bluuebunny/crossref_metadata_2025 huggingface dataset:
Strategic use of machine translation
Authors: Yuasa Mariko , Takeuchi Osamu
Published: November 2024

The development of generative artificial intelligence (AI) and its associated tools has revolutionised the
learning and use of foreign languages (L2). One such tool is machine translation (MT), which has become increasingly popular among
university students worldwide, spurring research on MT use in L2 writing. However, previous research has primarily focused on the
writing products of intermediate or advanced L2 learners, neglecting the writing process with MT of students with limited L2
proficiency. Therefore, this case study aimed to qualitatively explore how the Common European Framework of Reference for
Languages (CEFR) A2 university students employ strategies for L2 writing with MT and how their strategies change after strategy
instruction. Seven participants completed writing tasks on a PC before, immediately after, and four weeks after three one-hour
out-of-class instruction sessions based on the Strategic Content Learning (SCL) approach. Their writing process was
screen-recorded, followed by stimulated recall interviews to elicit their strategies, which were coded and categorised using a
framework by O’Malley and Chamot (1990). The results showed an increase in students’
elaborate use of strategies after instruction. In particular, strategy clusters were observed for all participants, demonstrating
their cognitive engagement in the writing process. Furthermore, first-language (L1)-related strategies were used more frequently
post-instruction, indicating learners’ efforts to create translation-friendly L1 input for MT. The findings suggest that teaching
MT-use strategies is crucial to fostering learners’ active engagement in the L2 writing process in a technology-enhanced learning
environment.
Achieving pure-fluorescent color-tunable WOLED through long-range coupling of spatially separated electron–hole pairs
Authors: Wang Guangyuan , Wang Yanbo , Guo Zhenyong , Kou Zhiqi
Published: November 2024

Color-tunable white organic light-emitting diode (CT-WOLED) with a wide correlated color temperature (CCT) offers numerous advantages in meeting human daily needs related to circadian rhythm. The study of CCT variation trends and the rules governing the expansion of the CCT range will help further improve the performance of such devices. This research proposes an effective strategy for achieving high-efficiency fluorescent CT-WOLEDs through long-range radiative coupling of spatially separated electron–hole pairs. After inserting a 5 nm thick DMAC-DPS layer between the donor (TAPC) and the acceptor (PO-T2T), the charge transfer excitons between TAPC and PO-T2T still exist. As the voltage increases, holes selectively undergo different photophysical processes, resulting in a wide CCT range. This demonstrates the extraordinary potential of spatially separated electron–hole pairs in regulating luminescent properties. By further introducing a bulk exciplex and the conventional red fluorescent dye DCJTB, the device’s efficiency, brightness, and CCT range have been further optimized. Additionally, significant highest occupied molecular orbital energy level difference between the hole transport layer TAPC and the spacer layer facilitates hole accumulation at the TAPC/spacer interface, thereby enhancing the long-range coupling effect. In device E, we achieved a wide CCT range of 2774 K along with a high external quantum efficiency of 9.2%. The results indicate that our proposed long-range coupling strategy not only enables a wide CCT range but also ensures broad spectral emission and high electroluminescence efficiency, providing new possibilities for the field of intelligent lighting.
Equation of state and universal solid phase of one-dimensional dipolar fluids
Authors: Meddour Sofiane , Bouzar Lila , Messina René
Published: November 2024

Macroscopic and structural properties of one-dimensional (1D) dipolar fluids are investigated theoretically. The equation of state is fully explored by means of analytical limiting laws, integral equations and corroborating Monte Carlo simulations. An interesting mapping with the Tonks gas (i.e. hard rods) is established at strong coupling. Crucially, we report a novel solid phase characterized by a universal algebraic decay of the pair distribution function whose range extends with increasing coupling. This discovery provides a clarified view in 1D systems and open new routes to explore theoretically as well as experimentally.
An unusual phase transition in a non-Hermitian Su–Schrieffer–Heeger model
Authors: Niveth A , Karthiga S , Senthilvelan M
Published: November 2024

This article studies a non-Hermitian Su–Schrieffer–Heeger model which has periodically staggered Hermitian and non-Hermitian dimers. The changes in topological phases of the considered chiral symmetric model with respect to the introduced non-Hermiticity are studied where we find that the system supports only complex eigenspectra for all values of u ≠ 0 and it stabilizes only non-trivial insulating phase for higher loss-gain strength. Even if the system acts as a trivial insulator in the Hermitian limit, the increase in loss-gain strength induces phase transition to non-trivial insulating phase through a (gapless) semi-metallic phase. Interesting phenomenon is observed in the case where Hermitian system acts as a non-trivial insulator. In such a situation, the introduced non-Hermiticity neither leaves the non-trivial phase undisturbed nor induces switching to trivial phase. Rather, it shows transition from non-trivial insulating phase to the same where it is mediated by the stabilization of (non-trivial) semi-metallic phase. This unusual transition between the non-trivial insulating phases through non-trivial semi-metallic phase gives rise to a question regarding the topological states of the system under open boundary conditions. So, we analyze the possibility of stable edge states in these two non-trivial insulating phases and check the characteristic difference between them. In addition, we study the nature of topological states in the case of non-trivial gapless (semi-metallic) region.
Experimental study of magnetorheological fluids under large periodic deformations
Authors: Horak Wojciech , Stępień Barbara , Sapiński Bogdan
Published: November 2024

