bluuebunny/crossref_metadata_2025 huggingface dataset:
DYNAMICS OF A SIMPLIFIED HOLLING IV TYPE PREDATOR–PREY SYSTEM WITH WEAK ALLEE EFFECT ON PREY AND ANTI-PREDATOR BEHAVIOR
Authors: PANG XIAOLI , QIAO YUANHUA
Published: September 2024

In this paper, we investigate a simplified Holling IV type predator–prey model with weak Allee effect on prey and anti-predator behavior. First, the existence and stability of all possible equilibria are analyzed, which suggests the changing trend of the predator-prey system under different initial values. Second, bifurcation analysis at the equilibria are performed to explore the dynamic behavior of the system while the parameters pass the critical values, which reveals the influence of the death rate, anti-predator behavior and weak Allee effect on the system. It is found that the system undergoes saddle-node bifurcation, cusp type Bogdanov–Takens bifurcation of codimension 2 and 3, and Hopf bifurcation, forming the organizing center of a series of codimensional bifurcations. The bifurcations indicate the change of the final state and the occurrence of oscillations of the predator–prey system under different parameters. Finally, the theoretical results are confirmed by numerical simulations.
A Dynamic Game Analysis of Hospitals’ Quality-Improving and Congestion-Reducing with Corresponding Knowledge Accumulations Effects
Authors: Jiang Xiuzhen , Zhang Ming
Published: September 2024

In this paper, we develop a dynamic control to investigate the hospitals’ quality improvement and congestion reduction, along with corresponding knowledge accumulations. The main features of our work are: (i) developing a dynamic analysis model of the hospitals’ quality improvement and congestion reduction, considering knowledge accumulations in health care markets; (ii) the demand function for medical treatment depends on treatment quality, congestion degree, price, and traveling cost; (iii) each hospital’s instantaneous costs of quality improvement and congestion reduction depend on treatment quality, quality-improving investment, corresponding knowledge accumulation as well as congestion degree, congestion-reducing investment and the corresponding knowledge accumulation; (iv) the hospitals’ dynamic competitions are not only in treatment quality and congestion degree but also in treatment prices. Our results show that (i) there exists a unique saddle-stable steady-state equilibrium under hospital optimum and social optimum; (ii) knowledge accumulation and the complementarity or substitutability affect the hospitals’ decision behavior; (iii) whether the price and the hospitals’ investments in quality improvement and congestion reduction are higher or lower under hospital optimum than that under social optimum depends on the parameter regions of complementarity or substitutability.
Dynamic Modeling and Analysis of Multi-Span Timoshenko Beams Under Moving Loads
Authors: Huang Xijun , Chai Yuyang , Li Fengming
Published: September 2024

Dynamic response analysis of multi-span beams is one of the important topics in the field of highway and railway engineering, which provides valuable guidance for the design, operation and maintenance of multi-span bridges. It is worth considering how to calculate the dynamic characteristics of multi-span beams quickly and conveniently. In this study, an effective analytical method is developed for the dynamic modeling and investigations of multi-span Timoshenko beams under moving loads by employing the assumed mode method (AMM). Based on Hamilton’s principle, the equation of motion of the Timoshenko multi-span beam subjected to moving loads is formulated and the natural frequencies are calculated. A comprehensive investigation is conducted on the dynamic responses of the multi-span Timoshenko beam considering different factors, including the length-to-thickness ratio, disorder degree, arrangement order, number of spans and related parameters of moving loads. In addition, the influence of the interval and velocity of the moving load series on the dynamic responses, including displacement, velocity and acceleration of the multi-span beam, are analyzed in detail. The theoretical calculation results of multi-span Timoshenko beams under moving loads are compared with numerical results obtained from ANSYS software, and the results are in good agreement. This demonstrates that the developed method, which utilizes the AMM to analyze the dynamic characteristics of multi-span beams subjected to moving loads, significantly simplifies the calculations and is well-suited for practical engineering applications.
Performance Analysis of Low-Frequency Piezoelectric Energy Harvesting Systems with Multiple Nonlinear Factors and Bidirectional Excitations
Authors: Xia Guanghui , Zhang Su , Liu Mingrui , Xia Hua , Wang Wei , Kang Xiaofang , Han Tingting , Chen Leiyu , Lim C. W.
Published: September 2024

With the swift advancement of microelectronic technology and MEMS, piezoelectric energy harvesting technology has garnered escalating attention due to its eco-friendly and sustainable attributes. In this paper, a bimorph piezoelectric energy harvesting system considering multi-nonlinearity complex factors is devised, and the approximate analytical solutions for vertical displacement, output voltage, and output power of the entire system are derived. Owing to inherent nonlinear softening characteristic of material nonlinearity, the effective frequency bandwidth of the energy harvesting system is significantly broadened. The result indicates that under horizontal excitation ranging from 0.2[Formula: see text]g to 0.3[Formula: see text]g, the peak output voltage of the energy harvesting system with a frequency of 3.2254[Formula: see text]Hz (open circuit) increases approximately by 7.9 times. At another frequency of 3.2054[Formula: see text]Hz (short circuit), the peak output voltage amplitude is multiplied by approximately 6.5 times. Considering material nonlinearity, it can be concluded that the system energy harvesting efficiency at low frequency can be greatly improved. The numerical result obtained is not only more accurate, but it is also more consistent with real situations. This conclusion provides a theoretical basis for research and analysis of similar systems in low-frequency ranges.
Probability Characteristics of Gompertz Model with Different Kinds of Colored Noise Excitation (invited talk)
Authors: Dubkov Alexander
Published: September 2024

