bluuebunny/crossref_metadata_2025 huggingface dataset:
Silicon nanoparticles encapsulated in Si3N4/carbon sheaths as an anode material for lithium-ion batteries
Authors: K Brijesh , Ikhe Amol Bhairuba , Pyo Myoungho
Published: March 2023

Novel composite materials comprising of silicon nanoparticles (SiNPs) encapsulated with thin layers of silicon nitride and reduced graphene oxide shells (Si@Si3N4@rGO) are prepared using a simple and scalable method. The composite exhibits significantly improved cycling stability and rate capability compared to bare SiNPs. The presence of inactive α and β phases of Si3N4 increases the mechanical endurance of SiNPs. Amorphous SiN
x
, which is possibly present with Si3N4, also contributes to high capacity and Li-ion migration. The rGO sheath enhances the electronic conduction and improves the rate capability. 15-Si@Si3N4@rGO, which is prepared by sintering SiNPs for 15 min at 1300 °C, spontaneous-coating GO on Si@Si3N4, and reducing GO to rGO, delivers the highest specific capacity of 1396 mAh g−1 after 100 cycles at a current density of 0.5 A g−1. The improved electrochemical performance of 15-Si@Si3N4@rGO is attributed to the unique combination of positive effects by Si3N4 and rGO shells, in which Si3N4 mitigates the issue of large volume changes of Si during charge/discharge, and rGO provides efficient electron conduction pathways. Si@Si3N4@rGO composites are likely to have great potential for a high-performance anode in lithium-ion batteries.
A stochastic control approach to intrafraction motion management in intensity-modulated radiotherapy
Authors: Salari Ehsan , Mazur Thomas , Sharp Gregory
Published: March 2023

Objective. The goal of this research is to demonstrate proof-of-principle for managing intrafraction motion via feedback control of delivered dose to achieve dosimetry comparable to respiratory gating without compromising delivery efficiency. Approach. We develop a stochastic control approach for step-and-shoot intensity-modulated radiotherapy (IMRT) in which the cumulative delivered dose and future trajectory of intrafraction motion are dynamically estimated by combining pre-treatment four-dimensional computed tomography imaging and intrafraction respiratory-motion surrogates. The IMRT plan is then re-optimized in real time to ensure delivery of the planned dose in the presence of free-breathing motion. We compare the performance of the proposed approach against traditional motion-management techniques, namely, respiratory gating and internal target volume (ITV) planning, using the four-dimensional extended cardiac-torso computational phantom. Main results. We simulate the delivery of treatment plans for a lung tumor in the presence of variable breathing amplitude, tumor size, and location. Results show that the proposed method reduces irradiated tissue volume compared to ITV treatment. Additionally, it significantly reduces treatment time compared to traditional respiratory-gated treatment, without compromising the dosimetric quality. Significance. Respiratory gating is a common technique to manage intrafraction motion. While gating supports reduced treatment volumes, it also prolongs the treatment delivery time. The proposed stochastic control approach can help improve the delivery efficiency of respiratory gating without compromising the dose quality.
Design and development of type-1 FBG based high temperature sensor
Authors: Khan R Y M , Ullah R , Faisal M
Published: March 2023

Thermal metrology is critical in many high-energy industrial processes to optimize the process efficiency, energy consumption and quality of end product. Here, we present the design and development of a double thimble type standard type-1 fiber Bragg grating (FBG) high temperature sensing probes. Two different probes named probe-1 and probe-2 are developed by encapsulating type-1 FBGs in two stainless steel thimbles with ceramic filling. The probes are experimentally tested in a high temperature box furnace and their responses are interrogated by an optical spectrum analyzer. FBGs encapsulated in both probe-1 and probe-2 exhibited a linear red-shift in their Bragg wavelength with increase in temperature from 30 °C to 700 °C with sensitivities of 13.86 ± 0.1 pm/°C and 14.10 ± 0.2 pm/°C which are 4.8% and 3.16% lower than temperature sensitivity of bare FBG, respectively. A deformation in the Bragg spectrum of probe-1 is observed at temperatures above 500 °C however, probe-2 is found to be thermally stable up to 700 °C. An estimated life-time of about 6 years is offered by the optimized probe-2 with a negligible hysteresis and repeatability of 1°C–5°C.
Classification of Parkinson’s disease with dementia using phase locking factor of event-related oscillations to visual and auditory stimuli
Authors: Tülay Emine Elif , Yıldırım Ebru , Aktürk Tuba , Güntekin Bahar
Published: March 2023