Magnetorheological (MR) fluids are smart materials whose properties can be controlled by a magnetic field. They are used in a variety of applications with tailored operating parameters, facilitating broad and relatively straightforward implementation and control of the functional properties of these systems. The aim of the study was to determine the variation in shear stress of MR fluids under varying shear deformation directions and different magnetic field induction levels. The experiments were carried out with the use of three commercially available fluids: MRF-122EG, MRF-132DG, and MRF-140CG, which primarily differ in the volumetric fraction of ferromagnetic particles. These fluids are designed for use in mechanical energy dissipation devices, clutches, and brakes. They are also characterized by high stability and a broad controllability range. The experiments were performed using a rotational rheometer with a parallel plate measuring system to examine shear stress variability during both the deformation and rest phases. The study applied relatively large deformations, exceeding the linear viscoelastic range and the deformation corresponding to the yield point. The test results revealed variations in the shear stress values across successive loading cycles, as well as fluctuations during the rest phase. It was also found that, depending on magnetic field induction level (i.e. the level of fluid magnetization), the rest phase could result in either a decrease (relaxation) or an increase (hardening) in shear stress values. These findings have practical significance, particularly for MR fluid devices operating in shear mode.
Strain analysis by neutron diffraction on Nb3Sn strands in ITER central solenoid conductors of short and long twist pitch
Authors: Tomone Suwa , Takaaki Isono , Harjo Stefanus , Takuro Kawasaki , Kazuya Aizawa
Published: November 2024

The ITER central solenoid (CS) conductors are composed of Nb3Sn superconducting cables and stainless steel jackets. Approximately 60 000 electromagnetic loading cycles will be applied to the Nb3Sn strands in the CS conductor over the course of ITER tokamak operation, and the CS conductor is required to maintain the current sharing temperature (T
cs) for these electromagnetic loading cycles. However, in CS conductor prototypes, degradation of T
cs was observed after electromagnetic loading cycles. Visual inspections of the tested CS conductors revealed large bending and buckling of the Nb3Sn strands. These strand deformations were considered to be the cause of T
cs degradation because even a small amount of strain markedly affects the critical current of Nb3Sn strands. To prevent the strands from bending and buckling, the twist pitch of the cable was shortened to improve stiffness. The stiffer cables did prevent T
cs from degrading after electromagnetic loading cycles owing to the shortened twist pitch of the conductors, but a slight increase of T
cs was observed. Visual inspections revealed no significant bent or buckled strands, but small deformations cannot be investigated visually. Thus, internal strain was measured by neutron diffraction and the internal strain states of the prototype CS conductors having long twist pitches and the improved short-twist-pitch (STP) CS conductors were evaluated. The results indicated that, after electromagnetic loading cycles, bending of the strands in the STP CS conductor was limited and compressive strain was reduced. Therefore, we determined that this STP is not only effective to prevent degradation caused by bent strands but it also increases T
cs by reducing compressive strain.
Higher-order incompatibility improves distinguishability of causal quantum networks
Authors: Sudarsanan Ragini Nidhin , Sazim Sk
Published: November 2024

Higher-order quantum theory deals with causal quantum processes, described by quantum combs, and test procedures, described by quantum testers, ‘measuring’ these processes. In this work, we show that ‘jointly non-implementable’ or incompatible quantum testers perform better in distinguishability tasks than their compatible counterparts. To demonstrate our finding, we consider a specific two-party game based on distinguishing quantum combs. We show that the player does better at winning the game when they have exclusive access to incompatible testers over compatible ones. Moreover, we show that, using the resource theoretic measure convex weight, any general quantum resource present in testers is resourceful in quantum comb exclusion tasks. These investigations generalise, respectively, an earlier finding that incompatibility of quantum observables to be a bona fide resource in quantum state distinguishability tasks and another finding that any resource present in observables result in improved performance in state exclusion or antidistinguishability tasks.
Quantum neural networks to detect entanglement transitions in quantum many-body systems
Authors: El Ayachi F , Ait Mansour H , El Baz M
Published: November 2024

Quantum entanglement becomes increasingly complex to analyze in many-body systems due to exponential growth in complexity with system size. In this work, we explore the potential of quantum machine learning (QML) to circumvent this. Specifically, we train a parameterized quantum neural network (QNN) model to detect transitions in the entanglement properties of the ground state in a multi-spin Ising model. This approach enables the classification of different entanglement states and provides deeper insights into the behavior of entanglement under multi-spin interactions. Our results demonstrate that QML can effectively simplify the classification process and overcome the complexity challenges encountered by classical algorithms.
Large-scale shell-model study of 2νECEC process in 78Kr
Authors: Patel Deepak , Srivastava Praveen C
Published: November 2024