We explore the steady-state probability distribution of Gompertz model in tumor growth rate for two different kinds of colored noise with exponential correlation functions, namely, for Ornstein–Uhlenbeck process and Markovian dichotomous noise. Comparing the behavior of the steady-state distributions depending on the correlation time of these noises with the same power, we establish the influence of the probability characteristics of fluctuations on the original system.
Multiscale Irreversibility Analysis of Time Series Based on Permutation Jensen–Shannon Distance
Authors: Fan Qingju , Song Jiayu , Li Dan
Published: September 2024

In this study, we propose a multiscale permutation Jensen–Shannon distance (MPJSD) to measure irreversibility of complex time series. The new quantifier is based on symbolic permutation pattern and Jensen–Shannon distance. As an alternative, the new method offers the best characterization of the underlying irreversibility on different scales. The ARFIMA process and three dissipative chaotic systems are used to verify the effectiveness of the new method. The numerical results indicate that the MPJSD can unveil subtle and interesting findings on different scales and the permutation Jensen–Shannon distance (PJSD) is scale-dependent. Furthermore, we apply the approach to detect the multiscale irreversibility of ECG and financial data. The underlying irreversible nature of the investigated series is well discriminated. The method here introduced gives a new way to distinguish different degrees of irreversibility.
On the automorphisms of the Drinfeld modular groups
Authors: Mason A. W. , Schweizer Andreas
Published: September 2024

Let [Formula: see text] be the ring of elements in an algebraic function field [Formula: see text] over [Formula: see text] which are integral outside a fixed place [Formula: see text]. In contrast to the classical modular group [Formula: see text] and the Bianchi groups, the Drinfeld modular group [Formula: see text] is not finitely generated and its automorphism group [Formula: see text] is uncountable. Except for the simplest case [Formula: see text] not much is known about the generators of [Formula: see text] or even its structure. We find a set of generators of [Formula: see text] for a new case.

On the way, we show that every automorphism of [Formula: see text] acts on both the cusps and the elliptic points of [Formula: see text]. Generalizing a result of Reiner for [Formula: see text] we describe for each cusp an uncountable subgroup of [Formula: see text] whose action on [Formula: see text] is essentially defined on the stabilizer of that cusp. In the case where [Formula: see text] (the degree of [Formula: see text]) is [Formula: see text], the elliptic points are related to the isolated vertices of the quotient graph [Formula: see text] of the Bruhat–Tits tree. We construct an infinite group of automorphisms of [Formula: see text] which fully permutes the isolated vertices with cyclic stabilizer.
A Bayesian-Based Credible and Reliable Control Method for Active Vibration Suppression of Structures with Uncertain Parameters
Authors: Hu Wenshuo , Zhang Guokang , Li Yunlong , Chen Wenpin , Xu Menghui , Qiu Zhiping
Published: September 2024

As a classical design method for addressing uncertainty in control systems, robust control is designed with the goal of complete reliability of the control system. Nevertheless, the pursuit of robustness can inadvertently give rise to considerable performance degradation, rendering the resultant closed-loop control system excessively conservative in its design. Reliability-based design methods serve as an effective approach for managing uncertainties, which will achieve a balance between the robustness and performance of the active control system by taking advantage of the characteristic of reliability that allows for a certain level of permissible failure probability. The accurate quantification of uncertainty is the key to achieving reliable control, but common uncertainty quantification methods cannot achieve credible quantification of uncertainty in small samples and update the distribution of new samples. In this paper, a nonprobabilistic Bayesian inference based interval uncertainty quantification method is proposed. This method updates the distribution of interval boundaries and radii by introducing a small number of samples, and obtains interval parameters under a given confidence level. On the basis of uncertainty quantification, the dynamic reliability of the vibration system is derived, and nonprobabilistic reliability is introduced into the design of active controllers through optimization strategies. The reliable control strategy aims to select the optimal controller parameters on a reliable path with a given credibility, in order to solve the problem of overly conservative robust control theory. Two numerical examples were used to verify the feasibility and applicability of this method.
On Connectivity of Multidimensional Fuzzy Graphs and its Applications
Authors: Josen Jomal , John Sunil Jacob
Published: September 2024

