bluuebunny/crossref_metadata_2025 huggingface dataset:
Compounds of amine-substituted cyclic amines: synthesis and structures
Authors: Curtis Neil F.
Published: August 2022

Cyclic tetra-amines with amine substituents on the central carbon atom of C3 ring segments are readily prepared by reduction of nitro-substituted aza-macrocycles, formed by reactions of metal-ion amine compounds with formaldehyde and a nitro-alkane. Reactions of bis-(ethane-1,2-diamine)-copper(ii) or -nickel(ii) cations with formaldehyde and nitroethane form the trans (anti) and cis (syn) isomers of (6,13-dimethyl-6,13-di-nitro-1,4,8,11-tetra-azacyclotetradecane)-copper(ii) or -nickel(ii)) cations, which are readily reduced to form the trans and cis-6,13-diamino cations, from which the trans- and cis-amine substituted cyclic tetra-amines can be isolated. Similar reactions for the (3,7-diaza-nonane-1,9-diamine)-copper(ii) or -nickel(ii) cations lead to 6-methyl-1,4,8,11-tetra-azacyclotetradecane-6-amine. Amine-substituted cyclic tetra-amines with different ring sizes or alkyl substituents can similarly be prepared by using different diamines or alkyl-nitro compounds. This review is primarily about compounds formed by trans-6,13-diamino and 6-amino-1,4,8,11-tetraazacyclotetradecanes with d-transition-metal ions. The amines react with transition-metal ions in much the same manner as 1,4,8,11-tetraazacyclotetradecane (cyclam), forming compounds with isomeric configurations arising from the four chiral nitrogen centres of coordinated cyclam, the cis- or trans-configurations of the amine substituents and a form of geometrical isomerism arising from the relationship between the chiral coordinated cyclam configuration and the orientation of the substituents. The amine-substituted cyclams coordinate by the four cyclam nitrogen atoms, in planar or folded arrangements, and also by one or both of the amine substituents. Non-coordinated amine substituents can be protonated. The amine substituents can be modified by methylation, amide formation and reaction with aldehydes to form imines. The imines formed with functionalised aldehydes can be reduced to form variously functionalised secondary amine substituents. This all leads to complex coordination chemistry and X-ray crystallographic structure determinations have been critical in understanding the configurations present. Structures in the Cambridge Crystallographic Data Base of all relevant compounds are listed.
Identification of quantitative trait loci governing biosynthesis of phospholipids in soybean
Authors: Anshu Aseem Kumar , Kumar Vineet , Rani Anita , Tayalkar Trupti , Parmar Hamendra Singh
Published: August 2022

Context Soybeans (Glycine max. (L.) Merr.) are a major source of phospholipids, which are vital to human and animal nutrition, as well having many pharmaceutical and industrial applications. Identification of quantitative trait loci (QTLs) is a prerequisite for the development of high-phospholipid soybean genotypes through marker-assisted breeding. Aims We aimed to identify QTLs associated with biosynthesis of four phospholipids in soybean. Methods We developed two F2 populations comprising 233 and 254 plants, respectively, from two crosses (JS20-34 × AVKS215 and JS20-98 × AVKS215), and used 208 polymorphic simple sequence repeat markers found common to both F2 populations for linkage map construction. QTLs associated with four phospholipids, phosphatidylethanolamine (PE), phosphatidic acid (PA), phosphatidylinositol (PI) and phosphatidylcholine (PC), were analysed via inclusive composite interval mapping of additive QTLs using QTL IciMapping software. Key results In the respective F2 populations, we identified seven and six QTLs for PE, seven and nine QTLs for PA, and nine and eight QTLs for PC. Six QTLs were associated with PI in each population. Five QTLs for each of PA and PC, three QTLs for PE, and four QTLs for PI were found common to both F2 populations. Conclusions The results showed that some genomic regions such as Sat_341–Satt331 on chromosome 10, and Satt325–Sat_387 and Sat_229–Satt510 on chromosome 13, were associated with all four phospholipids in both F2 populations. QTLs associated with phospholipids were also found to be annotated with genes involved in phospholipid biosynthesis. Implications The QTLs identified may be useful in marker-assisted breeding for the development of soybean genotypes with high levels of phospholipids of interest and for identifying functional genes involved in phospholipid biosynthesis.
Digital computing through randomness and order in neural networks
Authors: Pitti Alexandre , Weidmann Claudio , Quoy Mathias
Published: August 2022

We propose that coding and decoding in the brain are achieved through digital computation using three principles: relative ordinal coding of inputs, random connections between neurons, and belief voting. Due to randomization and despite the coarseness of the relative codes, we show that these principles are sufficient for coding and decoding sequences with error-free reconstruction. In particular, the number of neurons needed grows linearly with the size of the input repertoire growing exponentially. We illustrate our model by reconstructing sequences with repertoires on the order of a billion items. From this, we derive the Shannon equations for the capacity limit to learn and transfer information in the neural population, which is then generalized to any type of neural network. Following the maximum entropy principle of efficient coding, we show that random connections serve to decorrelate redundant information in incoming signals, creating more compact codes for neurons and therefore, conveying a larger amount of information. Henceforth, despite the unreliability of the relative codes, few neurons become necessary to discriminate the original signal without error. Finally, we discuss the significance of this digital computation model regarding neurobiological findings in the brain and more generally with artificial intelligence algorithms, with a view toward a neural information theory and the design of digital neural networks.
Recombinant rumen bacteria: problems and opportunities.
Authors: Kobayashi Y.
Published: August 2022