In this work, we present the systematic study of 2νECEC process in the 78Kr using large-scale shell-model calculations with the GWBXG effective interaction. We first validate the efficiency of the utilized interaction by comparing the theoretical low-lying energy spectra, the kinematic moment of inertia, and reduced transition probabilities with the experimental data for both the parent and grand-daughter nuclei 78Kr and 78Se, respectively. Additionally, we examine the shell-model level densities of the 1+ states in the intermediate nucleus 78Br, comparing them with the predictions from the Back-shifted Fermi gas model. We analyze the variation of cumulative nuclear matrix elements (NMEs) for the 2νECEC process in 78Kr as a function of 1+ state energies in the intermediate nucleus 78Br up to the saturation level. Our estimated half-life for 78Kr, extracted from the shell-model predicted NMEs, shows good agreement with the experimental value. The Gamow-Teller transitions from the lowest 1+ state of 78Br via both the EC+β
+ and β
−-channels are also discussed.
Transverse instability of electron-acoustic solitons in a relativistic degenerate astrophysical magnetoplasma
Authors: Misra A P , Abdikian A
Published: November 2024

We study the nonlinear theory of small-amplitude electron-acoustic solitons (EASs) in a relativistic astrophysical magnetoplasma consisting of two-temperature electrons: a sparse population of relativistic nondegenerate classical electrons and a group of fully degenerate dense relativistic electrons (main constituent) immersed in a static magnetic field with a neutralizing stationary ion background. By using the multiple-scale reductive perturbation technique with the Lorentz transformation, the Zakharov-Kuznetsov (ZK) and the modified Zakharov-Kuznetsov (mZK) equations are derived to describe the evolution of EASs in two different regimes of relativistic degeneracy: r

d0 < 50 and r

d0 ≳ 50, where

r

d
0

=

n

d
0

/

n

cr

1

/

3

is the degeneracy parameter in which n

d0 is the unperturbed number density of degenerate electrons and n
cr ≈ 6 × 1029 cm−3 the critical number density at which p

F
=m

ec
and which defines the emergence of the relativistic regime. Here, p

F
is the Fermi momentum, m

e
is the invariant electron mass, and c is the speed of light in vacuum. The characteristics of the plane soliton solutions of ZK and mZK equations and the soliton energy are studied. We show that the solitons moving at an angle α to the external magnetic field can be unstable under transverse long-wavelength perturbations. The growth rates of instabilities are obtained and analyzed with the effects of the relativity parameter β
cl = k

B

T
cl/m

e

c
2 and the degeneracy parameter r

d0, where k

B
is the Boltzmann constant and T
cl is the temperature of classical electrons. Interestingly, the ZK solitons, even if it is stable for the first-order perturbations, can be unstable in the second-order correction. Furthermore, while the first-order growth rates of perturbations for ZK solitons tend to vanish as α → 38°, that for the mZK soliton goes to zero as α → 90°. However, depending on the angle α, the growth rates are found to be reduced either by increasing the values of β
cl or by decreasing the values of r

d0. The applications of our results to astrophysical plasmas, such as those in the environments of white dwarfs are discussed.
Quantum Flutter from Nonlinear Luttinger Liquid perspective
Authors: Wang Sheng , Zhang Zhehao , Guan Xi-Wen
Published: November 2024

Quantum flutter is a ubiquitous phenomenon which can be observed from the fast moving impurityinjected into a fermionic or bosonic medium of quantum liquid. In this scenario, one usually considera medium of a fully polarized state and inject a spin-flipped impurity as the initial state. When theinitial velocity of the impurity is beyond the intrinsic sound velocity of the medium, the impuritymomentum dramatically exhibits a long-lived periodic oscillation with the periodicity remaininginvariant with respect to the initial velocity. In this letter, we show that such a novel phenomenoncan be explained by a linear Luttinger liquid coupled to a deep hole in the Fermi sea. Once thedeep hole excitations are involved and the impurity momentum surpass the Fermi momentum,the propagator thus displays a periodic oscillation after a quick relaxation decay. The oscillationperiodicity is solely determined by the energy of the deepest hole excitation. Our result providesdeep insights into the dynamical behavior of quantum impurities immersed into one-dimensionalquantum liquids.
A multi‐feature fusion graph attention network for decoding motor imagery intention in spinal cord injury patients
Authors: Leng Jiancai , Gao Licai , Jiang Xiuquan , Lou Yitai , Sun Yuan , Wang Chen , Li Jun , Zhao Heng , Feng Chao , Xu Fangzhou , Zhang Yang , Jung Tzyy-Ping
Published: November 2024