Connectivity, average connectivity, and its related concepts are prominent notions in fuzzy graph theory that have applications in various areas, including neural networks, transportation problems, cluster analysis, and telecommunication. This work introduces the concepts of connectivity index, average connectivity index, type 2 connectivity index, etc. to a more generalized variant of a fuzzy graph, namely the multidimensional fuzzy graph. Basic results such as the relation of these parameters to vertices and edges, their bounds in some particular multidimensional fuzzy graphs, etc. are studied with proper illustrations. Theorems on the connectivity index of multidimensional fuzzy graphs are obtained after performing operations like direct product, tensor product, composition, join, and so on. Finally, a decision-making problem that can be effectively handled using the connectivity index is demonstrated and compared with others and similar models.
Surface Super-Hydrophobicity of Aluminum Alloy and its Corrosion and Anti-Icing Properties
Authors: Zhang Yi , Zhang Yanxiu , Wang Senlin
Published: September 2024

Aluminum alloy was subjected to anodization and then treated with a mixture of dodecanoic acid and aluminum sulfate, which produced an aluminum alloy that was extremely hydrophobic. Using energy dispersive spectroscopy (EDS), Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM), the surface structure and composition of the aluminum alloy samples were examined. The results showed that the dodecanoic acid and aluminum sulfate mixture-treated aluminum alloy surface underwent etching while also absorbing aluminum dodecanoate, resulting in a micro–nano conical nonuniform structure. With a static contact angle (CA) of 156[Formula: see text], the superhydrophobic aluminum alloy has exceptional anti-icing and self-cleaning qualities. When compared to anodized aluminum alloys, the superhydrophobic aluminum alloy exhibits improved corrosion resistance in a 3.5[Formula: see text]wt.% NaCl solution.
Hydrothermal Approach of Spinel Copper Cobaltite (CuCo2O4) Nanostructures and Their Structural and Functional Properties
Authors: Manimegalai S. , Soundhirarajan P. , Silambarasan M.
Published: September 2024

CuCo2O4 nanoparticles were synthesized via facile hydrothermal route using oxalic as a precipitant, thermal decomposition of CuCo2O4 precursor at 400[Formula: see text]C. The structural studies from X-ray diffraction (XRD), Fourier transform infrared spectrometer, Raman spectroscopy and X-ray photoelectron spectroscopy (XPS) disclose the predominant spinel crystal phase for copper cobaltite. The optical absorption spectra reveal two band gaps of 3.8[Formula: see text]eV and 4.4[Formula: see text]eV in the CuCo2O4 nanoparticles. The cyclic voltammetry (CV) was used to assess the electrochemical characteristics of the resulting product in an organic electrolyte at −1.5–1.5[Formula: see text]V under ambient conditions. On 22.4[Formula: see text]nm CuCo2O4 nanoparticles, a greater capacitance of 920[Formula: see text]F/g at a scan rate of 5[Formula: see text]mV/s was achieved.
Effects of information-induced behavioral changes on brucellosis outbreak in Jilin province
Authors: Ma Xia , Luo Xiao-Feng , Sun Gui-Quan
Published: September 2024

Brucellosis, as a prevalent zoonosis caused by Brucella, primarily spreads in northern pastoral regions of China. The high levels of perceived risk about brucellosis before 2009 were largely suspected in Jilin province, as well as its effect in stemming the transmission of brucellosis. We will devise two epidemic models to investigate the effects of spontaneous changes in herder’s behavior awareness on the transmission of brucellosis. The global dynamics of these models will be thoroughly analyzed. The models are utilized to fit the data of newly infected cases of brucellosis in Jilin province from 2002–2020. The vital information-induced parameters of brucellosis have been estimated by the Markov Chain Monte Carlo (MCMC) method. The basic reproduction numbers are calculated as [Formula: see text] prior to 2009 and [Formula: see text] after 2009. Moreover, our findings indicate that a one-year delay in the implementation of pilot work in Jilin province by the government would result in a 50% increase in the peak number of newly infected brucellosis cases, surpassing 5000. On the contrary, if the government were to implement the pilot work in Jilin province one year ahead of schedule, there would be a 40% reduction in the peak number of newly infected brucellosis cases. Furthermore, the results suggest that enhancing the voluntary detection and protection rate is more effective than increasing voluntary rates. Information-induced detection and protection play a crucial role in curbing the spread of brucellosis. The increase in the reactivity factor of voluntary detection [Formula: see text] from 0.00128 to 0.0128 will result in a reduction of the incidence rate of human brucellosis cases to less than 1 per 100,000, enabling the achievement of the national control target seven years ahead of schedule. The insights shed herein may be conductive to suppress the spread of brucellosis in other areas.
Existence solutions for nondensely integrodifferential equations with state-dependent delay
Authors: Kpoumié Moussa El-Khalil , Djeunankam Yannick-Levis , Mbang Joseph , Noundjeu Pierre
Published: September 2024

In this work, we study the existence of mild solutions for some nondensely partial functional integro-differential equations with state-dependent delay in Banach spaces. We assume that the linear part is not necessarily densely defined and generates an integrated resolvant operators. The nonlinear part satisfies Carathéodory’s conditions. Our approach is based on the generalized Darbo Fixed Point Theorem on Banach spaces and the integrated resolvent operators theory. For illustration, we propose a reaction–diffusion equation with state-dependent delay. The results obtained in this paper are a generalization of some existing results in this area.
Computing free convolutions via contour integrals
Authors: Cortinovis Alice , Ying Lexing
Published: September 2024

