantation or annealing up to 900 °C, the split-vacancy fraction dropped to 6%–9% and the substitutional fraction reached 85%–96%. GeV complexes thus show a lower structural formation yield than other impurities, with substitutional Ge being the dominant configuration. Moreover, annealing or high-temperature implantation seem to favor the formation of substitutional Ge over GeV. Our results strongly suggest that GeV complexes are thermally unstable and transformed to substitutional Ge by capture of mobile carbon interstitials, which is likely to contribute to the difficulties in achieving high formation yields of these optically active centers.
Yearning to Submit
Authors: Frie Roger 
Published: May 2024

AbstractThis chapter traces the source of Fromm’s impassioned arguments against fascism in Escape From Freedom. With his arrival in New York in 1934, Fromm began a new chapter of his life as a German Jewish refugee. He watched from afar as the political situation in Europe deteriorated, ever conscious of the growing threat of Nazism for his family members, friends, and colleagues who remained in Germany. In 1938, Fromm traveled back to Europe for the first time. When the November Pogrom broke out, Fromm was convalescing in Switzerland from an attack of tuberculosis. In his weakened state, Fromm’s corresponded regularly with Horkheimer, and their letters reveal the depth of worry and doubt that Fromm felt as he sought to help his family members from the isolation of his hospital bed. When Fromm was finally well enough to return to the United States, he simultaneously engaged in a campaign to save his relatives and elaborated his arguments on the dangers of fascism, which would form the basis for Escape From Freedom. Fromm’s psychology of Nazism is examined and explained.
Confronting Genocide
Authors: Frie Roger 
Published: May 2024

AbstractThis chapter examines connections between the personal dimension of the Holocaust in Fromm’s life and his writings on the destructiveness and evil. The chapter sheds new light on Fromm’s marriage to Henny Gurland, a fellow German Jewish refugee, who accompanied the philosopher Walter Benjamin on his fateful attempt to flee Nazi-occupied France and on Fromm’s rescue of his cousin, Heinz Brandt, who had remarkably survived Auschwitz and was imprisoned by the East German secret police. Throughout the postwar years, the Holocaust correspondence forms the unspoken context for Fromm’s impassioned stance on human solidarity. At the height of the civil rights movement, Fromm spoke directly to the scourge of racism. In The Anatomy of Human Destructiveness, he analyzed the personal pathologies of Hitler and Himmler at the heart of the “Final Solution.” Fromm struggled to bridge his early life experiences in Germany with the reality of antisemitism; called out ambivalent postwar German commitments to remembrance and responsibility; and sought to understand the motivations of major Nazi figures like Albert Speer. At the end of his life, he offered a series of critical reflections on Zionism and Israel.
Understanding individual experiences with stick-built and modular cleanrooms: Lessons learned and a call to action
Authors: Armistead Lori T , Eckel Stephen F 
Published: May 2024

Abstract

Purpose
The purpose of this study was to assess the real-world experiences of cleanroom managers and specialists who have designed, installed, and maintained stick-built and/or modular cleanrooms, delineate the advantages and disadvantages of each type of cleanroom, and gather sterile compounding cleanroom design and installation advice and lessons learned.

Methods
This study was conducted via surveys and semistructured interviews of individuals with cleanroom experience in the previous 5 years. Qualitative analyses were conducted on participants’ survey and interview responses to assess their satisfaction with each type of cleanroom and to determine what they perceive to be the pros and cons of each type based on their own experiences. Key lessons learned and advice from these individuals were also extracted from their survey and interview responses.