Gene manipulation of rumen bacteria was initiated in the early 1980s with most of the effort primarily focused on developing plasmid vectors. From the 1990s, more functional (fibrolytic, essential amino acid-producing or detoxifying) rumen bacteria were produced using stable and efficient host vector systems, all of which were based on the sophisticated DNA and protein engineering techniques that had been developed in the preceding decade. However, the recombinants often suffered from poor settlement in the rumen when inoculated, showing rapid decreases in abundance within hours or a few days. However, a mixture of four recombinants, each exhibiting detoxifying enzyme activity, was settled in the rumen of sheep at a level up to 10
7
/ml. This level was high enough to degrade the toxic monofluoroacetate offered in the diet, making the sheep tolerant to the toxin. This success demonstrated the potential of using recombinants and suggested strategies for successfully settling recombinants in the rumen. In addition to promoting animal health and production, the gene cloning system for rumen bacteria may be used to clone genes and produce proteins that, to date, can not be cloned and expressed in an
Escherichia coli
system. This review describes (i) the methodology of gene manipulation; (ii) recombinant rumen bacteria obtained so far; (iii) fate of recombinants inoculated in the rumen; and (iv) perspectives and problems in current and future applications.
Realizing economic and environmental gains from cultivated forages and feed reserves in Ethiopia
Authors: Dey Bhramar , Notenbaert An , Makkar Harinder , Mwendia Solomon , Sahlu Yonas , Peters Michael
Published: August 2022

The livestock sector in Ethiopia is characterized by low productivity due to inadequate supply of affordable high-quality animal feed year-round, with more acute gaps in the drought-prone regions of the country. This paper presents the economic benefits and insights into the role of cultivated forages, such as densification into pellets, in bridging gaps in feed supply. Nutrient requirement calculations for feedlot and dairy animals and meeting those requirements using cultivated forage-based diets are presented. However, forage crops need a viable forage seed supply system to assure access to quality assured seeds. This study thus explores the role of forage seed systems and presents intervention areas for Ethiopia.

Results suggest diets containing greater than 85% cultivated forages can sustain daily body weight gain up to 1 kg in growing animals. The costs of nutrients from cultivated forages are up to 15-fold lower than those from conventional feed resources. The diets based on pelleted cultivated forages decrease costs of feeding animals during a 100-day drought period by 4-fold, fattening animals by 2.3-fold, and cost of feed for milk production by 4-fold. Utilization of cultivated forages could reduce methane emissions with abatement value between $165 and $240 USD per 1000 kg of body weight gain in the fattening sector. For the dairy sector, the abatement value would range from $1350 to $2400 USD per million liters of milk production. For the drought period of 120 days, the value of methane reductions would be between $5500 and $11,400 USD per 1000 animals.
A perspective review on the effect of different forms of zinc on poultry production of poultry with special reference to the hazardous effects of misuse
Authors: Abd El-Ghany Wafaa A.
Published: August 2022

Zinc (Zn) is a unique micro-mineral because it is an essential component in many enzymes such as superoxide dismutase, carbonic anhydrase, and alkaline phosphatase, as well as being important for regulation of proteins and lipids metabolism, and sex hormones. This mineral is applied in poultry production in three forms; inorganic, organic, and nanoparticle form. The nano-form of Zn is preferable in application to other conventional forms with regard to absorption, bioavailability, and efficacy. Broilers fed on diets supplemented with Zn showed improvement of growth performance, carcass meat yield, and meat quality. In addition, Zn plays an important role in enhancing of both cellular and humeral immune responses, beside its antimicrobial and antioxidant activities. In laying hens, dietary addition of Zn improves the eggshell quality and the quantity of eggs. Moreover, Zn has a vital role in breeders in terms of improving the egg production, fertility, hatchability, embryonic development, and availability of the hatched chicks. Therefore, this review article is focused on the effects of using Zn on the performance and immunity of poultry, as well as its antimicrobial and antioxidant properties with special reference to the hazardous effects of the misusing of this mineral.
Crop waste management: perspectives on alternative uses in India
Authors: Devi Randhi Uma , Balakrishna Kolli
Published: August 2022

India, which is primarily agricultural, produces approximately 683 million tonnes (MT) of crop waste. This waste is mostly used for animal feed and fuel. In India, roughly 178 MT of surplus crop leftovers and 92 MT of crop trash are burned each year because of a lack of sustainable agricultural management practices,  resulting in severe air pollution.  This has grown into a significant environmental issue, contributing to global warming. This crop residue burning can be prevented by adopting sustainable crop management practices through the support of government initiatives and policies. Crop waste generation, demand and feasibility differ from region to region.  As a result, crop residue management plan tailored to the needs of each region should be developed. The central and state governments in India have launched a number of strategies to deal with excess crop leftovers. The majority of innovations have focused on rice husk, straw, maize waste, bagasse and banana crop waste, which account for 56% of India’s crop waste. In addition, several millet crops and cereals such as bajra, sorghum and others generate more than 352 MT of crop waste annually. These wastes are potentially available in most of the Indian states and cover 44% of crop waste, and these are not being used effectively. This review suggests advanced and practical research to develop millet crop residue management using conservation agricultural methods.
Work Integrated Learning (WIL) in the Indo-Pacific: A Village Stay Model
Authors: Tarrant Michael A. , Gleason Mikell , Sykes Helen , Boyd Steven , Lyons Kevin , Herriman Nick
Published: August 2022