Objective. Electroencephalogram (EEG) signals exhibit temporal–frequency–spatial multi-domain feature, and due to the nonplanar nature of the brain surface, the electrode distributions follow non-Euclidean topology. To fully resolve the EEG signals, this study proposes a temporal–frequency–spatial multi-domain feature fusion graph attention network (GAT) for motor imagery (MI) intention recognition in spinal cord injury (SCI) patients. Approach. The proposed model uses phase-locked value (PLV) to extract spatial phase connectivity information between EEG channels and continuous wavelet transform to extract valid EEG information in the time–frequency domain. It then models as a graph data structure containing multi-domain information. The gated recurrent unit and GAT learn EEG’s dynamic temporal–spatial information. Finally, the fully connected layer outputs the MI intention recognition results. Main results. After 10 times 10-fold cross-validation, the proposed model can achieve an average accuracy of 95.82%. Furthermore, this study analyses the event-related desynchronization/event-related synchronization and PLV brain network to explore the brain activity of SCI patients during MI. Significance. This study confirms the potential of the proposed model in terms of EEG decoding performance and provides a reference for the mechanism of neural activity in SCI patients.
Narrative review of proximal tubular epithelial cell in-vitro co-culture models
Authors: Varda Luka , Petreski Tadej , Gradišnik Lidija , Maver Uroš , Bevc Sebastjan
Published: November 2024

Kidney diseases are among the leading causes of death globally. With the increasing rates of acute kidney injury (AKI) requiring hospitalisation, a better understanding of pathophysiological mechanisms is needed to treat the patients more efficiently. Nephrotoxicity is one of the most common causes of AKI, mainly due to the high availability of over-the-counter drugs and natural supplements, which may interact with prescribed drugs at the level of pharmacokinetics, among other factors. The latter can lead to clinically relevant complications (including AKI), which is even more pronounced given the increasingly ageing population in the Western world and the associated increase in polypharmacy. Drug testing starts at the preclinical level, where a reliable model is needed to predict human response to a tested drug with sufficient accuracy. Recently, in-vitro kidney models of different complexities have been created to study various aspects of kidney diseases. Because the proximal tubule plays a vital role in several mechanisms, many models include proximal tubular epithelial cells (PTECs). Monocultures of PTECs do not represent in-vivo tissue accurately enough. Therefore, more complex models with more cell types are being built. To our knowledge, this is the first review focusing on co-culture models and cell types used alongside PTECs for studying the nephrotoxicity of drugs and other mechanisms of AKI and chronic kidney disease.
Novel in situ and rapid self-gelation recombinant collagen-like protein hydrogel for wound regeneration: mediated by metal coordination crosslinking and reinforced by electro-oxidized tea polyphenols
Authors: Sun Yue , Gao Cungang , Jia Pengxin , Song Liang , Kang Jia , Han Min , Yu Wenfa , Nian Rui
Published: November 2024

Recombinant collagen holds immense potential in the development of medical functional materials, yet its widespread application remains hindered by the absence of a suitable self-assembly strategy. In this article, we report the discovery that the bacterial-derived collagen-like (CL) protein Scl2 can rapidly self-gelation (∼1 min at pH ∼7) due to properties enabled by metal coordination crosslinking. This was achieved by fusing metal ion chelating peptides to both termini of the protein. Our research further reveals the critical role of electrostatic interaction between globular domains (V domains) of recombinant collagen in the self-assembly process. We show that modifying the negative charge load of the N-terminal α-helix of the V domain enables control over the self-assembly time (from 1 min to 30 min) and strength (from 8 kPa to 26 kPa) of the Scl2 hydrogel. By adjusting the molecular weight of the core CL domain, we have remarkably further enhanced the strength of the Scl2 hydrogel to 78 kPa. Moreover, we innovatively employed electro-oxidized tea polyphenols to enhance the stability of the Scl2 hydrogel, resulting in the formation of a reliable self-assembled metal coordination hydrogel at physiological temperature. This approach not only eliminates the need for toxic chemical crosslinking agents but also confers the material with multiple functionalities, such as adhesion, antibacterial, and antioxidant properties. The novel recombinant Scl2 hydrogel exhibited exceptional in situ self-gelation and injectable properties. This innovative hydrogel not only demonstrates remarkable biological activity but also exhibits remarkable tissue repair-promoting capabilities in full-thickness skin injury models (shorten healing cycle by more than 30%). The convenient and versatile nature of this recombinant collagen hydrogel makes it promising for clinical applications in injury treatment, demonstrating broad applications in the future.
Bioprinting a resilient and transparent cornea stroma equivalent: harnessing dual crosslinking strategy with decellularized cornea matrix and silk fibroin hybrid
Authors: Ghosh Anwesha , Bera Ashis Kumar , Ghosh Soham , Singh Vivek , Basu Sayan , Pati Falguni
Published: November 2024