Objective. In the last decades, machine learning approaches have been widely used to distinguish Parkinson’s disease (PD) and many other neuropsychiatric diseases. They also speed up the clinicians and facilitate decision-making for several conditions with similar clinical symptoms. The current study attempts to detect PD with dementia (PDD) by event-related oscillations (EROs) during cognitive processing in two modalities, i.e. auditory and visual. Approach. The study was conducted to discriminate PDD from healthy controls (HC) using event-related phase-locking factors in slow frequency ranges (delta and theta) during visual and auditory cognitive tasks. Seventeen PDD and nineteen HC were included in the study, and linear discriminant analysis was used as a classifier. During classification analysis, multiple settings were implemented by using different sets of channels (overall, fronto-central and temporo-parieto-occipital (TPO) region), frequency bands (delta-theta combined, delta, theta, and low theta), and time of interests (0.1–0.7 s, 0.1–0.5 s and 0.1–0.3 s for delta, delta-theta combined; 0.1–0.4 s for theta and low theta) for spatial-spectral-temporal searchlight procedure. Main results. The classification performance results of the current study revealed that if visual stimuli are applied to PDD, the delta and theta phase-locking factor over fronto-central region have a remarkable contribution to detecting the disease, whereas if auditory stimuli are applied, the phase-locking factor in low theta over TPO and in a wider range of frequency (1–7 Hz) over the fronto-central region classify HC and PDD with better performances. Significance. These findings show that the delta and theta phase-locking factor of EROs during visual and auditory stimuli has valuable contributions to detecting PDD.
An efficient digital pulse processing approach for identification of BGO and LSO scintillator crystals
Authors: El Tokhy Mohamed S.
Published: March 2023

Identification and discrimination between BGO and LSO
scintillators is a fundamental target for handling parallax error
within positron emission tomography (PET) applications by depth of
interaction. An approach is built for discrimination and
identification of BGO and LSO scintillator crystals. This approach
is tested using a simulated BGO and LSO pulses. A Matlab Simulink
model is implemented for simulation and creation of BGO and LSO
scintillation pulses. The simulated pulses depend on 22Na
radiation source. The suggested approach has two different
algorithms. The first algorithm uses both 1D-Walsh ordered fast
Walsh-Hadamard transform (1WFWHT) and fast Chebyshev transform
(FCHT) for extracting the features of crystal pulses. The optimum
features are selected from 1WFWHT and FCHT using one of three
optimization techniques that are binary dragonfly optimization
(BDA), binary atom search optimization (BASO) and binary Harris Hawk
optimization (BHHO). These optimized features are trained and tested
using one of three based classifiers. These classifiers are Naive
Bayes classifier (NBC), hierarchical prototype-based (HP) classifier
and adaptive neuro-fuzzy inference system (ANFIS)
classification. The ANFIS classifier achieves the best accuracy with
all optimum (BASO, BDF and BHH) FCHT features. However, the NB
classifier introduces the highest accuracy with all optimum (BASO,
BDF and BHH) FWHT 1D features. The second algorithm uses the
conventional neural network (CNN) for extracting the pulse
features. Then, the deep neural network (DNN) is applied for
training and testing of the captured pulses. The suggested
algorithms are verified and compared in respect of statistical
measures. The compared results confirm that the best accuracy and
identification rate is accomplished using DNN algorithm. Besides,
the DNN has better results compared to conventional classification
techniques with optimum feature selection techniques in respect of
time consumption. The proposed approach aids in the realisation of
overcoming parallax inaccuracy in PET.
Experience in using methods for monitoring the energy efficiency of hydraulic systems
Authors: Glovatskii O , Ergashev R , Rashidov J , Mirzaev M , Sultonov A , Nasyrova N
Published: March 2023

The purpose of this research is to improve the system of water resources management and operation of water facilities, reduce the energy consumption of irrigation pumping stations, which is one of the urgent modern problems in the Republics of Central Asia. The authors decide on the choice of such a set of subsystems and elements from the universal set, in which the value of the design parameters is provided with minimal costs. The recommendations developed by the authors use methods for monitoring the energy efficiency of hydraulic systems and are aimed at reducing electricity consumption, primarily through effective methods for regulating the operation of pumping stations. The main feature of assessing the technical condition of the units of pumping stations is the use of diagnostics of the dynamic level of elements of hydraulic units during operation. Monitoring of operating parameters of pumping stations was carried out on two pilot canals according to special tables of basic parameters. As an optimality criterion, options are accepted that differ in terms of reconstruction, duration of development of the capacity of electrical networks, interface structures of pumping stations, taking into account the time factor. By carrying out these activities, the water supply of the irrigation array will increase and crop yields will increase. After analyzing the data obtained, it will be possible to make a decision on the further use or modernization of the units of pumping units and structures. At the same time, the conditions for energy efficiency and reliability of the operation of the PS will improve.
Study on automatic water level detection process using ultrasonic sensor
Authors: Djalilov A , Sobirov E , Nazarov O , Urolov S , Gayipov I
Published: March 2023

