bluuebunny/crossref_metadata_2025_split huggingface dataset:
Type-Safe Dynamic Placement with First-Class Placed Values
Authors: Zakhour George , Weisenburger Pascal , Salvaneschi Guido 
Published: October 2023

Several distributed programming language solutions have been proposed to reason about the placement of data, computations, and peers interaction. Such solutions include, among the others, multitier programming, choreographic programming and various approaches based on behavioral types. These methods statically ensure safety properties thanks to a complete knowledge about placement of data and computation at compile time. In distributed systems, however, dynamic placement of computation and data is crucial to enable performance optimizations, e.g., driven by data locality or in presence of a number of other constraints such as security and compliance regarding data storage location. Unfortunately, in existing programming languages, dynamic placement conflicts with static reasoning about distributed programs: the flexibility required by dynamic placement hinders statically tracking the location of data and computation.
In this paper we present Dyno, a programming language that enables static reasoning about dynamic placement. Dyno features a type system where values are explicitly placed, but in contrast to existing approaches, placed values are also first class, ensuring that they can be passed around and referred to from other locations. Building on top of this mechanism, we provide a novel interpretation of dynamic placement as unions of placement types. We formalize type soundness, placement correctness (as part of type soundness) and architecture conformance. In case studies and benchmarks, our evaluation shows that Dyno enables static reasoning about programs even in presence of dynamic placement, ensuring type safety and placement correctness of programs at negligible performance cost. We reimplement an Android app with ∼ 7 K LOC in Dyno, find a bug in the existing implementation, and show that the app's approach is representative of a common way to implement dynamic placement found in over 100 apps in a large open-source app store.
Formal Verification of Quantum Programs: Theory, Tools, and Challenges
Authors: Lewis Marco , Soudjani Sadegh , Zuliani Paolo 
Published: October 2023

Over the past 27 years, quantum computing has seen a huge rise in interest from both academia and industry. At the current rate, quantum computers are growing in size rapidly backed up by the increase of research in the field. Significant efforts are being made to improve the reliability of quantum hardware and to develop suitable software to program quantum computers.
In contrast, the verification of quantum programs has received relatively less attention. Verifying programs is especially important in the quantum setting due to how difficult it is to program complex algorithms correctly on resource-constrained and error-prone quantum hardware. Research into creating verification frameworks for quantum programs has seen recent development, with a variety of tools implemented using a collection of theoretical ideas.
This survey aims to be a short introduction into the area of formal verification of quantum programs, bringing together theory and tools developed to date. Further, this survey examines some of the challenges that the field may face in the future, namely the development of complex quantum algorithms.
Explorations and Exploitation for Parity-based RAIDs with Ultra-fast SSDs
Authors: Wang Shucheng , Cao Qiang , Jiang Hong , Lu Ziyi , Yao Jie , Chen Yuxing , Pan Anqun 
Published: October 2023

Following a conventional design principle that pays more fast-CPU-cycles for fewer slow-I/Os, popular software storage architecture Linux Multiple-Disk (MD) for parity-based RAID (e.g., RAID5 and RAID6) assigns one or more centralized worker threads to efficiently process all user requests based on multi-stage asynchronous control and global data structures, successfully exploiting characteristics of slow devices, e.g., Hard Disk Drives (HDDs). However, we observe that, with high-performance NVMe-based Solid State Drives (SSDs), even the recently added multi-worker processing mode in MD achieves only limited performance gain because of the severe lock contentions under intensive write workloads.
In this paper, we propose a novel stripe-threaded RAID architecture, StRAID, assigning a dedicated worker thread for each stripe-write (one-for-one model) to sufficiently exploit high parallelism inherent among RAID stripes, multi-core processors, and SSDs. For the notoriously performance-punishing partial-stripe writes that induce extra read and write I/Os, StRAID presents a two-stage stripe write mechanism and a two-dimensional multi-log SSD buffer. All writes first are opportunistically batched in memory, and then are written into the primary RAID for aggregated full-stripe writes or conditionally redirected to the buffer for partial-stripe writes. These buffered data are strategically reclaimed to the primary RAID. We evaluate a StRAID prototype with a variety of benchmarks and real-world traces. StRAID is demonstrated to outperform MD by up to 5.8 times in write throughput.
Incident Cardiovascular Disease Risk among Older Asian, Native Hawaiian and Pacific Islander Breast Cancer Survivors
Authors: Hashibe Mia , Wei Mei , Lee Catherine J. , Tao Randa , Koric Alzina , Wang Jing , Daud Anees , Tay Djin , Shen Jincheng , Lee Yuan-chin A. , Chang Chun-Pin E. 
Published: October 2023