This work proposes algorithms for computing additive and multiplicative free convolutions of two given probability measures. We consider probability measures with compact support whose free convolution results in a probability measure with a density function that exhibits a square-root decay at the boundary (for example, the semicircle distribution or the Marchenko–Pastur distribution). A key ingredient of our method is rewriting the intermediate quantities of the free convolution using the Cauchy integral formula and then discretizing these integrals using the trapezoidal quadrature rule, which converges exponentially fast under suitable analyticity properties of the functions to be integrated.
U.S.–China Competition: A Power Transition Perspective
Authors: Örmeci Ozan , Kisacik Sina , Helvacikőylȕ Gamze
Published: September 2024

U.S.–China competition has been widely viewed as the most important feature of world politics that will shape the emerging international order. Whereas Washington increasingly sees Beijing as the sole great power with the intent and capabilities to dismantle the U.S.-led liberal order, Beijing views Washington’s military buildup and new partnerships in the Indo-Pacific region as the latest U.S. attempt to contain and encircle China. This paper adopts a power transition perspective to compare the advantages and disadvantages of both powers, using six parameters to measure their relative national strength. In doing so, the authors try to update and modernize A.F.K. Organski’s theory in the 21st century, applying it to the most consequential relationship of our time.
Does Modernization of Irrigation Infrastructure Create Mental Accounts? Insights from an Exploratory Experiment with Spanish Water User Associations
Authors: Hoffmann Patrick , Villamayor-Tomas Sergio
Published: September 2024

Despite their potential to conserve water, technological modernization investments that increase the efficiency of irrigation systems rarely result in water savings. On the contrary, they oftentimes increase overall water consumption. An important factor for this outcome is that farmers adapt their behavior to the new technological possibilities. If actual water savings are to be achieved, water conservation policies need to be tailored to the logic adapted by water users. In this study, we investigate the applicability and relevance of mental accounting in agricultural water use. In particular, we test whether farmers’ perceptions of water diverge conditional on whether it is supplied naturally or obtained from efficiency gains. We conduct a survey-based experiment among representatives of water user associations in Spain. According to the results, farmers tend to have a stronger sense of ownership over water that is obtained from efficiency increases than over water that originates from natural supply increases; however, they do not intend to use both “types” of water differently. Future policies could strongly benefit from targeting the sense of ownership of higher efficiency gains to achieve water savings. Furthermore, the responsibility of translating efficiency gains into water savings should rather be delegated to water user associations than to individual users.
Reaction-diffusion for fish populations with realistic mobility
Authors: Broadbridge Philip
Published: September 2024

Nonlinear reaction-diffusion equations, with Fisher logistic growth and constant diffusion coefficient, have been used in fisheries research to estimate sustainable harvesting rates and critical domain sizes of no-take areas. However, constant diffusivity in a population density corresponds to standard Brownian motion of individuals, with a normal distribution for displacement over a fixed time interval. For available good data sets on mobile fish populations, the distribution is certainly not normal. The data can be fitted with a long-tailed stable Lévy distribution that results from diffusion by fractional Laplacian. Exact multidimensional solutions are developed here for realistic Fisher–Kolmogorov–Petrovski-Piscounov models with diffusion by fractional Laplacian. These can also account for a delay in the reaction term. It is then shown how to modify critical domain sizes of protected areas with Dirichlet and Robin boundary conditions for populations.
Refined Metamodel Disturbance Observer-Based Control for Coarse Pointing Assembly Under Constraints
Authors: Yang Yongjian , Bao Zeyu , Qiao Jianzhong , Zhu Yukai , Guo Lei
Published: September 2024

The target tracking performance of the coarse pointing assembly (CPA) is a critical factor in determining the data transmission efficiency of the inter-satellite laser communication. However, under the influence of multiple disturbances, such as gimbal coupling torque, friction, and satellite-transmitted vibration, the angle tracking performance of the CPA can be decreased, which then affects the safety of the system in terms of angular velocity. To address the performance and safety requirements of the CPA, this paper proposes a refined metamodel disturbance observer-based state constraints controller. First, a refined metamodel disturbance observer is proposed to achieve accurate disturbance estimation by combining the data-driven state-space Kriging metamodeling method with a refined disturbance observer. Both disturbance numerical data and partially known information (e.g. vibration frequency and structure) are fully utilized to reduce estimation conservatism. Second, based on the observer, a state constraint controller is designed to ensure the angle tracking performance and angular velocity constraints. Finally, the effectiveness and robustness of the proposed control method are validated through numerical simulations, indicating an enhanced angle tracking performance compared to the traditional disturbance observer-based control method.
Training Workers for the Future Through Tripartite Partnerships
Authors:   Harvard Business Review Analytic Services
Published: September 2024

As companies plan for the future of work, one key challenge is ensuring they have workers with relevant skills in order to thrive in the years ahead. A major driver of this challenge is that new digital technologies are quickly rendering some workers’ skills obsolete and shortening the half-life of others.