Results
Fourteen individuals from 13 US states completed the survey; 12 participated in follow-up interviews. Fifty percent of the participants (n = 7) had installed 5 or more cleanrooms in the previous 5 years and over half (n = 8; 57%) had 7 or more years of cleanroom experience. The average satisfaction scores for each type of cleanroom, on a 1 to 10 scale, was 5.3 for stick-built (n = 11) and 9.3 for modular (n = 4). The pros of stick-built cleanrooms included greater design and material flexibility and lower up-front costs. The pros of modular cleanrooms included the cleanroom experience and expertise of modular vendors, quick and easy installations, guaranteed certification, and high-quality and durable design features and materials. Additionally, modular cleanrooms had fewer long-term maintenance issues, greater long-term flexibility, and lower indirect and long-term costs than stick-built cleanrooms. Key pieces of advice from the participants included the following: do your homework before beginning a cleanroom project; make sure heating, ventilation, and air conditioning system(s) and air handlers are adequate for your needs; and remember that the ultimate purpose of a quality cleanroom is patient safety. Participants also advocated for industry-wide cleanroom standards that go beyond USP regulations.

Conclusion
The findings of this study confirm many of the purported pros and cons of each type of cleanroom, with further insight gained into the relative quality and costs of each type. Modular cleanrooms were considered by most participants to be a better long-term option, based on quality and lifetime costs, if feasible to install. Study participants also emphasized that designing and installing pharmacy cleanrooms is a complex and time-intensive process that often comes with a steep learning curve. While there are federal and state cleanroom standards available and consultants for hire, a comprehensive resource or manual that could provide guidance, insight, and collective lessons learned on cleanroom design and installation is needed.
II—Ownership, Property and Belonging: Some Lessons to Learn from Thinkers of Antiquity about Economics and Success
Authors: Rowett Catherine 
Published: May 2024

Abstract
I explore some enlightening alternative economic theories in Plato’s Republic which help to cast doubt on standard models of rationality in economics. Starting from Socrates’ suggestion that things work best if everyone says ‘mine’ about the same things, I discuss a kind of ‘belonging’ which merits more attention in political and economic theory. This kind of belonging is not about owning property, but it can (better) explain the desire to do things for others and for the collective good. But did Socrates forget to invoke it when addressing the puzzle about why the philosopher would willingly return to the cave?
Transcriptome analysis: a powerful tool to understand individual microbial behaviors and interactions in ecosystems
Authors: Sato Yuya 
Published: May 2024

ABSTRACT
Transcriptome analysis is a powerful tool for studying microbial ecology, especially individual microbial functions in an ecosystem and their interactions. With the development of high-throughput sequencing technology, great progress has been made in analytical methods for microbial communities in natural environments. 16S rRNA gene amplicon sequencing (ie microbial community structure analysis) and shotgun metagenome analysis have been widely used to determine the composition and potential metabolic capability of microorganisms in target environments without requiring culture. However, even if the types of microorganisms present and their genes are known, it is difficult to determine what they are doing in an ecosystem. Gene expression analysis (transcriptome analysis; RNA-seq) is a powerful tool to address these issues. The history and basic information of gene expression analysis, as well as examples of studies using this method to analyze microbial ecosystems, are presented.
Direct and indirect treatment effects in the presence of semicompeting risks
Authors: Deng Yuhao , Wang Yi , Zhou Xiao-Hua 
Published: May 2024

Abstract
Semicompeting risks refer to the phenomenon that the terminal event (such as death) can censor the nonterminal event (such as disease progression) but not vice versa. The treatment effect on the terminal event can be delivered either directly following the treatment or indirectly through the nonterminal event. We consider 2 strategies to decompose the total effect into a direct effect and an indirect effect under the framework of mediation analysis in completely randomized experiments by adjusting the prevalence and hazard of nonterminal events, respectively. They require slightly different assumptions on cross-world quantities to achieve identifiability. We establish asymptotic properties for the estimated counterfactual cumulative incidences and decomposed treatment effects. We illustrate the subtle difference between these 2 decompositions through simulation studies and two real-data applications in the Supplementary Materials.
Testing conditional quantile independence with functional covariate
Authors: Feng Yongzhen , Li Jie , Song Xiaojun 
Published: May 2024