This ongoing Work Integrated Learning (WIL) programme began in Fiji in the mid-2010s and was most recently extended to include Indonesia. The project, to establish a commercially viable village stay aligned with a resort, has operated in conjunction with several universities in Australia and the USA and has received external funding. Through outbound mobility programmes, and using an established business toolbox, students work with existing village group structures (i.e. youth, women, elders and church groups) to create a collaborative venture (a cultural immersion and educational stay) between the village and a local eco-resort. To date, five enterprises including four in Fiji and one in Indonesia have been created. Student evaluations attest to the transformational nature of the WIL programme in providing a unique business acumen and global skill set that can position graduates to live and work in the Indo-Pacific region. The long-term goal is to enable an operational system that can be adapted to include multiple village–resort partnerships, producing a replicable business model (and associated tourism toolkit) that can be applied throughout the developing world.

Information

In the Work Integrated Learning (WIL) programmes described here, university students collaborate with eco-resorts and local villagers to create a commercially viable and culturally experiential village stay.

© CAB International 2022
Chemokines form nanoparticles with DNA and can superinduce TLR-driven immune inflammation
Authors: Du Yong , Ah Kioon Marie Dominique , Laurent Paoline , Chaudhary Vidyanath , Pierides Michael , Yang Chao , Oliver David , Ivashkiv Lionel B. , Barrat Franck J.
Published: August 2022

Chemokines control the migratory patterns and positioning of immune cells to organize immune responses to pathogens. However, many chemokines have been associated with systemic autoimmune diseases that have chronic IFN signatures. We report that a series of chemokines, including CXCL4, CXCL10, CXCL12, and CCL5, can superinduce type I IFN (IFN-I) by TLR9-activated plasmacytoid DCs (pDCs), independently of their respective known chemokine receptors. Mechanistically, we show that chemokines such as CXCL4 mediate transcriptional and epigenetic changes in pDCs, mostly targeted to the IFN-I pathways. We describe that chemokines physically interact with DNA to form nanoparticles that promote clathrin-mediated cellular uptake and delivery of DNA in the early endosomes of pDCs. Using two separate mouse models of skin inflammation, we observed the presence of CXCL4 associated with DNA in vivo. These data reveal a noncanonical role for chemokines to serve as nucleic acid delivery vectors to modulate TLR signaling, with implications for the chronic presence of IFN-I by pDCs in autoimmune diseases.
Nucleon–nucleon correlations in the extreme oxygen isotopes
Authors: Wang S M , Nazarewicz W , Charity R J , Sobotka L G
Published: August 2022

There has been an upsurge of interest in two-nucleon decays thanks to the studies of nucleon–nucleon correlations. In our previous work (2021 Phys. Rev. Lett.
126 142501), based on a novel time-dependent three-body approach, we demonstrated that the energy and angular correlations of the emitted nucleons can shed light on the structure of nucleonic pairs formed inside the nucleus. In this work, we apply the new framework to study the decay dynamics and properties of some extreme proton-rich and neutron-rich oxygen isotopes, including two-proton (2p) decays of 11,12O and two-neutron (2n) decay of 26O. Here we show that the low-ℓ components of 11,12O wave functions, which are affected by continuum and configuration-interaction effects, strongly impact decay dynamics and asymptotic correlations. In the calculated wave functions of 11,12O, diproton and cigarlike structures merge together during the tunneling process and the resulting energy and angular correlations are very consistent with the experimental data. The asymptotic correlations of the 2n decay of 26O dramatically change as the 2n decay energy approaches the zero-energy threshold. The small reported value of Q
2n suggests that the 2n decay of this nucleus can be understood in terms of the universal phase-space limit.
Personal dosimetry for positron emitters, and occupational exposures from clinical use of gallium-68
Authors: Eakins J , Hager L , O’Connor U , Cooke J , O’Reilly G , Walsh C , Willson T
Published: August 2022

The current status and issues regarding positron dosimetry in nuclear medicine are summarized. The suitability of the United Kingdom Health Security Agency extremity and eye beta-gamma personal thermoluminescence dosemeters are then considered. Monte Carlo modelling is performed to determine their responses and derive sets of calibration factors, along with H
p(0.07) and H
p(3) conversion coefficients, for carbon-11, nitrogen-13, oxygen-15, fluorine-18 and gallium-68 sources, which are commonly used in positron emission tomography (PET) computed tomography; data for these isotopes is assumed extrapolatable to other positron sources. It is found that the dosemeters are adequate for assessing exposures to PET radionuclides, even if their routine calibrations to caesium-137 were maintained. An idealized set of measurements representing gallium-68 exposure scenarios is then described, including reproducible mock-ups of individuals manipulating vials and syringes. Finally, a short case-study is presented that explores occupational doses during routine clinical use of gallium-68. The extremity dosemeter results demonstrated significant variations dependent upon the exposure conditions, with some seen to be comparatively large; whole-body and eye dose rates per activity were found to be lower. The importance of routine dose monitoring of workers is emphasized, with the need for a longer-termed follow-up study demonstrated.
Deep learning based instance segmentation of particle streaks and tufts
Authors: Tsalicoglou C , Rösgen T
Published: August 2022