Artificial intelligence, automation, and other advances are also forcing executives to reconsider which roles humans are best suited to and which skills they will need to support companies’ digital ambitions. Answering these questions effectively will ensure companies have the talent to stay competitive and seize new opportunities for growth and profitability.
The Impact of Internships on Graduates’ Employability: Employers’ Insights
Authors: Yeong Janine , Kam Christabel , Lye Edwin , Boo Shannon
Published: September 2024

Internships serve as a valuable tool for students to develop their skills and knowledge, preparing them for a smooth transition into the workforce. The participation in internships amongst students in Singapore has increased as students recognise the need to distinguish themselves from their peers in the job market. Additionally, there is a common belief that employers prioritise fresh graduates with extensive internship backgrounds from reputable organisations. The Singapore National Employers Federation conducted a survey to challenge this belief and examine employers’ perspectives on the internship experiences of fresh graduates. A total of 208 organisations, with a combined workforce size of nearly 250,000, responded to the survey conducted from December 14, 2023 to February 20, 2024. Results suggested that a majority of employers do not consider the number of internships completed and profile of internship organisation as priorities. This paper sheds light on what employers look out for when assessing the internship experiences of fresh graduates. It also discusses the implications for other stakeholders, including students and Institutes of Higher Learning.
How Close Collaboration With Unions During the COVID-19 Pandemic Helped the SIA Group to Save Jobs and Emerge Stronger
Authors: Cham Hui Fong , Ng Wee Leng Vanessa
Published: September 2024

When airports around the world were brought to a standstill by the pandemic, Singapore Airlines (SIA) Group was faced with its biggest challenge—management of its almost 30,000-strong staff in trying times which called for resource cuts. Nevertheless, the SIA Group successfully surmounted these challenges and emerged as one of the most resilient airlines in the post-pandemic landscape. The collaboration between the SIA Group and unions was pivotal in skilfully navigating a balance between a compassionate approach towards its workers and strategic measures aimed at ensuring organisational survival. Through the collaboration, schemes rooted in the SMART Strategy model—comprising Job Support, Job Matching, Job Advocacy, and Job Re-creation and Training—were developed to safeguard the livelihoods and bolster resilience within the workforce. This paper offers valuable lessons for other organisations at risk of technological disruption or industry transitions, and as layoffs become more commonplace.
Practitioner Insights Into Supporting Women at Work Through Administering Flexible Work Arrangements
Authors: Yeo Wan Ling
Published: September 2024

This practitioner note recognises Flexible Work Arrangements (FWAs) as instrumental in supporting workers with caregiving responsibilities, especially working women, in sustaining and developing their careers. Survey findings reveal that workers in full-time positions often find it necessary to take time off from work, but that this negatively impacts their performance, well-being, and career prospects. FWAs therefore benefit workers by helping them manage both caregiving and work responsibilities without the fear of facing unspoken penalties at work. Drawing on two successful case studies of companies committed to empowering women to reenter the workforce, this practitioner note shares key insights into the implementation process of FWAs, which includes job redesign, management support, and a shift towards outcome-based deliverables. These findings and strategies show that job redesign and support from top management are key factors for the successful implementation and maintenance of FWAs, which by extension supports women’s and caregivers’ equal participation and career advancement in the workforce.
Grappling with Health Rights of Women in Climate Change-Induced Conflict and Post-Conflict Situations
Authors: Abledu Yorm , Mike Jennifer Heaven
Published: September 2024

Adverse climate change is more than an environmental concern. The are several consequential outcomes of climate change such as loss of oil wealth, depletion of scarce resources, decline in sources of livelihood, property loss, water shortages, and land scarcity. Secondary effects could include increased mortality, deteriorating health, hunger, poverty, inequality, and financial hardship. Studies over the years have shown that climate change could also precipitate conflicts and lead to displacements. For many women in conflict situations, it is difficult to access medical care, especially reproductive healthcare. Amid efforts to contain insecurity and its devastating effect, the government often loses sight of the vulnerabilities of women and girls, whose reproductive health challenges have been exacerbated by the effects of climate change. Men and women may encounter health challenges in climate change-induced conflict situations however, women may be affected more differently than men. Specific healthcare services, treatments, and commodities for women’s general and reproductive/sexual health are often ignored despite the need for healthcare, menstrual hygiene products, health education, and general health supplies in times of conflict. In addition to the associated conflict-related risk, women may face a heightened risk of rape and other sexual-related violence. The risk to women and girls may further increase if resources are diverted from sexual and reproductive health care to respond to the insecurity and crises or where the supply chain is affected by climate change-induced conflicts. This study examines the challenges that women face in climate change-induced conflict and post-conflict situations, particularly as it affects their reproductive health rights. It further argues that the realization that women’s reproductive and sexual health in a climate change-induced conflict setting is a human right that warrants concerted attention. Ultimately, it advocates for gender-sensitive responses to the reproductive and sexual health of women and girls as a matter of fundamental human right.
Software Product Line Engineering via Software Transplantation
Authors: Oliveria de Souza Leandro , Santana de Almeida Eduardo , Silveira Neto Paulo Anselmo da Mota , Barr Earl T. , Petke Justyna
Published: September 2024