Abstract

Background:
Cardiotoxicity among breast cancer survivors is associated with chemotherapy and radiation therapy. The risk of cardiovascular disease (CVD) among Asian, Native Hawaiian and Pacific Islander (ANHPI) breast cancer survivors in the United States is unknown.

Methods:
We used the SEER-Medicare linked database to estimate the risk of CVD among older breast cancer survivors. International Classification of Disease diagnosis codes were used to identify incident CVD outcomes. Cox proportional hazards models were used to estimate HRs and 95% confidence intervals (CI) comparing ANHPI with Non-Hispanic White (NHW) patients with breast cancer for CVD, and among ANHPI race and ethnicity groups.

Results:
A total of 7,122 ANHPI breast cancer survivors and 21,365 NHW breast cancer survivors were identified. The risks of incident heart failure and ischemic heart disease were lower among ANHPI compared with NHW breast cancer survivors (HRheart failure, 0.72; 95% CI, 0.61–0.84; HRheart disease, 0.74; 95% CI, 0.63–0.88). Compared with Japanese patients with breast cancer, Filipino, Asian Indian and Pakistani, and Native Hawaiian breast cancer survivors had higher risks of heart failure. ischemic heart disease and death. Among ANHPI breast cancer survivors, risk factors for heart failure included older age, higher comorbidity score, distant cancer stage and chemotherapy.

Conclusions:
Our results support heterogeneity in CVD outcomes among breast cancer survivors among ANHPI race and ethnicity groups. Further research is needed to elucidate the disparities experienced among ANHPI breast cancer survivors.

Impact:
Filipino, Asian Indian and Pakistani, and Native Hawaiian patients with breast cancer had higher risks of heart failure, ischemic heart disease and death among ANHPI patients with breast cancer.
Landscape of Clinical Resistance Mechanisms to FGFR Inhibitors in FGFR2-Altered Cholangiocarcinoma
Authors: Wu Qibiao , Ellis Haley , Siravegna Giulia , Michel Alexa G. , Norden Bryanna L. , Fece de la Cruz Ferran , Balasooriya Eranga Roshan , Zhen Yuanli , Silveira Vanessa S. , Che Jianwe , Corcoran Ryan B. , Bardeesy Nabeel 
Published: October 2023

Abstract

Purpose:
FGFR inhibitors are effective in FGFR2-altered cholangiocarcinoma, leading to approval of reversible FGFR inhibitors, pemigatinib and infigratinib, and an irreversible inhibitor, futibatinib. However, acquired resistance develops, limiting clinical benefit. Some mechanisms of resistance have been reported, including secondary FGFR2 kinase domain mutations. Here, we sought to establish the landscape of acquired resistance to FGFR inhibition and to validate findings in model systems.

Experimental Design:
We examined the spectrum of acquired resistance mechanisms detected in circulating tumor DNA or tumor tissue upon disease progression following FGFR inhibitor therapy in 82 FGFR2-altered cholangiocarcinoma patients from 12 published reports. Functional studies of candidate resistance alterations were performed.