3D particle streak velocimetry (3D-PSV) and surface flow visualization using tufts both require the detection of curve segments, particle streaks or tufts, in images. We propose the use of deep learning based instance segmentation neural networks Mask region-based convolutional neural network (R-CNN) and Cascade Mask R-CNN, trained on fully synthetic data, to accurately identify, segment, and classify streaks and tufts. For 3D-PSV, we use the segmented masks and detected streak endpoints to volumetrically reconstruct flows even when the imaged streaks partly overlap or intersect. In addition, we use Mask R-CNN to segment images of tufts and classify the detected tufts according to their range of motion, thus automating the detection of regions of separated flow while at the same time providing accurate segmentation masks. Finally, we show a successful synthetic-to-real transfer by training only on synthetic data and successfully evaluating real data. The synthetic data generation is particularly suitable for the two presented applications, as the experimental images consist of simple geometric curves or a superposition of curves. Therefore, the proposed networks provide a general framework for instance detection, keypoint detection and classification that can be fine-tuned to the specific experimental application and imaging parameters using synthetic data.
Rolling bearing fault diagnosis method based on multi-sensor two-stage fusion
Authors: Liu Cang , Tong Jinyu , Zheng Jinde , Pan Haiyang , Bao Jiahan
Published: August 2022

Despite the great achievements of deep learning methods based on a single sensor in fault diagnosis, learning useful information from multi-sensor data is still a challenge. In order to make full use of multi-sensor information and improve the performance of rolling bearing fault diagnosis, a novel multi-sensor information fusion framework is proposed in this paper. First, a multi-sensor-based multi-frequency information fusion method is proposed. The multi-frequency information of each sensor is segmented first to enhance the datasets, and then a weighted fusion rule based on fuzzy entropy is constructed to fuse the information of different frequency components for multi-sensors. Second, a multi-kernel attention convolutional neural network is designed to realize multi-frequency feature capture, fusion, and fault classification of multi-sensors. Finally, two different rolling bearing datasets are used to implement fault diagnosis experiments. Experimental results show that the proposed method outperforms the comparative methods in terms of diagnostic performance and robustness.
Bioinspired micro- and nano-structured neural interfaces
Authors: Mariano Anna , Bovio Claudia Latte , Criscuolo Valeria , Santoro Francesca
Published: August 2022

The development of a functional nervous system requires neurons to interact with and promptly respond to a wealth of biochemical, mechanical and topographical cues found in the neural extracellular matrix (ECM). Among these, ECM topographical cues have been found to strongly influence neuronal function and behavior. Here, we discuss how the blueprint of the architectural organization of the brain ECM has been tremendously useful as a source of inspiration to design biomimetic substrates to enhance neural interfaces and dictate neuronal behavior at the cell-material interface. In particular, we focus on different strategies to recapitulate cell-ECM and cell–cell interactions. In order to mimic cell-ECM interactions, we introduce roughness as a first approach to provide informative topographical biomimetic cues to neurons. We then examine 3D scaffolds and hydrogels, as softer 3D platforms for neural interfaces. Moreover, we will discuss how anisotropic features such as grooves and fibers, recapitulating both ECM fibrils and axonal tracts, may provide recognizable paths and tracks that neuron can follow as they develop and establish functional connections. Finally, we show how isotropic topographical cues, recapitulating shapes, and geometries of filopodia- and mushroom-like dendritic spines, have been instrumental to better reproduce neuron–neuron interactions for applications in bioelectronics and neural repair strategies. The high complexity of the brain architecture makes the quest for the fabrication of create more biologically relevant biomimetic architectures in continuous and fast development. Here, we discuss how recent advancements in two-photon polymerization and remotely reconfigurable dynamic interfaces are paving the way towards to a new class of smart biointerfaces for in vitro applications spanning from neural tissue engineering as well as neural repair strategies.
An inception network for positron emission tomography based dose estimation in carbon ion therapy
Authors: Rutherford Harley , Saha Turai Rohan , Chacon Andrew , Franklin Daniel R , Mohammadi Akram , Tashima Hideaki , Yamaya Taiga , Parodi Katia , Rosenfeld Anatoly B , Guatelli Susanna , Safavi-Naeini Mitra
Published: August 2022