Abstract
We propose a new non-parametric conditional independence test for a scalar response and a functional covariate over a continuum of quantile levels. We build a Cramer–von Mises type test statistic based on an empirical process indexed by random projections of the functional covariate, effectively avoiding the “curse of dimensionality” under the projected hypothesis, which is almost surely equivalent to the null hypothesis. The asymptotic null distribution of the proposed test statistic is obtained under some mild assumptions. The asymptotic global and local power properties of our test statistic are then investigated. We specifically demonstrate that the statistic is able to detect a broad class of local alternatives converging to the null at the parametric rate. Additionally, we recommend a simple multiplier bootstrap approach for estimating the critical values. The finite-sample performance of our statistic is examined through several Monte Carlo simulation experiments. Finally, an analysis of an EEG data set is used to show the utility and versatility of our proposed test statistic.
Pattern of recurrence after stereotactic body radiotherapy of nodal lesions: a single-institution analysis
Authors: Ferro Milena , Macchia Gabriella , Pezzulla Donato , Cilla Savino , Romano Carmela , Ferro Marica , Boccardi Mariangela , Bonome Paolo , Picardi Vincenzo , Buwenge Milly , Morganti Alessio G , Deodato Francesco 
Published: May 2024

Abstract

Objectives
Stereotactic body radiotherapy (SBRT) and/or single fraction stereotactic body radiosurgery (SRS) are effective treatment options for the treatment of oligometastatic disease of lymph nodes. Despite the encouraging local control rate, progression-free survival remains unfair due to relapses that might occur in the same district or at other sites. The recurrence pattern analysis after nodal local ablative RT (laRT) in oligometastatic patients is presented in this study.

Methods
The pattern of failure of patients with nodal metastases who were recruited and treated with SBRT in the Destroy-1 or SRS in the Destroy-2 trials was investigated in this single-institution, retrospective analysis. The different relapsed sites following laRT were recorded.

Results
Data on 190 patients who received SBRT or SRS on 269 nodal lesions were reviewed. A relapse rate of 57.2% (154 out of 269 nodal lesions) was registered. The pattern of failure was distant in 88 (57.4%) and loco-regional in 66 (42.6%) patients, respectively. The most frequent primary malignancies among patients experiencing loco-regional failure were genitourinary and gynaecological cancers. Furthermore, the predominant site of loco-regional relapse (62%) was the pelvic area. Only 26% of locoregional relapses occurred contra laterally, with 74% occurring ipsilaterally.

Conclusions
The recurrence rates after laRT for nodal disease were more frequent in distant regions compared to locoregional sites. The most common scenarios for locoregional relapse appear to be genitourinary cancer and the pelvic site. In addition, recurrences often occur in the same nodal station or in a nodal station contiguous to the irradiated nodal site.

Advances in knowledge
Local ablative radiotherapy is an effective treatment in managing nodal oligometastasis. Despite the high local control rate, the progression free survival remains dismal with recurrences that can occur both loco-regionally or at distance. To understand the pattern of failure could aid the physicians to choose the best treatment strategy. This is the first study that reports the recurrence pattern of a significant number of nodal lesions treated with laRT.
A Quasi-Experimental Evaluation of the Lifelong Links Intervention for Reducing Homelessness amongst Care Leavers
Authors: Sanders Michael , Hirneis Vanessa , Picker Vanessa 
Published: May 2024

Abstract
Despite the fact that care leavers are at significantly higher risk of homelessness than their peers who have not experienced care, there is a paucity of information on evidence-based interventions to address this risk. Lifelong Links is a program developed and delivered by the Family Rights Group in England. The intervention aims to ensure that a child in care has a positive support network around them to help during their time in care and into adulthood. In this article, we analyse the outcomes of a quasi-experimental evaluation of the Lifelong Links program. Specifically, we make use of a combination of coarsened exact matching, and a triple-differences approach (or difference in difference in differences analysis). Results of our analyses show that Lifelong Links is associated with a reduction in the risk of becoming homeless for care leavers aged eighteen to twenty in the years following its implementation. Our most robust model showed a reduction of around 10 per cent in the risk of a young care leaver being deemed at risk of, or experiencing homelessness, suggesting that improving ties between young people in care and their birth families (and/or building other sources of support) could have beneficial impacts on housing outcomes into adulthood.