Currently, we live in a world where all fields are developing very rapidly. In particular, the field of water management is developing day by day, and the water supply system is being intelligent automated. Nevertheless, mechanical means and human labor are used to monitor the water level in many water management facilities of our region. This situation causes many problems in the automatic management of the system. In this article, we will consider the process of automating the measurement and control of water level, that is, an automated system that helps to know when the water in the tank is full or empty. In the automation of this system, an ultrasonic sensor that meets the requirements of the time was used. The working principle of ultrasonic sensors is based on the movement of ultrasonic waves over time. The analysis of the results of this experiment showed that the water level measurement and control system did not make more than 1.5% error in different values of the water level. This situation showed that the developed system can be effectively used in all water level control facilities.
Optimization of the technological process for the production of dried soursop (Annona muricata Linn) for vitamin C content by response surface methodology
Authors: Nguyen Ngoc Quy , Nguyen Van Thuy , Nguyen Minh Tien , Pham Tri Nhut , Dao Tan Phat , Tran Thi Yen Nhi
Published: March 2023

Soursop is a popular edible fruit in the world, because of its delicious taste as well as its pharmacological values and therapeutic uses. However, this is also a perishable fruit. To increase the value of this fruit, we conducted a study to optimize the process of creating dried soursop products by the response surface method. The optimal value was osmosis at 45 cmHg pressure and heat pump drying at 25°C, obtaining the dried soursop product with the highest vitamin C content of 0.382 ± 0.011 (mg/g DW).
Assessment of The Antropogenic Impact on Mangrove Ecosystem and Endemic Fauna in Muaragembong, Bekasi, West Java
Authors: Suryono D D , Salim H L , Solihuddin T , Husrin S , Hidayat  , Sudirman N , Heriati A
Published: March 2023

The Muaragembong coast is degraded by anthropogenic factors such as pollution and ponds. The area that used to be a mangrove ecosystem is now experiencing abrasion. Trash trapped in the mangrove ecosystem also affects the ecosystem and its biodiversity. This research is descriptive in nature with the aim of knowing changes in mangrove areas through analysis of Landsat satellite imagery and identifying the causes of changes and impacts on endemic species. This research was conducted with the stages of literature study, analysis of satellite imagery in 2000, 2009, 2010, 2014, 2019 and 2020. Based on the analysis of satellite imagery, it was found that changes in mangrove area were confirmed with secondary data so that the factors that caused these changes were known. The results of the analysis show that the degradation of the mangrove ecosystem in 2017 was approximately 2800 ha and affected the existence of the Lutung Jawa (Trachypithecus auratus) as an endemic fauna in Muaragembong which inhabits the mangrove ecosystem on the north coast of Bekasi. It is currently estimated that there are no more than 50 present in the area, therefore the Lutung Jawa is considered a vulnerable species as cited in CITES Annex II 2008.
The Institutional Social Role for Maritim Village’s Food Stability
Authors: Khodijah I , Lestari F , Setiawan T , Habibah S N , Zulfikar A , Lumbantoruan L H
Published: March 2023

This study aims to explore social networks and interactions between networks in strengthening food stability in maritime villages in coastal areas. The geographical condition of the region has become one of the triggers for food instability and food security problems in coastal areas. This study uses the method of Social Network Analysis (SNA). Data processing uses R to visualize the role of stakeholder centrality. The analysis used is the analysis of baseline network, degree, and betweenness centrality. The value of modularity is an indicator of increasing or decreasing community networks. The number of nodes and links identifies the actors in the network and the interactions between actors. The results showed that social networks have an essential role in food stability. The private sector is a key actor in food stability in maritime villages. Is indicated by the modularity value of 0.43 (>0), which connects to 30 social network nodes and 62 links to food stability in maritime villages in the coastal area of Bintan Regency.
Photonic spin Hall effect with high coupling efficiency in the combined structure of periodic dielectric waveguides and photonic crystal waveguide
Authors: Zhang Yi-Chen , Zhao Li-Ming , Zhou Yun-Song
Published: March 2023

In this paper, we discuss the photonic spin Hall effect (PSHE) in the combined structure of periodic dielectric waveguides (PDWs) and photonic crystal waveguide (PCW). By controlling the polarization of the dipole source, we have successfully achieved the arbitrary manipulation of PSHE for the PDW guided mode in our structure. The advantage of PDW is that it can be designed to different shapes without the geometric constraints, and still maintains a relatively high transmission rate. Therefore, by further changing the structure, including the adjustment of the intersection angle between PDW and PCW, and the alteration of the straight PDW to the bending or bifurcated shapes, we find that the output of highly unidirectional PSHE is mainly determined by the intersection angle between PDW and PCW and almost independent of the detailed shape of PDW.
Biorealistic hand prosthesis with compliance control and noninvasive somatotopic sensory feedback
Authors: Lan Ning , Zhang Jie , Zhang Zhuozhi , Chou Chih-Hong , Rymer William Zev , Niu Chuanxin M , Fang Peng
Published: March 2023