Bioprinting a resilient yet optically transparent corneal tissue substitute remains a challenge. In this study we introduce an innovative methodology aimed at bolstering the mechanical and optical attributes of silk fibroin (SF) hydrogels, pivotal for the progression of cornea tissue engineering. We devised a unique eosin Y-based photoinitiator system to instigate di-tyrosine linkages within highly concentrated pristine SF solutions under green light exposure. This pioneering technique resulted in SF hydrogels fortified by dityrosine covalent bonds, preserving exceptional transparency and soft elastomeric qualities devoid of spontaneous transitions to stiff, opaque beta-sheet conformations. Furthermore, we synergistically combined SF with decellularized cornea matrix (DCM) hydrogel, leveraging photo-polymerization under green light followed by thermal gelation to establish resilient and stable gel formation. The ensuing dual crosslinked hybrid hydrogels exhibited superior mechanical and thermal resilience in comparison to dual crosslinked DCM hydrogels. The inclusion of SF in DCM further augmented the hydrogel’s elasticity and shear recovery, positioning it as an optimal bioink for cornea bioprinting endeavors. During the extrusion printing process, photocrosslinking of the bioink superficially fortified SF and DCM polymer chains via di-tyrosine linkages, furnishing initial stability and mechanical fortitude. Subsequent post-printing thermal gelation further reinforced collagen chains through self-assembly. Notably, the bioprinted cornea constructs, housing human limbal mesenchymal stem cells, manifested transparency, structural integrity, and optimal functionality, underscored by the expression of keratocyte proteoglycans. In summation, our engineered 3D constructs exhibit promising potential for in vivo applications in cornea tissue engineering, marking a significant stride forward in the field’s advancement.
Climate change perceptions, expectations, observations, and projections at Lake Victoria
Authors: Liersch Stefan , Broek Karlijn van den , Pilz Tobias , Isyaku Usman , Chappin Maryse , Böhm Gisela , Mbilingi Bwambale , Luomba Joseph , Awuor Fonda Jane , Kayanda Robert , Mahongo Shigalla , Ogunbode Charles , Nyamweya Chrispine , Kubiriza Godfrey K. , Wanguche Patrick Otuo , Aura Christopher Mulanda , Kishe Mary A. , Okello William , Kariuki Paul Njoroge , Adam Emelda Teikwa , Koch Hagen
Published: November 2024

Understanding people's perceptions of climate change and associated environmental risks is paramount in assessing how individuals respond to climate change. Awareness of the consequences of climate change determines the present and future behaviours and expectations, as well as the actions taken to mitigate the likely impacts. We surveyed the perceived and expected climate change consequences of experts and community members in the Lake Victoria basin in East Africa, compared them with hydro-meteorological observations and projections, and established that some perceived trends, such as increasing temperature or rainfall intensity, correspond with meteorological observations. However, the perceived increase in drought occurrence (believed to be a recent consequence), was not substantiated by the meteorological data. It was only in the northwestern region that drought frequency increased since the year 2000, while the rest of the basin did not experience such a trend. Community members were concerned about the already noticeable consequences of climate change on their livelihoods through agriculture or fishing, while experts were mainly focused on the amplification of hazards such as floods and droughts. This divergence may imply that experts underestimate the consequences that society is already facing. Nevertheless, both groups expect that climate change will undoubtedly lead to the deterioration of human well-being by affecting food security, increasing poverty, and increasing the incidence of disease. This is a serious concern that requires immediate attention. Such insights into people's climate change perceptions can help policy-makers, researchers, and community members to better tailor adaptation solutions acceptable to the local context. Effective governance is essential to enable people to adapt to climate change and other challenges, including those resulting from the impacts of globalisation, demographic trends, and the degradation and scarcity of resources.
Urban building energy models: how can we improve the treatment of uncertainty for energy policy decision-making?
Authors: Fennell Pamela J , Ebrahimigharehbaghi Shima , Mata Érika , Kokogiannakis Georgios , Amrith Shyam , Ignatiadou Sotiria , Piamo Samuele Lo
Published: November 2024

Urban Building Energy Models (UBEMs) are emerging as a powerful tool for cities and regions seeking to make decisions on the best pathways for increasing the energy efficiency of their buildings. As model results are used to inform critical policy decisions, it is essential to understand and communicate the limits of inference of model results and how sensitive they are to changes in inputs. In the absence of standard datasets and protocols for model validation, Uncertainty Analysis and Sensitivity Analysis (UASA) procedures offer vital insights. However, there is no consensus on how UASA should be applied to bottom-up building physics-based UBEMs, nor on how different use cases might influence the choice of UASA approach. This study uses a systematic review of the literature (2009–2023) to explore the procedures which are applied and assess their appropriateness. We find a need for a more holistic view of uncertainty to be taken, and present a decision framework for selecting the most appropriate form of quantitative sensitivity analysis, based on model form, data provenance and use case. We also propose a number of approaches to improve the application of sensitivity analysis in UBEM studies, including the importance of undertaking a complementary assessment of information quality.
Femtosecond laser micro/nano processing: from fundamental to applications
Authors: Gao Le , Zhang Qiming , Gu Min
Published: November 2024