Objective. We aim to evaluate a method for estimating 1D physical dose deposition profiles in carbon ion therapy via analysis of dynamic PET images using a deep residual learning convolutional neural network (CNN). The method is validated using Monte Carlo simulations of 12C ion spread-out Bragg peak (SOBP) profiles, and demonstrated with an experimental PET image. Approach. A set of dose deposition and positron annihilation profiles for monoenergetic 12C ion pencil beams in PMMA are first generated using Monte Carlo simulations. From these, a set of random polyenergetic dose and positron annihilation profiles are synthesised and used to train the CNN. Performance is evaluated by generating a second set of simulated 12C ion SOBP profiles (one 116 mm SOBP profile and ten 60 mm SOBP profiles), and using the trained neural network to estimate the dose profile deposited by each beam and the position of the distal edge of the SOBP. Next, the same methods are used to evaluate the network using an experimental PET image, obtained after irradiating a PMMA phantom with a 12C ion beam at QST’s Heavy Ion Medical Accelerator in Chiba facility in Chiba, Japan. The performance of the CNN is compared to that of a recently published iterative technique using the same simulated and experimental 12C SOBP profiles. Main results. The CNN estimated the simulated dose profiles with a mean relative error (MRE) of 0.7% ± 1.0% and the distal edge position with an accuracy of 0.1 mm ± 0.2 mm, and estimate the dose delivered by the experimental 12C ion beam with a MRE of 3.7%, and the distal edge with an accuracy of 1.7 mm. Significance. The CNN was able to produce estimates of the dose distribution with comparable or improved accuracy and computational efficiency compared to the iterative method and other similar PET-based direct dose quantification techniques.
Personalized mid-course FDG-PET based adaptive treatment planning for non-small cell lung cancer using machine learning and optimization
Authors: Ajdari Ali , Liao Zhongxing , Mohan Radhe , Wei Xiong , Bortfeld Thomas
Published: August 2022

Objective. Traditional radiotherapy (RT) treatment planning of non-small cell lung cancer (NSCLC) relies on population-wide estimates of organ tolerance to minimize excess toxicity. The goal of this study is to develop a personalized treatment planning based on patient-specific lung radiosensitivity, by combining machine learning and optimization. Approach. Sixty-nine non-small cell lung cancer patients with baseline and mid-treatment [18]F-fluorodeoxyglucose (FDG)-PET images were retrospectively analyzed. A probabilistic Bayesian networks (BN) model was developed to predict the risk of radiation pneumonitis (RP) at three months post-RT using pre- and mid-treatment FDG information. A patient-specific dose modifying factor (DMF), as a surrogate for lung radiosensitivity, was estimated to personalize the normal tissue toxicity probability (NTCP) model. This personalized NTCP was then integrated into a NTCP-based optimization model for RT adaptation, ensuring tumor coverage and respecting patient-specific lung radiosensitivity. The methodology was employed to adapt the treatment planning of fifteen NSCLC patients. Main results. The magnitude of the BN predicted risks corresponded with the RP severity. Average predicted risk for grade 1–4 RP were 0.18, 0.42, 0.63, and 0.76, respectively (p < 0.001). The proposed model yielded an average area under the receiver-operating characteristic curve (AUROC) of 0.84, outperforming the AUROCs of LKB-NTCP (0.77), and pre-treatment BN (0.79). Average DMF for the radio-tolerant (RP grade = 1) and radiosensitive (RP grade ≥ 2) groups were 0.8 and 1.63, p < 0.01. RT personalization resulted in five dose escalation strategies (average mean tumor dose increase = 6.47 Gy, range = [2.67–17.5]), and ten dose de-escalation (average mean lung dose reduction = 2.98 Gy [0.8–5.4]), corresponding to average NTCP reduction of 15% [4–27]. Significance. Personalized FDG-PET-based mid-treatment adaptation of NSCLC RT could significantly lower the RP risk without compromising tumor control. The proposed methodology could help the design of personalized clinical trials for NSCLC patients.
Interstitial fluid streaming in deep tissue induced by ultrasound momentum transfer for accelerating nanoagent transport and controlling its distribution
Authors: Yuan Baohong
Published: August 2022

Objective. This study aims to theoretically investigate the dynamics of ultrasound-induced interstitial fluid streaming and tissue recovery after ultrasound exposure for potentially accelerating nanoagent transport and controlling its distribution in tissue. Approach. Starting from fundamental equations, the dynamics of ultrasound-induced interstitial fluid streaming and tissue relaxation after an ultrasound exposure were modeled, derived and simulated. Also, both ultrasound-induced mechanical and thermal effects were considered in the models. Main results. The proposed new mechanism was named squeezing interstitial fluid via transfer of ultrasound momentum (SIF-TUM). It means that an ultrasound beam can squeeze the tissue in a small focal volume from all the directions, and generate a macroscopic streaming of interstitial fluid and a compression of tissue solid matrix. After the ultrasound is turned off, the solid matrix will recover and can generate a backflow. Rather than the ultrasound pressure itself or intensity, the streaming velocity is determined by the dot product of the ultrasound pressure gradient and its conjugate. Tissue and nanoagent properties also affect the streaming and recovery velocities. Significance. The mobility of therapeutic or diagnostic agents, such as drugs, drug carriers, or imaging contrast agents, in the interstitial space of many diseased tissues, such as tumors, is usually extremely low because of the inefficiency of the natural transport mechanisms. Therefore, the interstitial space is one of the major barriers hindering agent deliveries. The ability to externally accelerate agent transport and control its distribution is highly desirable. Potentially, SIF-TUM can be a powerful technology to accelerate agent transport in deep tissue and control the distribution if appropriate parameters are selected.
Constraints on τNLfrom Planck temperature and polarization
Authors: Marzouk Kareem , Lewis Antony , Carron Julien
Published: August 2022