Significant advances have been made to improve control and to provide sensory functions for bionic hands. However, great challenges remain, limiting wide acceptance of bionic hands due to inadequate bidirectional neural compatibility with human users. Recent research has brought to light the necessity for matching neuromechanical behaviors between the prosthesis and the sensorimotor system of amputees. A novel approach to achieving greater neural compatibility leverages the technology of biorealistic modeling with real-time computation. These studies have demonstrated a promising outlook that this unique approach may transform the performance of hand prostheses. Simultaneously, a noninvasive technique of somatotopic sensory feedback has been developed based on evoked tactile sensation (ETS) for conveying natural, intuitive, and digit-specific tactile information to users. This paper reports the recent work on these two important aspects of sensorimotor functions in prosthetic research. A background review is presented first on the state of the art of bionic hand and the various techniques to deliver tactile sensory information to users. Progress in developing the novel biorealistic hand prosthesis and the technique of noninvasive ETS feedback is then highlighted. Finally, challenges to future development of the biorealistic hand prosthesis and implementing the ETS feedback are discussed with respect to shaping a next-generation hand prosthesis.
Study on novel steel slag foam concrete pore structure and bp neural network prediction model
Authors: Zhi Zeng , Xiaohua LI , Fan Huang , Wangxing Zhan , Huan SU , Wenjing LI , Xianglong LIU
Published: March 2023

In this paper, a new type of steel slag foamed concrete was prepared. Its pore structure was analyzed by MATLAB image processing technique, and the influence of steel slag on the compressive strength of foamed concrete was investigated. In addition, a BP neural network prediction model for the pore structure of foam concrete was established. The research results show that when the content of steel slag is 30%, the pore structure of steel slag foamed concrete is appropriate. The compressive strength of steel slag foamed concrete increases with the decrease of the density and the proportion of irregular pores. With the density remaining unchanged, the compressive strength of foamed concrete increases with the increase of the ratio of round and small pores. The prediction errors of the BP neural network model in the average pore diameter and average pore roundness factor were less than 8.5% and 5%, respectively.This research can provide a theoretical basis for the production of steel slag foam concrete.
Machine learning-based signal quality assessment for cardiac volume monitoring in electrical impedance tomography
Authors: Min Hyun Chang , Jun Jang Tae , Nam Jeongchan , Kwon Hyeuknam , Jeon Kiwan , Lee Kyounghun
Published: March 2023

Owing to recent advances in thoracic electrical impedance tomography (EIT), a patient’s hemodynamic function can be noninvasively and continuously estimated in real-time by surveilling a cardiac volume signal (CVS) associated with stroke volume and cardiac output. In clinical applications, however, a CVS is often of low quality, mainly because of the patient’s deliberate movements or inevitable motions during clinical interventions. This study aims to develop a signal quality indexing method that assesses the influence of motion artifacts on transient CVSs. The assessment is performed on each cardiac cycle to take advantage of the periodicity and regularity in cardiac volume changes. Time intervals are identified using the synchronized electrocardiography system. We apply divergent machine-learning methods, which can be sorted into discriminative-model and manifold-learning approaches. The use of machine-learning could be suitable for our real-time monitoring application that requires fast inference and automation as well as high accuracy. In the clinical environment, the proposed method can be utilized to provide immediate warnings so that clinicians can minimize confusion regarding patients’ conditions, reduce clinical resource utilization, and improve the confidence level of the monitoring system. Numerous experiments using actual EIT data validate the capability of CVSs degraded by motion artifacts to be accurately and automatically assessed in real-time by machine learning. The best model achieved an accuracy of 0.95, positive and negative predictive values of 0.96 and 0.86, sensitivity of 0.98, specificity of 0.77, and AUC of 0.96.
From Weyl groups to semisimple groups
Authors: Lusztig G.
Published: March 2023

In this paper we show, using ideas from the theory of total positivity, how a number of properties of a semisimple group over the complex numbers can be presented purely in terms of the Weyl group. We also describe some new connections of the theory of canonical bases with total positivity.
Use of Activated Platelet-Rich Plasma (A-PRP) on Alopecia: A Systematic Review and Meta-Analysis
Authors: Morkuzu Suat , McLennan Alexandra Loren , Kanapathy Muholan , Mosahebi Afshin
Published: March 2023

Alopecia affects perceptions of age, beauty, success, and adaptability. Hair loss can be caused by genetic, physiological, environmental, and immunologic factors. The current treatment for alopecia is varied. This systematic review and meta-analysis evaluates activated platelet rich plasma (A-PRP) for alopecia treatment. The objective of this review was to assess the clinical efficacy and safety of A-PRP injections in alopecia patients. We compared the safety, limitations, and outcomes of A-PRP use with those of previous research on alopecia. We searched PubMed, EMBASE, the Cochrane Database, and Google Scholar for relevant articles. We included all primary clinical studies involving patients that evaluated A-PRP. Twenty-nine articles, which included 864 patients, met the eligibility criteria and were analyzed for qualitative review. Our review found 27 studies that indicated A-PRP was significantly effective in treating alopecia, especially for improving hair density before and after therapy (n = 184, mean difference [MD] = 46.5, I2 = 88%, 95% CI: 29.63, 63.37, P < .00001), as well as when comparison was made between treatment and control groups (n = 88, MD = 31.61, I2 = 80%, 95% CI: 6.99, 56.22, P = .01), and of terminal hair density between treatment and control groups (n = 55, MD = 26.03, I2 = 25%, 95% CI: 8.08, 43.98, P = .004); hair counts after therapy (n = 85, MD = 12.79, I2 = 83%, 95% CI: -5.53, 31.12, P = .0006); promoting hair regrowth; folliculogenesis; reducing hair loss; combining with follicular unit extraction (FUE) surgery; and initiating the hair cycle. Two studies did not report significant results. This is the first systematic review and meta-analysis of A-PRP as a treatment option for alopecia. A-PRP appears to be a promising and safe method for treating alopecia.