Able to precisely control and manipulate materials’ states at micro/nano-scale level, femtosecond (fs) laser micro/nano processing technology has undergone tremendous development over the past three decades. Free-forming three-dimensional (3D) microscale functional devices and inducing fascinating and unique physical or chemical phenomena have granted this technology powerful versatility that no other technology can match. As this technology advances rapidly in various fields of application, some key challenges have emerged and remain to be urgently addressed. This review firstly introduces the fundamental principles for understanding how fs laser pulses interact with materials and the associated unique phenomena in section 2. Then micro/nano-fabrication in transparent materials by fs laser processing is presented in section 3. Thereafter, several high efficiency/throughput fabrication methods as well as pulse-shaping techniques are listed in sections 4 and 5 reviews four-dimensional (4D) and nanoscale printing realized by fs laser processing technology. Special attention is paid to the heterogeneous integration (HI) of functional materials enabled by fs laser processing in section 6. Several intriguing examples of 3D functional micro-devices created by fs laser-based manufacturing methods such as microfluidics, lab-on-chip, micro-optics, micro-mechanics, micro-electronics, micro-bots and micro-biodevices are reviewed in section 7. Finally, a summary of the review and a perspective are proposed to explore the challenges and future opportunities for further betterment of fs laser micro/nano processing technology.
Modular scaffolds with intelligent visual guidance system for in situ bone tissue repair
Authors: Shao Huifeng , Xia Pengcheng , Zhang Tao , Shi Jinyuan , Huang Zhiqiang , Yuan Xianqi , Nian Zhiheng , Zhao Xiao , Zhou Rougang , Gong Youping , He Yong
Published: November 2024

In clinical practice, the irregular shapes of traumas pose a significant challenge in rapidly manufacturing personalized scaffolds. To address these challenges, inspired by LEGO® bricks, this study proposed a novel concept of modular scaffolds and developed an innovative system based on machine vision for their rapid and intelligent assembly tailored to defect shapes. Trapezoidal interfaces effectively connect standardized bone units based on magnesium-doped silicate calcium, ensuring high stability of the modular scaffolds, with compressive strength up to 135 MPa and bending strength up to 17 MPa. Through self-developed defect recognition and reconstruction algorithms, defect recognition and personalized assembly schemes for bone scaffolds can be achieved autonomously. Modular scaffolds seamlessly integrate with surrounding bone tissue, promoting new bone growth, with no apparent differences compared to fully 3D printed integral scaffolds in the skull and femur repair experiments. In summary, the adoption of modular scaffolds not only integrates personalization and standardization but also satisfies the optimal treatment window.
The resilience value of residential solar + storage systems in the continental U.S.
Authors: Baik Sunhee , Miller Cesca , Carvallo Juan Pablo
Published: November 2024

Behind the meter rooftop solar plus storage (PVESS) has the potential to benefit the hosting customers by providing affordability, environmental, and reliability and resilience value. Whereas the bill reduction and environmental benefits of PVESS are well studied, its monetary resilience benefits are less understood. The increasing trend of power interruptions driven by extreme weather events heightens the need to understand these benefits. This study leverages various publicly available datasets to perform a cost benefit analysis of adding to determine the resilience value of PVESS for a typical single family home in each county in the continental U.S. We find that PVESS is very effective to technically mitigate interruptions across the country. However, the monetary benefits in the base case only cover about 14% of battery costs, with no county exceeding 60%. This is somewhat expected, given that PVESS provide other monetary benefits that are not part of this analysis. Through sensitivities, we find that higher frequency of extreme weather events roughly triples the resilience value of PVESS and that higher values of lost load double the same metric. Our sensitivity analysis shows that the benefit cost ratio of PVESS for customers living in areas with higher-than-average frequency of long duration interruptions and value of lost load is already above one even without considering other value streams. We conclude with recommendations that regulators and utilities could implement to enable customers to calculate and capture the resilience value of PVESS more efficiently.
Scaling rainwater harvesting for irrigation in Kenya: potential sustainability risks and the need for adaptive governance
Authors: Singh Radhika , Oguge Nicholas , Odote Collins
Published: November 2024