Results:
Overall, 49 of 82 patients (60%) had one or more detectable secondary FGFR2 kinase domain mutations upon acquired resistance. N550 molecular brake and V565 gatekeeper mutations were most common, representing 63% and 47% of all FGFR2 kinase domain mutations, respectively. Functional studies showed different inhibitors displayed unique activity profiles against FGFR2 mutations. Interestingly, disruption of the cysteine residue covalently bound by futibatinib (FGFR2 C492) was rare, observed in 1 of 42 patients treated with this drug. FGFR2 C492 mutations were insensitive to inhibition by futibatinib but showed reduced signaling activity, potentially explaining their low frequency.

Conclusions:
These data support secondary FGFR2 kinase domain mutations as the primary mode of acquired resistance to FGFR inhibitors, most commonly N550 and V565 mutations. Thus, development of combination strategies and next-generation FGFR inhibitors targeting the full spectrum of FGFR2 resistance mutations will be critical.
Diversified ESG Evaluation by Rating Agencies and Net Carbon Tax to Regain Optimal Portfolio Allocation
Authors: Yoshino Naoyuki , Yuyama Tomonori , Taghizadeh-Hesary Farhad 
Published: October 2023

Abstract
Environmental, Society, and Governance (ESG) investments have become increasingly popular in recent years, and, at the same time, many rating agencies provide ESG scores for each company. This means that the ESG investment model may have moved from the traditional two-factor model of risk-return to a three-factor model adding an ESG component to it. This paper highlights the potential for distortion of asset allocation through the shift from traditional risk-return considerations to ESG score considerations. This is equally true for green bonds, resulting in the potential for asset allocation to be distorted by green bond criteria. Furthermore, we show that imposing a net carbon tax on greenhouse gas (GHG) emissions is a measure to correct this distortion in asset allocation and make asset allocation more risk-return based, in addressing global environmental issues.
Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs
Authors: Wilson Emma 
Published: October 2023

Abstract
Prior applications of the cerebellar adaptive filter model have included a range of tasks within simulated and robotic systems. However, this has been limited to systems driven by continuous signals. Here, the adaptive filter model of the cerebellum is applied to the control of a system driven by spiking inputs by considering the problem of controlling muscle force. The performance of the standard adaptive filter algorithm is compared with the algorithm with a modified learning rule that minimizes inputs and a simple proportional-integral-derivative (PID) controller. Control performance is evaluated in terms of the number of spikes, the accuracy of spike input locations, and the accuracy of muscle force output. Results show that the cerebellar adaptive filter model can be applied without change to the control of systems driven by spiking inputs. The cerebellar algorithm results in good agreement between input spikes and force outputs and significantly improves on a PID controller. Input minimization can be used to reduce the number of spike inputs, but at the expense of a decrease in accuracy of spike input location and force output. This work extends the applications of the cerebellar algorithm and demonstrates the potential of the adaptive filter model to be used to improve functional electrical stimulation muscle control.
Robustness to Transformations Across Categories: Is Robustness Driven by Invariant Neural Representations?
Authors: Jang Hojin , Zaidi Syed Suleman Abbas , Boix Xavier , Prasad Neeraj , Gilad-Gutnick Sharon , Ben-Ami Shlomit , Sinha Pawan 
Published: October 2023

Abstract
Deep convolutional neural networks (DCNNs) have demonstrated impressive robustness to recognize objects under transformations (e.g., blur or noise) when these transformations are included in the training set. A hypothesis to explain such robustness is that DCNNs develop invariant neural representations that remain unaltered when the image is transformed. However, to what extent this hypothesis holds true is an outstanding question, as robustness to transformations could be achieved with properties different from invariance; for example, parts of the network could be specialized to recognize either transformed or nontransformed images. This article investigates the conditions under which invariant neural representations emerge by leveraging that they facilitate robustness to transformations beyond the training distribution. Concretely, we analyze a training paradigm in which only some object categories are seen transformed during training and evaluate whether the DCNN is robust to transformations across categories not seen transformed. Our results with state-of-the-art DCNNs indicate that invariant neural representations do not always drive robustness to transformations, as networks show robustness for categories seen transformed during training even in the absence of invariant neural representations. Invariance emerges only as the number of transformed categories in the training set is increased. This phenomenon is much more prominent with local transformations such as blurring and high-pass filtering than geometric transformations such as rotation and thinning, which entail changes in the spatial arrangement of the object. Our results contribute to a better understanding of invariant neural representations in deep learning and the conditions under which it spontaneously emerges.
Joint Impacts of Intraseasonal Oscillation and Diurnal Cycle on East Asian Summer Monsoon Rainfall
Authors: Liu Biqi , Chen Guixing , Qin Huiling 
Published: October 2023