Level of Evidence: 4
α-Tomatine degradation to tomatidine by food-related Aspergillus species belonging to the section Nigri
Authors: Hui Chun-Wai , Kishino Shigenobu , Nakatani Yuki , Ogawa Jun
Published: March 2023

α-Tomatine is a steroidal glycoalkaloid in tomato plants and degrades with ripening. The aglycone form, tomatidine, is reported to have beneficial effects. In this study, the ability of food-related microorganisms to produce tomatidine from α-tomatine was evaluated. A total of 11 strains of Aspergillus species belonging to the section Nigri exhibited tomatinase activity, and Aspergillus luchuensis JCM 22302 was selected for optimization due to its high activity in its mycelia, conidia, and non-mycotoxin-producing property. Next, using A. luchuensis JCM22302 conidia, the highest yield was obtained in a 24-h reaction with 50 m m of acetic acid–sodium acetate buffer (pH 5.5) at 37 °C. Similar to the tomato pathogen Fusarium oxysporum f. lyceopersici, the time course analysis suggested that A. luchuensis JCM 22302 removed the entire sugar moiety in a single step. Future research will focus on utilizing conidia for large-scale tomatidine production because of their high tolerance and manageability.
The hidden factor: accounting for covariate effects in power and sample size computation for a binary trait
Authors: Zhang Ziang , Sun Lei
Published: March 2023

Motivation

Accurate power and sample size estimation is crucial to the design and analysis of genetic association studies. When analyzing a binary trait via logistic regression, important covariates such as age and sex are typically included in the model. However, their effects are rarely properly considered in power or sample size computation during study planning. Unlike when analyzing a continuous trait, the power of association testing between a binary trait and a genetic variant depends, explicitly, on covariate effects, even under the assumption of gene–environment independence. Earlier work recognizes this hidden factor but the implemented methods are not flexible. We thus propose and implement a generalized method for estimating power and sample size for (discovery or replication) association studies of binary traits that (i) accommodates different types of nongenetic covariates E, (ii) deals with different types of G–E relationships, and (iii) is computationally efficient.

Results

Extensive simulation studies show that the proposed method is accurate and computationally efficient for both prospective and retrospective sampling designs with various covariate structures. A proof-of-principle application focused on the understudied African sample in the UK Biobank data. Results show that, in contrast to studying the continuous blood pressure trait, when analyzing the binary hypertension trait ignoring covariate effects of age and sex leads to overestimated power and underestimated replication sample size.

Availability and implementation

The simulated datasets can be found on the online web-page of this manuscript, and the UK Biobank application data can be accessed at https://www.ukbiobank.ac.uk. The R package SPCompute that implements the proposed method is available at CRAN. The genome-wide association studies are carried out using the software PLINK 2.0 [Purcell et al. (Plink: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007;81:559–75.)].
Phenonaut: multiomics data integration for phenotypic space exploration
Authors: Shave Steven , Dawson John C , Athar Abdullah M , Nguyen Cuong Q , Kasprowicz Richard , Carragher Neil O
Published: March 2023

Data integration workflows for multiomics data take many forms across academia and industry. Efforts with limited resources often encountered in academia can easily fall short of data integration best practices for processing and combining high-content imaging, proteomics, metabolomics, and other omics data. We present Phenonaut, a Python software package designed to address the data workflow needs of migration, control, integration, and auditability in the application of literature and proprietary techniques for data source and structure agnostic workflow creation.

Availability and implementation

Source code: https://github.com/CarragherLab/phenonaut, Documentation: https://carragherlab.github.io/phenonaut, PyPI package: https://pypi.org/project/phenonaut/.
Seqpac: a framework for sRNA-seq analysis in R using sequence-based counts
Authors: Skog Signe , Örkenby Lovisa , Kugelberg Unn , Öst Anita , Nätt Daniel
Published: March 2023

Motivation

Feature-based counting is commonly used in RNA-sequencing (RNA-seq) analyses. Here, sequences must align to target features (like genes or non-coding RNAs) and related sequences with different compositions are counted into the same feature. Consequently, sequence integrity is lost, making results less traceable against raw data.