Rainwater harvesting for irrigation (RWHI) systems offer many benefits to smallholder farmers in Kenya, including the possibility of agricultural intensification and improved resilience to climate change in more arid areas. However, the scaling of RWHI systems could inadvertently pose risks to environmental, social, and economic sustainability. Governance institutions in Kenya tasked with managing RWHI adoption processes are often unaware of such risks and ill-equipped to manage them when they emerge. To address this gap, this article first presents key insights from the literature on innovation scaling and adaptive governance on how undesirable effects of scaling can be mitigated. Then, based on the results of a global literature review and a case study in Kenya, it outlines potential environmental, social, and economic risks of scaling RWHI that may manifest in the Kenyan context. Environmentally, the biggest risk is that widespread adoption of RWHI, while increasing water availability at the household level, will alter hydrological flows and impact ecosystem functioning. Socially, major risks of scaling RWHI include increased inequities in water access and rights, as those with the resources to adopt RWHI are able to store and use more water than others. Finally, economic risks may emerge when farmers who have adopted RWHI to grow cash crops experience heightened vulnerability to market fluctuations. The article ends with a discussion on governance approaches that could be applied to ensure responsible RWHI scaling in Kenya. Key recommendations include creating institutions that embed adaptive governance mechanisms, democratizing the development of scaling strategies to ensure their collective ownership, and enhancing monitoring and data collection capacities for effective response. These measures aim to balance short-, medium-, and long-term objectives across various scales and user groups to maximize sustainability outcomes during RWHI scaling processes.
A systematic review of progress in food security research and implications for achievement of the UN’s zero-hunger goal in Bangladesh
Authors: Hossain Abdul Mohammed Mokter , Hossain Md Sarwar , Tortajada Cecilia
Published: November 2024

Despite numerous policy initiatives to achieve food security, more than 2 billion people are food insecure across the world. Food security research can help addressing food insecurity effectively by summarizing the state of knowledge and providing future research direction to make sure no one is left behind. Yet, there are no comprehensive studies of food security research in Global South countries such as in Bangladesh, where nearly one-third of the population is food insecure. Here, this systematic review aims to identify the progress, gaps, and future research directions for food security in Bangladesh by investigating current research trends and the influence of socioeconomic and environmental drivers on food security and recommend policy interventions for achieving the zero-hunger goal of the Sustainable Development Goals (SDGs). We systematically reviewed articles both quantitatively and qualitatively and summarized the trends, methods, challenges, and opportunities of food security research in Bangladesh. Our findings reveal that longitudinal trends and inequality in food security across administrative and agroecological zones are underexplored. Moreover, most studies focused on the influence of socioeconomic drivers, with insufficient attention to environmental drivers, and none examined the causal relationships among them. The access and availability dimensions of food security are the most studied, while stability and utilization are the least addressed in food security research. Addressing these gaps is essential for establishing a sustainable food system that may help Bangladesh achieving the SDG target of ending hunger (SDG 2) and ensuring no one is left behind.
Introduction: Victimhood in Transition
Authors: Lawther Cheryl
Published: November 2024

Chapter 1 sets the book in its scholarly and empirical context. The chapter begins by setting out the two key pillars of scholarly work on which this book rests. The first part of the chapter, ‘The Rise of the Victim’, contextualises the growing centrality of victims in transitional justice and elaborates on claims of a mismatch between the rhetoric and reality of victim centrism. The second part of the chapter, ‘Defining Victimhood: Innocence, Guilt, and Beyond’, traces the conceptualisation and construction of victimhood in criminology and transitional justice. The chapter then establishes the empirical foundations of the book, providing a brief overview of the Northern Ireland conflict, the nature of victimhood, and the politicisation of pain. A discussion on the research design and methodological considerations which informed the fieldwork on which the book is based follows. The chapter concludes by offering a brief overview of the chapters to come.
Victimhood and Voice
Authors: Lawther Cheryl
Published: November 2024

The objective of Chapter 4 is to go beyond the existing theory and practice on ‘victim-centred’ transitional justice to examine the challenges, dangers, and contradictions that are inherent to the exercise of victims’ voices. The chapter argues that what we come to hear and know as ‘victims’ voices’ shapes the construction and reproduction of victimhood and often does so in profoundly discomforting ways. The chapter addresses three overlapping areas. First, the chapter examines the intersection between the use of victims’ voices and political claims-making. Second, the chapter addresses the ossification of victims’ voices around their experience of death and injury, with the risk that victims become defined ‘by’ their voice and their identity is reduced to the point of trauma. Third, the chapter turns to a critical examination of the argument that victimhood confers epistemic privilege and how this assumed privilege translates regarding hearing and receiving voice.
Victimhood and the Haunting of Lives, Landscapes, and Unresolved Pasts
Authors: Lawther Cheryl
Published: November 2024

Building on approaches to ghosts and haunting by Gordon (1997), Chapter 7 focuses on the haunting presence of the unresolved past and its impact on the construction, reproduction, and politicisation of victimhood. This chapter argues for three conceptualisations of haunting when past traumas remain unaddressed. The first of these—‘Haunting and Lost Lives’—examines the haunting impact of the failure to deal with the legacy of conflict by way of truth, justice, or reparations for example. Under the heading of ‘The Haunting of Landscape’, the second part of the chapter examines how landscape and physical structures are also capable of ‘holding’ memories, conjuring up and housing spectres of the past. The final conceptual theme—‘Victimhood, Haunting, and Trauma’—critically explores how the failure to comprehensively deal with the legacy of conflict and human rights abuses can contribute to high levels of conflict-related mental health problems and transgenerational trauma.
Nut consumption and disability-free survival in community-dwelling older adults: a prospective cohort study
Authors: Wild Holly , Nurgozhina Madina , Gasevic Danijela , Coates Alison M , Woods Robyn L , Ryan Joanne , Beilin Lawrence , Govindaraju Thara , McNeil John J , Owen Alice J
Published: November 2024

Objectives

The relationship between nut intake and disability-free survival (healthy lifespan) in later life is unclear. The objective was to evaluate the association between nut intake and disability-free survival in a cohort of adults aged ≥70 years, and whether this varied according to overall diet quality.