We update constraints on the amplitude of the primordial trispectrum, using the finalPlanckmission temperature and polarization data. In the squeezed limit, a cosmological local trispectrum would be observed as a spatial modulation of small-scale power on the CMB sky. We reconstruct this signal as a source of statistical anisotropy via quadratic estimator techniques. We systematically demonstrate how the estimated power spectrum of a reconstructed modulation field can be translated into a constraint onτNLvia likelihood methods, demonstrating the procedures effectiveness by inferring knownτNLsignal(s) from simulations. Our baseline results constrainτNL< 1700 at the 95% confidence level, providing the most stringent constraints to date.
Dark photon stars: formation and role as dark matter substructure
Authors: Gorghetto Marco , Hardy Edward , March-Russell John , Song Ningqiang , West Stephen M.
Published: August 2022

Any new vector boson with non-zero mass (a 'dark photon' or 'Proca boson') that is present during inflation is automatically produced at this time from vacuum fluctuations and can comprise all or a substantial fraction of the observed dark matter density, as shown by Graham, Mardon, and Rajendran. We demonstrate, utilising both analytic and numerical studies, that such a scenario implies an extremely rich dark matter substructure arising purely from the interplay of gravitational interactions and quantum effects. Due to a remarkable parametric coincidence between the size of the primordial density perturbations and the scale at which quantum pressure is relevant, a substantial fraction of the dark matter inevitably collapses into gravitationally bound solitons, which are fully quantum coherent objects. The central densities of these 'dark photon star', or 'Proca star', solitons are typically a factor 106 larger than the local background dark matter density, and they have characteristic masses of 10-16
M
⊙ (10-5 eV/m)3/2, where m is the mass of the vector.
During and post soliton production a comparable fraction of the energy density is initially stored in, and subsequently radiated from, long-lived quasi-normal modes. Furthermore,
the solitons are surrounded by characteristic 'fuzzy' dark matter halos in which quantum wave-like properties are also enhanced relative to the usual virialized dark matter expectations.
Lower density compact halos, with masses a factor of ∼ 105 greater than the solitons, form at much larger scales. We argue that, at minimum, the solitons are likely to survive to the present day without being tidally disrupted. This rich substructure, which we anticipate also arises from other dark photon dark matter production mechanisms, opens up a wide range of new direct and indirect detection possibilities, as we discuss in a companion paper.
Bound noise-like pulse generation from Yb-doped passively mode-locked fiber lasers
Authors: Gao Zi-Qi , Wu Yun-Feng , Liu Hai-Yan , Zhang Ze-Xin , Tian Jin-Rong , Song Yan-Rong
Published: August 2022

We demonstrated two different types of bound noise-like pulses (NLPs) in ytterbium-doped mode-locked fiber lasers using the nonlinear polarization rotation technique. In the anomalous dispersion area, there were multiple spikes in the intensity autocorrelation (IAC) trace. In the normal dispersion area, the spike presented only in the center the of IAC trace. The results of the experiment show that the bound state NLPs may have partial coherence.
Microwave enhanced precision in 2D and 3D atom localization at nonzero temperatures
Authors: Iqbal Dar Zubair , Kaur Amanjot , Singh Neeraj , Kaur Paramjit
Published: August 2022

Two- and three-dimensional (2D and 3D) atom localization is analyzed by monitoring the probe absorption spectrum in a microwave driven X-type scheme. It is found that for both stationary and moving atom cases, the precision and certainty in atomic position can be significantly improved by proper adjustment of the system parameters. Our results also reveal that the high microwave field strength curbs the Doppler broadening effect to a large extent and enhances detection probability to 100% in 2D and 3D subspace at nonzero temperatures. Our proposed scheme may be helpful for experimental realization of high precision position measurement and atom nanolithography at room temperature.
Influence of the neck parameter on the fission dynamics within the two-center shell model parametrization*
Authors: Liu Li-Le , Wu Xi-Zhen , Chen Yong-Jing , Shen Cai-Wan , Li Zhu-Xia , Ge Zhi-Gang , Shu Neng-Chuan
Published: August 2022

The influence of the neck parameter on the fission dynamics at low excitation energy is studied based on the three-dimensional Langevin approach, in which the nuclear shape is described with the two-center shell model (TCSM) parametrization, and the elongation, mass asymmetry, and fragment deformation are set to be the generalized coordinates of the Langevin equation. We first study the influence of the neck parameter on the scission configuration. We find that there is almost no obvious correlation between the neck parameter

and mass asymmetry η at the scission point, indicating that

has no evident impact on the fragment mass distribution. The elongation

and its correlation with the mass asymmetry η at the scission point are clearly influenced by the neck parameter

, which has a strong effect on the total kinetic energy (TKE) distribution of the fragments. The pre-neutron emission fragment mass distributions for 14 MeV n+