Small RNA (sRNA) often maps to multiple features and shows an incredible diversity in form and function. Therefore, applying feature-based strategies may increase the risk of misinterpretation. We present a strategy for sRNA-seq analysis that preserves the integrity of the raw sequence making the data lineage fully traceable. We have consolidated this strategy into Seqpac: An R package that makes a complete sRNA analysis available on multiple platforms. Using published biological data, we show that Seqpac reveals hidden bias and adds new insights to studies that were previously analyzed using feature-based counting.

We have identified limitations in the concurrent analysis of RNA-seq data. We call it the traceability dilemma in alignment-based sequencing strategies. By building a flexible framework that preserves the integrity of the read sequence throughout the analysis, we demonstrate better interpretability in sRNA-seq experiments, which are particularly vulnerable to this problem. Applying similar strategies to other transcriptomic workflows may aid in resolving the replication crisis experienced by many fields that depend on transcriptome analyses.

Availability and implementation

Seqpac is available on Bioconductor (https://bioconductor.org/packages/seqpac) and GitHub (https://github.com/danis102/seqpac).
SOX8 is essential for male sexual differentiation in the Chinese soft-shelled turtle Pelodiscus sinensis
Authors: Yang Bangsai , Sun Wei , Jin Lin , Li Pan , Zhou Yingjie , Qian Guoying , Ge Chutian , Xiao Ling
Published: March 2023

SOX8, which belongs to SOXE transcription factor subfamily together with SOX9, participates in sex differentiation and testicular development by enhancing the function of SOX9 in mammals. However, the functional role of SOX8 in sex differentiation has not yet been identified in any non-mammalian vertebrates. Here, we found in the Chinese soft-shelled turtle Pelodiscus sinensis that SOX8 exhibited male-specific higher expression from stage 14 to 18, the critical period of sex determination, prior to the onset of gonadal differentiation. In addition, SOX8 was rapidly down-regulated during male-to-female sex reversal induced by estradiol. Moreover, knockdown of SOX8 led to complete feminization of ZZ P. sinensis, determined by gonadal morphology and distribution of germ cells, as well as the down-regulation of testicular marker DMRT1 and the up-regulation of ovarian regulator FOXL2. In conclusion, this study provides evidence that SOX8 is a key regulator of early male differentiation in P. sinensis, highlighting the significance of the SOX family in reptile sex determination.
A case of hermaphroditism in the gonochoristic sea urchin, Strongylocentrotus purpuratus, reveals key mechanisms of sex determination
Authors: Pieplow Cosmo A , Furze Aidan R , Wessel Gary M
Published: March 2023

Sea urchins are usually gonochoristic, with all of their five gonads either testes or ovaries. Here, we report an unusual case of hermaphroditism in the purple sea urchin, Strongylocentrotus purpuratus. The hermaphrodite is self-fertile, and one of the gonads is an ovotestis; it is largely an ovary with a small segment containing fully mature sperm. Molecular analysis demonstrated that each gonad producedviable gametes, and we identified for the first time a somatic sex-specific marker in this phylum: Doublesex and mab-3 related transcription factor 1 (DMRT1). This finding also enabled us to analyze the somatic tissues of the hermaphrodite, and we found that the oral tissues (including gut) were out of register with the aboral tissues (including tube feet) enabling a genetic lineage analysis. Results from this study support a genetic basis of sex determination in sea urchins, the viability of hermaphroditism, and distinguish gonad determination from somatic tissue organization in the adult.
Telling Stories of Practice in the Neo-liberal Context of English Social Work
Authors: Amas Deborah , Fox Joanna
Published: March 2023

The authors contend that the rise of neo-liberal codified management systems within English social work increasingly restricts social workers freedom to be creative in their practice reducing them to social administrators. We are two registered social work professionals and academics who believe managerial contexts encroach on our professional values. As insider researchers, we engaged in conversations and case storytelling to examine how our knowledge and practice as social workers positively influenced outcomes for people who have lived experiences. The two stories articulated in this article magnify how professional use of self can enact emancipatory empathy in the minutiae of practice. Collaborating as insider ethnographers supported us to deconstruct practice using critical reflection and reflexivity in post-modernist contexts. We highlight how micro examinations in collaborative autoethnography have potential for engaging wider philosophical conversations about social work identity.
The Privatisation of Private (and) International Law
Authors: Mills Alex
Published: March 2023

Privatisation is much studied and debated as a general phenomenon, including in relation to its legal effects and the challenges it presents to the boundaries of public and private law. Outside the criminal context there has however been relatively limited focus on privatisation of the governmental functions which are perhaps of most interest to lawyers—law making, law enforcement and dispute resolution—or on the international legal implications of privatisation. This article argues that modern legal developments in the context of private law and cross-border private legal relations—generally known as party autonomy in private international law—can be usefully analysed as two distinct forms of privatisation. First, privatisation of certain allocative functions of public and private international law, in respect of both institutional and substantive aspects of private law regulation, through the legal effect given to choice of court and choice of law agreements. Second, privatisation of the institutional and substantive regulation of private legal relationships themselves, through arbitration and the recognition of non-state law. Together, these developments have established a global marketplace of state and non-state dispute resolution institutions and private laws, which detaches private law authority from its traditional jurisdictional anchors. Analysing these developments through the lens of privatisation highlights a number of important critical questions which deserve greater consideration—this article further examines in particular whether this form of privatisation in fact increases efficiency in either private international law decision-making or private law dispute resolution, as well as its distributive and regulatory effects.
Cryptanalysis of Reduced-Round SipHash
Authors: He Le , Yu Hongbo
Published: March 2023