Methods

This prospective cohort study involved 9916 participants from the ASPREE Longitudinal Study of Older Persons. Participants completed a 49-item Food Frequency questionnaire from which frequency of nut intake was obtained and were asked to categories usual intake as no/infrequent [never/rarely, 1–2 times/month], weekly [1–2 times/week, often 3–6 times/week] or daily [every day or several times a day]. The outcome measured was a composite of first-event mortality, onset of dementia, or persistent physical disability. Cox proportional hazards regression models, adjusted for socio-demographic factors, health-related and clinical covariates and overall dietary quality were conducted to examine the association between varying levels of nut intake and disability-free survival.

Results

Over a mean of 3.9 years of follow-up, the risk of reaching the DFS endpoint were 23% lower (HR 0.77 [0.61–0.98]) for those who consumed nuts daily, when compared to those with no/infrequent nut consumption. Subgroup analysis demonstrated a significant association between daily nut consumption and healthy lifespan among individuals in the second dietary quality tertile (HR 0.71[0.51–0.98]).

Conclusion

For community-dwelling adults aged 70 years and over with sub-optimal diets, daily nut consumption is associated with the promotion of healthy lifespan (disability-free survival).
A gentle introduction to pangenomics
Authors: Matthews Chelsea A , Watson-Haigh Nathan S , Burton Rachel A , Sheppard Anna E
Published: November 2024

Pangenomes have emerged in response to limitations associated with traditional linear reference genomes. In contrast to a traditional reference that is (usually) assembled from a single individual, pangenomes aim to represent all of the genomic variation found in a group of organisms. The term ‘pangenome’ is currently used to describe multiple different types of genomic information, and limited language is available to differentiate between them. This is frustrating for researchers working in the field and confusing for researchers new to the field. Here, we provide an introduction to pangenomics relevant to both prokaryotic and eukaryotic organisms and propose a formalization of the language used to describe pangenomes (see the Glossary) to improve the specificity of discussion in the field.
Digital annealing optimization for natural product structure elucidation
Authors: Lee Chien , Wang Pei-Hua , Tseng Yufeng Jane
Published: November 2024

The digital annealer (DA) leverages its computational capabilities of up to 100 000 bits to address the complex nondeterministic polynomial-time (NP)-complete challenge inherent in elucidating complex structures of natural products. Conventional computational methods often face limitations with complex mixtures, as they struggle to manage the high dimensionality and intertwined relationships typical in natural products, resulting in inefficiencies and inaccuracies. This study reformulates the challenge into a Quadratic Unconstrained Binary Optimization framework, thereby harnessing the quantum-inspired computing power of the DA. Utilizing mass spectrometry data from three distinct herb species and various potential scaffolds, the DA proficiently locates optimal sidechain combinations that adhere to predefined target molecular weights. This methodology enhances the probability of selecting appropriate sidechains and substituted positions and ensures the generation of solutions within a reasonable 5-min window. The findings underscore the transformative potential of the DA in the realms of analytical chemistry and drug discovery, markedly improving both the precision and practicality of natural product structure elucidation.
Dynamic factor analysis with dependent Gaussian processes for high-dimensional gene expression trajectories
Authors: Cai Jiachen , Goudie Robert J B , Starr Colin , Tom Brian D M
Published: November 2024

The increasing availability of high-dimensional, longitudinal measures of gene expression can facilitate understanding of biological mechanisms, as required for precision medicine. Biological knowledge suggests that it may be best to describe complex diseases at the level of underlying pathways, which may interact with one another. We propose a Bayesian approach that allows for characterizing such correlation among different pathways through dependent Gaussian processes (DGP) and mapping the observed high-dimensional gene expression trajectories into unobserved low-dimensional pathway expression trajectories via Bayesian sparse factor analysis. Our proposal is the first attempt to relax the classical assumption of independent factors for longitudinal data and has demonstrated a superior performance in recovering the shape of pathway expression trajectories, revealing the relationships between genes and pathways, and predicting gene expressions (closer point estimates and narrower predictive intervals), as demonstrated through simulations and real data analysis. To fit the model, we propose a Monte Carlo expectation maximization (MCEM) scheme that can be implemented conveniently by combining a standard Markov Chain Monte Carlo sampler and an R package GPFDA,which returns the maximum likelihood estimates of DGP hyperparameters. The modular structure of MCEM makes it generalizable to other complex models involving the DGP model component. Our R package DGP4LCF that implements the proposed approach is available on the Comprehensive R Archive Network (CRAN).