Software Product Lines (SPLs) improve time-to-market, enhance software quality, and reduce maintenance costs. Current SPL reengineering practices are largely manual and require domain knowledge. Thus, adopting and, to a lesser extent, maintaining SPLs are expensive tasks, preventing many companies from enjoying their benefits. To address these challenges, we introduce
Foundry
, an approach utilising software transplantation to reduce the manual effort of SPL adoption and maintenance.
Foundry
enables integrating features across different codebases, even codebases that are unaware that they are contributing features to a software product line. Each product produced by
Foundry
is pure code, without variability annotation, unlike feature flags, which eases variability management and reduces code bloat.

We realise
Foundry
in
prodScalpel
, a tool that transplants multiple organs (i.e., a set of interesting features) from donor systems into an emergent product line for codebases written in C. Given tests and lightweight annotations identifying features and implantation points,
prodScalpel
automates feature extraction and integration. To evaluate its effectiveness, our evaluation compares feature transplantation using
prodScalpel
to the current state of practice: on our dataset,
prodScalpel
’s use speeds up feature migration by an average of 4.8 times when compared to current practice.
From Muscle-Based Nonshivering Thermogenesis to Malignant Hyperthermia in Mammals
Authors: Launikonis Bradley S. , Murphy Robyn M.
Published: September 2024

For physiological processes in the vital organs of eutherian mammals to function, it is important to maintain constant core body temperature at ∼37°C. Mammals generate heat internally by thermogenesis. The focus of this review is on heat generated in resting skeletal muscles, using the same cellular components that muscles use to regulate cytoplasmic calcium concentrations [Ca2+] and contraction. Key to this process, known as muscle-based nonshivering thermogenesis (MB-NST), are tiny Ca2+ movements and associated ATP turnover coordinated by the plasma membrane, sarcoplasmic reticulum (SR), and the mitochondria. MB-NST has made mammals with gain-of-function SR ryanodine receptor (RyR) variants vulnerable to excessive heat generation that can be potentially lethal, known as malignant hyperthermia. Studies of RyR variants using recently developed techniques have advanced our understanding of MB-NST.
Electrochemical Separation of Pb-Ag-Sb Alloys in the KCl-PbCl2 Melt
Authors: Arkhipov P. A. , Zaikov Yu. P. , Khalimullina Yu. R. , Kholkina A. S. , Arkhipov S. P.
Published: September 2024

Anode dissolution of lead, silver, antimony and liquid lead-bismuth-antimony alloys has been studied by the polarization method depending on the alloy composition in the molten KCl-PbCl2 eutectic. Lead was found to dissolve and to form Pb2+ ions within the whole range of anode current densities in the Pb-Ag-Sb (49.0–28.0-23.0) and Pb-Ag-Sb (11.0-55.0-34.0) melts. The limiting diffusion current of lead dissolution was observed at the anode current density of 0.34 А cm−2 in the Pb-Ag-Sb (5.0-65.0-30.0) alloy. At the anode current densities exceeding these values the antimony dissolution was observed. To define a mechanism of metals electro dissolution, the number of electrons participating in the electrode reactions was calculated. Based on the polarization curves analysis the regime of electrochemical separation of lead alloys was selected. Metallic lead and the remaining Ag-Sb-Pb alloy with the valuable components concentration exceeding 90 wt% were obtained in the laboratory-scale electrolytic cell.
A New Translation Operator by Covariant Derivative in the Generalized Space
Authors: Jafari Matehkolaee Mehdi , Noshad Houshyar
Published: September 2024

In this paper, we substituted the ordinary derivative with the covariant derivative in simple translation, that is built by applying the ordinary derivative and we investigate the new display of the simple translation. We have introduced a new translation operator in which its generator is exactly covariant derivative. To know the translation of a quantum particle around a space where the effect of gravity is significant, such as a black hole, it is enough to put the metric of that space in the translation derived in this paper.
Global Prevalence of Perinatal Depression and Its Determinants Among Rural Women: A Systematic Review and Meta‐Analysis
Authors: Pan Ting , Zeng Yi , Chai Xiaoni , Wen Zhang , Tan Xiangmin , Sun Mei
Published: September 2024

Background: Perinatal depression (PND) in low‐resource areas is a significant concern that imposes a substantial burden on both families and societies. Although many studies have explored rural PND, there is a lack of systematic synthesis of the existing research. This study aimed to estimate the global prevalence of PND among rural women and to summarize its determinants.

Methods: Comprehensively electronic searches were performed across eight English databases. Two reviewers independently assessed the eligibility of the study and extracted the relevant data. Any inconsistencies were resolved through discussion with a third reviewer. Prevalence estimates were calculated using a random‐effects meta‐analysis model. Subgroup analysis, sensitivity analysis, and meta‐regression were employed to examine the source of heterogeneity. In addition, a narrative synthesis of the influence factors reported in the included studies was provided.