SipHash is a family of ARX-based MAC algorithms optimized for short inputs. So far, a lot of implementations and applications for SipHash have been proposed, whereas the cryptanalysis of SipHash still lags behind. In this paper, we study the property of truncated differential in reduced-round SipHash. By exhaustively testing all kinds of 1-bit input differences, we find out the greatest differential biases from corresponding output bits through 3 or 4 SipRounds. Making use of these results, we construct distinguishers for SipHash-2-1 and SipHash-2-2 with practical complexities of $2^{12}$ and $2^{36}$, respectively. However, one limitation of the latter is that it begins with 1-bit input differences on the most significant message bit, which means it can only work when neglecting the padding rules of SipHash. Furthermore, we reveal the relations between the value of output bias and the difference after the first modular addition step, which is directly determined by corresponding key bits. Based on these relations, we propose a key recovery method for SipHash-2-1 that can obtain a significantly nonuniform distribution of the 128-bit secret key. It is summarized that about $97\%$ of random keys can be fully recovered under this method within a complexity of $2^{83}$.
Time use, time pressure and sleep: is gender an effect modifier?
Authors: Scovelle Anna J , Hewitt Belinda , Lallukka Tea , O’Neil Adrienne , King Tania L
Published: March 2023

Background

The gendered division of labour contributes to differences in the way time is spent and experienced by women and men. Time spent in paid and unpaid labour is associated with sleep outcomes, therefore, we examined (i) the relationships between time use and time pressure, and sleep, and (ii) whether these relationships were modified by gender.

Methods

Adults from the Household Income and Labour Dynamics in Australia survey were included in the analysis (N = 7611). Two measures of time use (total time commitments, ≥50% of time spent in paid work) were calculated based on estimates of time spent in different activities. One measure of time pressure was also included. Three sleep outcomes (quality, duration and difficulties) were examined. Logistic regression and effect measure modification analyses were employed.

Results

Total time commitments were associated with sleep duration, whereby more hours of total time commitments were associated with an increase in the odds of reporting <7 h sleep. Gender was an effect modifier of the association between ≥50% of time spent in paid work and (i) sleep duration on the multiplicative scale, and (ii) sleep difficulties on the multiplicative and additive scales. Men who spent <50% of time in paid work reported more sleep difficulties than men who spent ≥50% of time spent in paid work. Feeling time pressured was associated with poor sleep quality, short sleep duration and sleep difficulties.

Conclusions

Time use and time pressure were associated with sleep, with some effects experienced differently for men and women.
Alive and kicking: suicide rates and major soccer events in Austria, Germany and Switzerland
Authors: Pichler Eva-Maria , Ploederl Martin , Rainer Lucas , Gilhofer Thomas S , Michel Jonathan , van der Stouwe Jan Gerrit , Luescher Thomas F , Schmied Christian M , Kawohl Wolfram , Kronschnabel Jens , Niederseer David
Published: March 2023

Background

Major sporting events are postulated to reduce suicide rates by increased social connectedness, by identifying with winning teams, or, conversely, to increase suicide rates by the ‘broken promise effect’.

Methods

In our observational epidemiological study, we investigated changes in suicide rates between 1970 and 2017 in Austria, Germany and Switzerland during the European and World Soccer Championships in general, and on days that the home team played, won or lost.

Results

Combining all three studied nations no statistically significant change in the incidence of daily suicides during soccer championships compared to a control period was noted (38.29 ± 9.02 vs. 37.33 ± 10.58; incidence risk ratio = 1.03; 95% confidence interval: 1.01–1.05, P = 0.05). Essentially, no differences in the expected directions were found, and none remained statistically significant after correcting for multiple comparisons in subgroups for country, age and gender in all three studied countries. Compared to a control period, neither a significant difference in the respective national suicide rate was found after Germany’s four championship victories nor after Austria’s emotional only win over Germany.

Conclusion

Our results do not support the assumption of increased social connectedness and, thus, lowered suicide risk during major sporting events or changes in suicide risk depending on the outcome of important games as predicted by the broken promise effect or changes in self-efficacy by identification with winning teams.
Sleep Behaviors and Progression of Multimorbidity in Middle-Aged and Older Adults: A Prospective Cohort Study From China
Authors: Zhou Yaguan , Ni Yujie , Jones Mark , Dai Xiaochen , Lim Carmen C W , Zhu Anna , Xu Xiaolin
Published: March 2023

Background

Sleep behavior (eg, sleep duration, sleep quality, and nap) is closely related to many chronic conditions. However, less is known about its association with multiple chronic conditions (multimorbidity), particularly evidence from cohort studies.