Abstract
Intraseasonal and diurnal variations are two basic periodic oscillations in global/regional climate and weather. To investigate their joint impacts over East Asia, this paper categorizes the boreal summer intraseasonal oscillations (ISOs) in 1998–2019 into two groups with different diurnal cycles. It is shown that the active ISOs with large diurnal cycles feature a northwestward-moving anomalous anticyclone with strong southerlies at the western flank. These ISOs have in-phase patterns of geopotential height anomaly between low and midlatitudes over East Asia, associated with the simultaneous expansions of the western Pacific subtropical high (WPSH) and South Asian high (SAH). They couple with the anomalous ABL heating by daytime solar radiation over East Asia, which acts to enhance monsoon southerlies at midnight. The nocturnally strengthened southerlies facilitate dynamic lifting, moisture transport, and convective instability for producing midnight to morning rainfall at their northern terminus, thereby yielding a remarkable northward propagation of the monsoon rain belt. In contrast, the other ISOs with small diurnal cycles are related to a westward-moving anomalous anticyclone, while the WPSH and SAH have relatively small expansions and the westerly trough is active at middle latitudes. They lead to the dipole patterns of geopotential height anomaly and weak ABL heating over East Asia. The daily-mean southerlies and moisture conditions as well as their nocturnal enhancements are relatively weak, and thus, the northward shift of the monsoon rain belt is less pronounced. These results highlight that the large-scale conditions of ISOs can be distinguished by their different couplings with regional-scale diurnal forcings, which help the understanding and prediction of multiscale rainfall activities.
Development of hybrid plantain fiber/calcite particles reinforced polyvinyl chloride biocomposites for automobile applications
Authors: Oluwagbenga Adelani Samson , Oluwole Oladele Isiaka , Ilesanmi Akinbamiyorin , Akinlabi Oyetunji , Olanrewaju Olajesu Favor 
Published: October 2023

This study aimed to develop environmentally friendly PVC composites for automotive by incorporating plantain fiber (PF) and calcite particles (CP) as reinforcements. Different weight percentages of PF and CP (ranging from 3% to 15%) were utilized. The mixtures underwent compounding and compression molding at 150°C for 10 min. The mechanical and thermal properties of the resulting composites were analyzed, and their fracture surfaces were examined using SEM. Results indicated that the inclusion of these reinforcements significantly enhanced the properties of the composites compared to unreinforced samples, with the hybrid composites exhibiting the best performance. Optimal compositions were identified within the range of 6-8 wt% PF and 3-4 wt% CP. The composite containing 6 wt% PF/3 wt% CP showcased the highest ultimate tensile strength (63.77 MPa), optimum elongation at break, and best insulating property (0.24 W/Mk). The composite with 8 wt% PF/4 wt% CP demonstrated the highest tensile modulus (4.79 GPa), flexural strength (91.35 MPa), and flexural modulus (8.2 GPa). Impact strength peaked at 10 wt% PF/5 wt% CP, reaching 107.02 J/m2. These findings indicate that the developed hybrid reinforced biocomposite compositions hold great promise for various automotive applications, including instrument panels, sun visors, headlining, seals, floor coverings, and protective strips
Diagnostic delay of multiple sclerosis: prevalence, determinants and consequences
Authors: Uher Tomas , Adzima Adrian , Srpova Barbora , Noskova Libuse , Maréchal Bénédicte , Maceski Aleksandra Maleska , Krasensky Jan , Stastna Dominika , Andelova Michaela , Novotna Klara , Vodehnalova Karolina , Motyl Jiri , Friedova Lucie , Lindner Jiri , Ravano Veronica , Burgetova Andrea , Dusek Petr , Fialova Lenka , Havrdova Eva Kubala , Horakova Dana , Kober Tobias , Kuhle Jens , Vaneckova Manuela 
Published: October 2023