U and

Pu are calculated, and then, based on these results, the post-neutron emission fragment mass distributions are obtained by using the experimental data of prompt neutron emission. The calculated post-neutron emission fragment mass distributions can reproduce the experimental data well. The TKE distributions for 14 MeV n+

U fission are calculated for

=0.25, 0.35, and 0.45, and the results show that the TKE distribution cannot be described very well for the three cases. However, the trend of the calculated TKE distribution with

is just as expected from the scission configuration calculations. The results with

=0.35 present a better agreement with the experiment data compared with the other two cases.
Transcranial ultrasound neuromodulation induces neuronal correlation change in the rat somatosensory cortex
Authors: Ramachandran Sandhya , Niu Xiaodan , Yu Kai , He Bin
Published: August 2022

Objective. Transcranial focused ultrasound (tFUS) is a neuromodulation technique which has been the focus of increasing interest for noninvasive brain stimulation with high spatial specificity. Its ability to excite and inhibit neural circuits as well as to modulate perception and behavior has been demonstrated, however, we currently lack understanding of how tFUS modulates the ways neurons interact with each other. This understanding would help elucidate tFUS’s mechanism of systemic neuromodulation and allow future development of therapies for treating neurological disorders. Approach. In this study, we investigate how tFUS modulates neural interaction and response to peripheral electrical limb stimulation through intracranial multi-electrode recordings in the rat somatosensory cortex. We deliver ultrasound in a pulsed pattern to induce frequency dependent plasticity in a manner similar to what is found following electrical stimulation. Main Results. We show that neural firing in response to peripheral electrical stimulation is increased after ultrasound stimulation at all frequencies, showing tFUS induced changes in excitability of individual neurons in vivo. We demonstrate tFUS sonication repetition frequency dependent pairwise correlation changes between neurons, with both increases and decreases observed at different frequencies. Significance. These results extend previous research showing tFUS to be capable of inducing synaptic depression and demonstrate its ability to modulate network dynamics as a whole.
Coupling rare event algorithms with data-based learned committor functions using the analogue Markov chain
Authors: Lucente Dario , Rolland Joran , Herbert Corentin , Bouchet Freddy
Published: August 2022

Rare events play a crucial role in many physics, chemistry, and biology phenomena, when they change the structure of the system, for instance in the case of multistability, or when they have a huge impact. Rare event algorithms have been devised to simulate them efficiently, avoiding the computation of long periods of typical fluctuations. We consider here the family of splitting or cloning algorithms, which are versatile and specifically suited for far-from-equilibrium dynamics. To be efficient, these algorithms need to use a smart score function during the selection stage. Committor functions are the optimal score functions. In this work we propose a new approach, based on the analogue Markov chain, for a data-based learning of approximate committor functions. We demonstrate that such learned committor functions are extremely efficient score functions when used with the adaptive multilevel splitting algorithm. We illustrate our approach for a gradient dynamics in a three-well potential, and for the Charney–DeVore model, which is a paradigmatic toy model of multistability for atmospheric dynamics. For these two dynamics, we show that having observed a few transitions is enough to have a very efficient data-based score function for the rare event algorithm. This new approach is promising for use for complex dynamics: the rare events can be simulated with a minimal prior knowledge and the results are much more precise than those obtained with a user-designed score function.
Unveiling the connection between the global roughness exponent and interface fractal dimension in EW and KPZ lattice models
Authors: Mozo Luis Edwin E , de Assis Thiago A , Oliveira Fernando A
Published: August 2022

A connection between the global roughness exponent and the fractal dimension of a rough interface, whose dynamics are expected to be described by stochastic continuum models, still needs more support from simulations in lattice models, which are key to provide completeness for the characterization of a given universality class. In this work, we investigate the asymptotic fractal dimension of interfaces that evolve according to some specific lattice models in d + 1 dimensions (d = 1, 2), which are expected to belong to the Edwards–Wilkinson or Kardar–Parisi–Zhang universality classes. Our results, based on the Higuchi method and on the extrapolation of the effective fractal dimension, allow one to achieve dependence between the asymptotic fractal dimension and global roughness exponent, in which the latter is expected to be hardly accessible for experimentalists. Conversely, we also use a two-points correlation function, which gives the time evolution of the local roughness exponent. As a byproduct, our results suggest that, for d = 1, the fractal dimension converges faster than the global roughness exponents to the asymptotic ones. Therefore, the analysis of the fractal dimension, for d = 1, is suggested to be more accessible than the global roughness exponents to determine the universality class. Corrections for the fractal dimensions in d = 2 were found to be stronger than for d = 1.
Pedestrian counterflow in a floor field cellular automaton model coupled with an evolutionary game
Authors: Chen Ze-Hao , Wu Zhi-Xi , Guan Jian-Yue
Published: August 2022