Methods

Data were collected from a cohort of 8 937 individuals aged 45 and older from the China Health and Retirement Longitudinal Study (2011–2018). Sleep duration, sleep quality, and nap duration were collected in 2011 and 2013. Progression of multimorbidity was defined as the first report of 2 or more chronic conditions for participants without multimorbidity or the new report of 1 or more conditions for those with multimorbidity. Cox regression models were performed to calculate the hazard ratios and 95% confidence intervals (CIs) of the associations between sleep behaviors and the progression of multimorbidity.

Results

Short sleep duration and poor sleep quality were associated with the progression of multimorbidity independently and jointly, especially in those less than 65 years and females. The U-shaped dose–response relationships were observed between nighttime and total sleep duration and the progression of multimorbidity. Persistent short and unsteadily changed sleep behaviors increased the risk of multimorbidity progression. Individuals sleeping ≤5 h/night with 5–7 restless days/week had 1.53 times higher risk of multimorbidity progression (95% CI: 1.37–1.71), compared to those sleeping 7–8 h/night with <1 restless day/week.

Conclusions

Short sleep duration and poor sleep quality were independently and jointly associated with a higher risk of multimorbidity progression in a mid-to-older population. Optimal sleep duration and sleep quality should be emphasized in multimorbidity prevention and control.
Trends in Gender and Racial/Ethnic Disparities in Physical Disability and Social Support Among U.S. Older Adults With Cognitive Impairment Living Alone, 2000–2018
Authors: Chen Shanquan , Zhang Huanyu , Underwood Benjamin R , Wang Dan , Chen Xi , Cardinal Rudolf N
Published: March 2023

Background and Objectives

Informal care is the primary source of support for older adults with cognitive impairment, yet is less available to those who live alone. We examined trends in the prevalence of physical disability and social support among older adults with cognitive impairment living alone in the United States.

Research Design and Methods

We analyzed 10 waves of data from the U.S. Health and Retirement Survey spanning 2000–2018. Eligible people were those aged ≥65, having cognitive impairment, and living alone. Physical disability and social support were measured via basic and instrumental activities of daily living (BADLs, IADLs). We estimated linear temporal trends for binary/integer outcomes via logistic/Poisson regression, respectively.

Results

A total of 20 070 participants were included. Among those reporting BADL/IADL disability, the proportion unsupported for BADLs decreased significantly over time (odds ratio [OR] 0.98, 95% confidence interval [CI] 0.97–0.99), and the proportion unsupported for IADLs increased (OR = 1.02, CI 1.01–1.04). Among those receiving IADL support, the number of unmet IADL support needs increased significantly over time (relative risk [RR] 1.04, CI 1.03–1.05). No gender disparities were found for these trends. Over time, Black respondents had a relatively increasing trend of being BADL-unsupported (OR = 1.03, CI 1.0–1.05) and Hispanic and Black respondents had a relatively increasing trend in the number of unmet BADL needs (RR = 1.02, CI 1.00–1.03; RR = 1.01, CI 1.00–1.02, respectively), compared to the corresponding trends in White respondents.

Discussion and Implications

Among lone-dwelling U.S. older adults with cognitive impairment, fewer people received IADL support over time, and the extent of unmet IADL support needs increased. Racial/ethnic disparities were seen both in the prevalence of reported BADL/IADL disability and unmet BADL/IADL support needs; some but not all were compatible with a reduction in disparity over time. This evidence could prompt interventions to reduce disparities and unmet support needs.
Application of the EEPAS earthquake forecasting model to Italy
Authors: Biondini E , Rhoades D A , Gasperini P
Published: March 2023

The Every Earthquake a Precursor According to Scale (EEPAS) forecasting model is a space–time point-process model based on the precursory scale increase ($\psi $ ) phenomenon and associated predictive scaling relations. It has been previously applied to New Zealand, California and Japan earthquakes with target magnitude thresholds varying from about 5–7. In all previous application, computations were done using the computer code implemented in Fortran language by the model authors. In this work, we applied it to Italy using a suite of computing codes completely rewritten in Matlab. We first compared the two software codes to ensure the convergence and adequate coincidence between the estimated model parameters for a simple region capable of being analysed by both software codes. Then, using the rewritten codes, we optimized the parameters for a different and more complex polygon of analysis using the Homogenized Instrumental Seismic Catalogue data from 1990 to 2011. We then perform a pseudo-prospective forecasting experiment of Italian earthquakes from 2012 to 2021 with Mw ≥ 5.0 and compare the forecasting skill of EEPAS with those obtained by other time independent (Spatially Uniform Poisson, Spatially Variable Poisson and PPE: Proximity to Past Earthquakes) and time dependent [Epidemic Type Aftershock Sequence (ETAS)] forecasting models using the information gain per active cell. The preference goes to the ETAS model for short time intervals (3 months) and to the EEPAS model for longer time intervals (6 months to 10 yr).