Results: The search identified 17,810 studies, of which 86 were included in the analyses. The pooled prevalence of PND in rural areas was 22.1% (95% CI 19.0%–25.3%, p < 0.001, I2 = 99.2%). Subgroup analyses indicated higher PND prevalence in low‐income (24.5%) and lower middle‐income countries (22.8%). Additionally, PND prevalence was greater when assessed using self‐reported screening instruments (22.8%) compared to diagnostic interviews (17.6%). Major risk factors included violence, antenatal psychiatric disorder, low family income, male‐child preference, and food insecurity, while positive social support and higher levels of education were protective factors.

Conclusions: Our findings suggest that the prevalence of PND is higher in rural areas compared to global data, particularly in low‐income and lower middle‐income countries. To improve rural maternal mental health, it is essential to develop measures targeting modifiable risk factors for PND, including promoting gender equality, implementing antiviolence initiatives, and strengthening economic support systems. Addressing these factors can help reduce the burden of PND and enhance the well‐being of mothers in rural communities.
Machine Learning–Enhanced Microseismic Analysis for Evaluating Rock Crack Trajectory
Authors: Feng Xinglong , Chen Zeng , Li Zhengrong , Zeng Qingtian , Wang Jing , Wang Ping
Published: September 2024

Microseismic (MS) monitoring is an effective method for tracking the development of rock fractures. However, the utilization of existing data is severely limited by current visualization techniques. In this study, the evolution characteristics of MS parameters during the rock fracture process were investigated using MS localization techniques and spatial clustering methods. Machine learning methods were applied to cluster acoustic emission events, enabling the automatic identification of hazardous regions and the construction of crack propagation trajectories. The applicability of clustering methods was assessed using MS monitoring data collected during an in situ rock fracture process. The research results show that the spatial clustering method can effectively delineate hazardous areas, and the changes in these regions reflect the progressive development of rock mass fractures. Regions with a higher proportion of high‐energy MS events pose greater risks. Additionally, the propagation trajectory of MS events can effectively characterize the concentration and development direction of fractures. This study provides valuable insights into the characterization of crack evolution and seepage channels.
Comparative Analysis of Vanilla CNN and Transfer Learning Models for Glaucoma Detection
Authors: Ubochi Brendan , Olawumi Abayomi E. , Macaulay John , Ayomide Oyawoye I. , Akingbade Kayode F.
Published: September 2024

Glaucoma is a leading cause of blindness worldwide and results from high eye pressure‐induced damage to the optic nerves, thereby preventing visual information from reaching the brain. While glaucoma is incurable in its advanced stages, its early detection improves the treatment outcome. Recently, computational models for image classification have enabled early detection of glaucoma from OCT scans of patients and will potentially augment the medical diagnosis of this disease. Models that are based on the convolutional neural networks (CNNs) have shown promise in the early detection of glaucoma. These models vary in their architectures and their accuracies depend largely on the intrinsic nature of the training datasets used. Hence, in this work, a comparative analysis is performed on vanilla CNN, AlexNet, GoogLeNet, and ResNet50 using two popular glaucoma datasets (ACRIMA and ORIGA). With careful attention to exhaustive image processing, an impressive training accuracy of 89% and validation accuracy of 50% was obtained from the vanilla CNN, showing a high sensitivity of 88% in detecting glaucomatous patients from OCT scans. However, the other models (AlexNet, GoogLeNet, and ResNet5) overfitted with a large difference between the obtained training accuracy and validation accuracy. The results also reveal that ResNet50 has the highest computational cost compared to the rest of the models. The obtained results demonstrate the peculiarity of the dataset, its selectiveness of the most appropriate model, and the potential of deep neural networks (DNNs) as an effective screening tool for glaucoma, enabling prompt interventions, reducing healthcare costs, and helping optometrists make swift decisions.
Enhancing Radiation Shielding with Gadolinium(III) Oxide in Cerium(III) Fluoride‐Doped Silica Borate Glass
Authors: Almousa N. , Nabil Islam M. , Issa Shams A. M. , Zakaly Hesham M. H.
Published: September 2024