Background: Early diagnosis and treatment of patients with multiple sclerosis (MS) are associated with better outcomes; however, diagnostic delays remain a major problem. Objective: Describe the prevalence, determinants and consequences of delayed diagnoses. Methods: This single-centre ambispective study analysed 146 adult relapsing-remitting MS patients (2016–2021) for frequency and determinants of diagnostic delays and their associations with clinical, cognitive, imaging and biochemical measures. Results: Diagnostic delays were identified in 77 patients (52.7%), including 42 (28.7%) physician-dependent cases and 35 (24.0%) patient-dependent cases. Diagnosis was delayed in 22 (15.1%) patients because of misdiagnosis by a neurologist. A longer diagnostic delay was associated with trends towards greater Expanded Disability Status Scale (EDSS) scores ( B = 0.03; p = 0.034) and greater z-score of the blood neurofilament light chain ( B = 0.35; p = 0.031) at the time of diagnosis. Compared with patients diagnosed at their first clinical relapse, patients with a history of >1 relapse at diagnosis ( n = 63; 43.2%) had a trend towards greater EDSS scores ( B = 0.06; p = 0.006) and number of total ( B = 0.13; p = 0.040) and periventricular ( B = 0.06; p = 0.039) brain lesions. Conclusion: Diagnostic delays in MS are common, often determined by early misdiagnosis and associated with greater disease burden.
Read-depth based approach on whole genome resequencing data reveals important insights into the copy number variation (CNV) map of major global buffalo breeds
Authors: Ahmad Sheikh Firdous , Chandrababu Shailaja Celus , Vaishnav Sakshi , Kumar Amit , Gaur Gyanendra Kumar , Janga Sarath Chandra , Ahmad Syed Mudasir , Malla Waseem Akram , Dutt Triveni 
Published: October 2023

Abstract
Background
Elucidating genome-wide structural variants including copy number variations (CNVs) have gained increased significance in recent times owing to their contribution to genetic diversity and association with important pathophysiological states. The present study aimed to elucidate the high-resolution CNV map of six different global buffalo breeds using whole genome resequencing data at two coverages (10X and 30X). Post-quality control, the sequence reads were aligned to the latest draft release of the Bubaline genome. The genome-wide CNVs were elucidated using a read-depth approach in CNVnator with different bin sizes. Adjacent CNVs were concatenated into copy number variation regions (CNVRs) in different breeds and their genomic coverage was elucidated.

Results
Overall, the average size of CNVR was lower at 30X coverage, providing finer details. Most of the CNVRs were either deletion or duplication type while the occurrence of mixed events was lesser in number on a comparative basis in all breeds. The average CNVR size was lower at 30X coverage (0.201 Mb) as compared to 10X (0.013 Mb) with the finest variants in Banni buffaloes. The maximum number of CNVs was observed in Murrah (2627) and Pandharpuri (25,688) at 10X and 30X coverages, respectively. Whereas the minimum number of CNVs were scored in Surti at both coverages (2092 and 17,373). On the other hand, the highest and lowest number of CNVRs were scored in Jaffarabadi (833 and 10,179 events) and Surti (783 and 7553 events) at both coverages. Deletion events overnumbered duplications in all breeds at both coverages. Gene profiling of common overlapped genes and longest CNVRs provided important insights into the evolutionary history of these breeds and indicate the genomic regions under selection in respective breeds.

Conclusion
The present study is the first of its kind to elucidate the high-resolution CNV map in major buffalo populations using a read-depth approach on whole genome resequencing data. The results revealed important insights into the divergence of major global buffalo breeds along the evolutionary timescale.