We study the bidirectional pedestrian flow in a straight corridor using a floor field cellular automaton model, where a game-theoretical framework is exclusively introduced to deal with conflicts that multiple pedestrians are trying to move to the same target position. The pedestrians can behave as either cooperators or defectors, depending on whether they show gentle or aggressive in face of conflicts, respectively. When competing with cooperators, a defector always obtains a relatively greater payoff, characterizing the advantage of occupying the preferred vacant cell, while a reduced payoff factor δ is introduced for mutual defection due to the possible injuries by aggressiveness. We study how the pedestrian counterflow dynamics depends on δ, the corridor width W and the anticipation floor field parameter k
A. It is found that the average separation time of the pedestrians displays a resonance-like behavior as a function of δ, irrespective of the width of the corridor as long as jam does not happen. The way of dealing with conflicts has no qualitative effect on the lane formation, where the jam probability mainly depends on the parameters W and k
A as well as the pedestrian density. A large value of k
A means a strong tendency to avoid potential future collisions and suppress the overtaking motivation, but, at a cost, increases the average separation time of the two groups of pedestrians when the width of the corridor is not so narrow. Our results provide a meaningful perspective on the understanding of the process of lane formation and jam dissolution in the bidirectional pedestrian flow, and may shed light on designing policies to improve the efficiency of passing through.
Half-cell and noise voltages at a metal-electrode and dilute solution interface
Authors: Barbero G , Evangelista L R , Merletti R
Published: August 2022

The detection of bioelectric signals is usually based on an electrode-skin contact that is often mediated by a layer of conductive gel. This interface produces a DC voltage (half-cell potential) and a random noise voltage whose relationship is not well known. The first may cause amplifier saturation and the second posits a limit to the detection of small signals. This work investigates the mechanisms of generation of these two voltages in the simpler case of a metal-electrolyte junction and finds a theoretical expression for both, under a few simplifying hypotheses. An expression is found that relates the two voltages to the ionic concentration and to the parameters defining the dynamics of the adsorption–desorption phenomena taking place at the interface. A relationship is found between the two voltages that is in qualitative agreement with experimental findings reported in the literature. This theoretical background provides a basis for further investigation of the metal-gel and of the gel-skin interfaces not addressed in this work.
Transformer Health Index by Prediction Artificial Neural Networks Diagnostic Techniques
Authors: Abdullah A.M. , Ali R. , Yaacob S.B. , Ananda-Rao K. , Uloom N.A.
Published: August 2022

This paper presents the artificial neural network diagnostic techniques for predicting the health index in transformer. Collection data is measured and tested from insulation resistance in between phase-ground, phase to phase and also the winding resistance transformer. The data was collected from 10 units of transformers from Company Transformer Manufacturing and Servicing (CTMS) in Malaysia. The data was used to calculate condition transformer index or health index transformer. Condition transformer index can identify whether transformer in good condition or not good condition. The purpose of knowing transformer health index or condition transformer index is to prevent failures functional transformer and ensure transformer in stable condition. Prediction health index or condition transformer index can be determined by artificial neural network. Therefore, it can monitor and observe very closely conditions of the transformer. Data health index transformer is very important because it know the condition transformer and can solve the major problem in transformer or do the maintenance in early stage before the transformer is totally malfunction.
The prospect of green energy and technology in Bangladesh
Authors: Askary Md A H A , Hai T B , Showmik S S K , Kader Md A. , Rahman Md Tauhidur
Published: August 2022

Green Energy comes from environmental natural resources which are renewable. Green technology alludes that is earth unneighbourly, created, and utilized in a way with the goal that it does not irritate our condition and conserves natural resources. Its uses are getting a solution for widespread global warming fears and the increasing scarcity of many natural resources. Green energy and technology are interrelated to achieve a stable environment and sustainable development. This paper reviews the studies which are related to green energy and technology and shows the existing scenario, potentialities of using it in Bangladesh. Data identifying strategies are gathered from research papers, government documents, relevant green energy and technology policies, interviews with experts. There are some problems with the growing green energy and technology in the country. Therefore, based on problems, some strategic ideas are recommended in this paper.
Air Plasma Sterilizer Using a Parallel Dielectric Barrier Discharge
Authors: Santjojo Dionysius J D H , Masruroh  , Sakti Setyawan P
Published: August 2022

Air sterilizer is one of the essential components in combating the Covid-19. A wind tunnel model of the air sterilizer using a dielectric barrier discharge plasma is proposed to destroy the virus by direct contact with the plasma. Dangerous ozone production in the plasma reactor should be controlled to a safe level. Two parameters affecting the ozone concentration, i.e., electrical power and airflow, were investigated. The DBD reactor was a cell constructed from an array of alternate electrodes. The plasma was generated by an AC high voltage generator with a range of 2kV -3kV. The power and the high voltage were varied by controlling the DC input voltage of the generator. The airflow was varied by controlling the speed of an exhaust fan from 0.5 m/s to 3.0 m/s. The state was characterized using optical emission spectroscopy in the range of 200 nm – 1000 nm. The results showed that both parameters played a significant role in ozone concentration. The trend of the ozone is strongly correlated with the OH species, which reacts with oxygen. The highest ozone concentration of 4.51 ppm was observed at the DC voltage around 19 volts or the power of 34.2 watts. However, a decrease of the ozone concentration at a voltage higher than 19 volts related to 2.9 kV was observed. In general, the data showed that faster airflow decreases ozone concentration. A drastic decrease of the nitrogen species sustaining the plasma occurred at the airflow higher than 2 m/s.