This study investigates the radiation shielding properties of glass samples within the xGd2O3‐5SiO2‐40Na2O‐(54.5‐x) B2O3:0.5CeF3 composition, where x varies from 0 to 10 mol.%, which is coded as GSNBCX (X = 1, 2, 3, and 4). The assessment is done through comprehensive Monte Carlo simulation and Phy‐X/PSD software analyses. The primary objective of this study is to comprehensively evaluate the radiation shielding properties of glass compositions with varying Gd2O3 concentrations. This evaluation encompasses both the attenuation of gamma radiation within the broad energy range of 0.015 MeV to 15 MeV and the assessment of fast neutron removal cross sections, with a specific focus on simulations spanning energy levels from 0.5 to 10 MeV. By examining these parameters, we aim to elucidate the impact of Gd2O3 concentration on the material’s overall effectiveness in radiation shielding applications. The results reveal a significant variation in the mass attenuation coefficient (μm) across the investigated glass samples. For instance, μm values range from 3.244 to 0.019 cm2·g−1 for GSNBC1, 20.471 to 0.025 cm2·g−1 for GSNBC2, 27.245 to 0.027 cm2·g−1 for GSNBC3, and 32.223 to 0.029 cm2·g−1 for GSNBC4. Notably, GSNBC4, characterized by a substantial Gd2O3 concentration (10 mol.%), exhibits the highest values of both μm and linear attenuation coefficient (μ). Furthermore, the investigation delves into the fast neutron removal cross section (FNRCS), which displays values of 0.97, 0.95, 0.094, and 0.93 cm−1, respectively. GSNBC1, marked by its elevated B2O3 content (54.5 mol.%), showcases the highest FNRCS. These findings underscore the efficacy of Gd2O3‐doped materials in shielding against gamma rays, holding promise for various applications in radiation protection, particularly in the medical and nuclear sectors. This study contributes valuable insights into developing effective radiation‐blocking materials for diverse industrial and scientific contexts.
Advanced Human Papillomavirus–Negative Head and Neck Squamous Cell Carcinoma: Unmet Need and Emerging Therapies
Authors: Park Robin , Chung Christine H.
Published: September 2024

Despite notable progress in the treatment of advanced head and neck squamous cell carcinoma (HNSCC), survival remains poor in patients with recurrent and/or metastatic (R/M) human papillomavirus (HPV)–negative HNSCC. Worse outcomes in patients who are HPV-negative may be partly related to loss of cell-cycle regulators and tumor suppressors as well as a noninflamed and hypoxic tumor microenvironment, both of which contribute to treatment resistance and disease progression. Anti–programmed cell death protein 1–based regimens as current standard-of-care treatment for R/M HNSCC are associated with durable responses in a limited number of patients. The anti-EGFR mAb, cetuximab, has antitumor activity in this treatment setting, but responses are short-lived and inevitably curtailed due to treatment resistance. Crosstalk between the EGFR and hepatocyte growth factor–dependent mesenchymal–epithelial transition (c-MET) receptor tyrosine kinase pathway is a known mechanism of resistance to cetuximab. Dual targeting of EGFR and c-MET pathways may overcome resistance to cetuximab in patients with HPV-negative HNSCC. Here, we review clinical data of treatments evaluated in patients with R/M HPV-negative HNSCC and highlight the potential role of combining hepatocyte growth factor/c-MET and EGFR pathway inhibitors to overcome cetuximab resistance in this population.
Data from NCI’s Proteomic Data Commons: A Cloud-Based Proteomics Repository Empowering Comprehensive Cancer Analysis through Cross-Referencing with Genomic and Imaging Data
Authors: Thangudu Ratna R. , Holck Michael , Singhal Deepak , Pilozzi Alexander , Edwards Nathan , Rudnick Paul A. , Domagalski Marcin J. , Chilappagari Padmini , Ma Lei , Xin Yi , Le Toan , Nyce Kristen , Chaudhary Rekha , Ketchum Karen A. , Maurais Aaron , Connolly Brian , Riffle Michael , Chambers Matthew C. , MacLean Brendan , MacCoss Michael J. , McGarvey Peter B. , Basu Anand , Otridge John , Casas-Silva Esmeralda , Venkatachari Sudha , Rodriguez Henry , Zhang Xu
Published: September 2024

Abstract
Proteomics has emerged as a powerful tool for studying cancer biology, developing diagnostics, and therapies. With the continuous improvement and widespread availability of high-throughput proteomic technologies, the generation of large-scale proteomic data has become more common in cancer research, and there is a growing need for resources that support the sharing and integration of multi-omics datasets. Such datasets require extensive metadata including clinical, biospecimen, and experimental and workflow annotations that are crucial for data interpretation and reanalysis. The need to integrate, analyze, and share these data has led to the development of NCI’s Proteomic Data Commons (PDC), accessible at https://pdc.cancer.gov. As a specialized repository within the NCI Cancer Research Data Commons (CRDC), PDC enables researchers to locate and analyze proteomic data from various cancer types and connect with genomic and imaging data available for the same samples in other CRDC nodes. Presently, PDC houses annotated data from more than 160 datasets across 19 cancer types, generated by several large-scale cancer research programs with cohort sizes exceeding 100 samples (tumor and associated normal when available). In this article, we review the current state of PDC in cancer research, discuss the opportunities and challenges associated with data sharing in proteomics, and propose future directions for the resource.
Significance:
The Proteomic Data Commons (PDC) plays a crucial role in advancing cancer research by providing a centralized repository of high-quality cancer proteomic data, enriched with extensive clinical annotations. By integrating and cross-referencing with complementary genomic and imaging data, the PDC facilitates multi-omics analyses, driving comprehensive insights, and accelerating discoveries across various cancer types.