Experiences of healthcare providers and caregivers regarding health system bottlenecks affecting child healthcare service delivery in a rural district: Empirical qualitative study.

AIM: To explore the experiences of nurses and caregivers about the health system bottlenecks to the delivery of child healthcare services in a rural district in Ghana. DESIGN: The study employed a qualitative approach using an exploratory, descriptive design. METHODS: Collection of data was through semi-structured, face-to-face interviews with 26 participants in the Nkwanta South Municipality, Ghana. Audio recordings of interviews were transcribed verbatim and analysed qualitatively. Inductive codes generated were organised into themes and sub-themes. RESULTS: The main health system bottlenecks that emerged were the poor state of in-patient facilities, inadequate basic logistics and persistent shortage of essential medicines needed for child healthcare delivery. CONCLUSIONS: Health system bottlenecks have the tendency to affect the treatment and hospitalisation outcomes of sick children and eventually impact the state of child healthcare negatively. Concerted efforts by government and local authorities to remove these barriers will help to improve child health and child health outcomes. PUBLIC CONTRIBUTION: A total of 26 participants comprising nurses and caregivers, agreed and participated in this study. Interviews with these participants were conducts either in the health facilities or in the communities where they live. Their responses contributed significantly to the content of this article.

Review of the Phonological System of Contemporary Urdu Spoken in Pakistan.

PURPOSE: Urdu is the lingua franca and national language of Pakistan, and is the 10th most-spoken language worldwide with over 230 million speakers. The Urdu phonological system has been examined over the past decades. However, the system has been evolving. This paper aimed to review the available studies investigating various aspects of the Urdu phonological system and to reveal the variations noted among these studies. METHOD: Twenty-one studies examining the phonological system of Urdu were located. The studies were reviewed in terms of consonants, geminates, consonant clusters, vowels, diphthongs, syllable structure, phonotactic constraints, and stress. RESULT: The findings indicated that 38 consonants, 23 vowels, and 15 diphthongs are used in contemporary Urdu. Most consonants exist as geminates word medially. There are six syllable structures. The consonant clusters are constrained to the coda position only, and short vowels cannot exist in the word-final position. Like other syllable-timed languages, stress is not prominent in Urdu. CONCLUSION: Based on this review, a contemporary Urdu phonemic and syllable structure inventory has been proposed. This will serve as a reference for use in further acquisition research and clinical practice.

Autoclaving is at least as effective as gamma irradiation for biotic clearing and intentional microbial recolonization of soil.

Sterilization is commonly used to remove or reduce the biotic constraints of a soil to allow recolonization by soil-dwelling organisms, with autoclaving and gamma irradiation being the most frequently used approaches. Many studies have characterized sterilization impacts on soil physicochemical properties, with gamma irradiation often described as the preferred approach, despite the lower cost and higher scalability of autoclaving. However, few studies have compared how sterilization techniques impact soil recolonization by microorganisms. Here, we compared how two sterilization approaches (autoclaving; gamma irradiation) and soil washing impacted microbial recolonization of soil from a diverse soil inoculum. Sterilization method had little impact on microbial alpha diversity across recolonized soils. For sterile soil regrowth microcosms, species richness and diversity were significantly reduced by autoclaving relative to gamma irradiation, particularly for fungi. There was no impact of sterilization method on bacterial composition in recolonized soils and minimal impact on fungal composition (P = 0.05). Washing soils had a greater impact on microbial composition than sterilization method, and sterile soil regrowth had negligible impacts on microbial recolonization. These data suggest that sterilization method has no clear impact on microbial recolonization, at least across the soils tested, indicating that soil autoclaving is an appropriate and economical approach for biotically clearing soils.IMPORTANCESterilized soils represent soil-like environments that act as a medium to study microbial colonization dynamics in more "natural" settings relative to artificial culturing environments. Soil sterilization is often carried out by gamma irradiation or autoclaving, which both alter soil properties, but gamma irradiation is thought to be the gentler technique. Gamma irradiation can be cost prohibitive and does not scale well for larger experiments. We sought to examine how soil sterilization technique can impact microbial colonization, and additionally looked at the impact of soil washing which is believed to remove soil toxins that inhibit soil recolonization. We found that both gamma-irradiated and autoclaved soils showed similar colonization patterns when reintroducing microorganisms. Soil washing, relative to sterilization technique, had a greater impact on which microorganisms were able to recolonize the soil. When allowing sterilized soils to regrow (i.e., persisting microorganisms), gamma irradiation performed worse, suggesting that gamma irradiation does not biotically clear soils as well as autoclaving. These data suggest that both sterilization techniques are comparable, and that autoclaving may be more effective at biotically clearing soil.

Clinical impact of DVH uncertainties.

Dose-volume histograms (DVH), along with dose and volume metrics, are central to radiotherapy planning. As such, errors have the potential to significantly impact the selection of appropriate treatment plans. Dose distributions that pass tests in one TPS may fail the same tests when transferred to another, even if using identical structures and dose grid information. This work shows the design and implementation of methods for assessing the accuracy of dose and volume computations performed by treatment planning systems (TPS), and other analytical tools. We demonstrate examples where differences in calculations between systems can change the assessment of a plan's clinical acceptability. Our work also provides a more detailed DVH analysis of single targets than earlier published studies. This is relevant for SRS plans and small structure dose assessments. Very small structures are a particular problem because of their coarse digital representation, and the impact of this is thoroughly examined. Reference DVH curves were derived mathematically, based on Gaussian dose distributions centered on spherical structures. The structures and dose distributions were generated synthetically, and imported into RayStation, MasterPlan, and ProKnow. Corresponding DVHs were analytically derived and taken as ground truth references, for comparison with the commercial DVH calculations. Two commonly used dose metrics PCI and MGI were used to determine the limit of calculation accuracy for small structures. In addition, to measure the DVH differences between a larger range of commercial DVH calculators, the D95 metric from a set of real clinical plans was compared across both the 3 DVH calculators under test, and across a further six TPSs from other hospitals. We show that even slight deviations between the results of DVH calculators can lead to plan check failures, and we illustrate this with the commonly used D95 planning metric. We present clinical data across eight planning systems that highlight instances where plan checks would pass in one software and fail in another due to DVH calculation differences. For the smallest volumes tested, errors of up to 20% were observed in the DVHs. RayStation was tested down to a 3 mm radius sphere (≈0.1 cc) and this showed close to 10% error, reducing to 1% for 10 mm radius (≈4.0 cc) and 0.1% for 20 mm radius (≈33 cc). In clinical plans, the variation in D95 was up to 9% for the smallest volumes, and typically around 2% in the range 0.5 cc-20 cc, and 1% in 20 cc-70 cc, falling to <0.1% for large volumes. Paddick Conformity Index (PCI) and Modified Gradient Index (MGI) are commonly used plan quality indicators for very small volumes. For volumes ≈0.1 cc we observed errors of up to 40% in PCI, and up to 75% in MGI. Our study extends the range of tested DVH calculators in published work, and shows their performance over a wider range of volume sizes. We provide quantitative evidence of the critical need to test the accuracy of DVH calculators in the TPS before clinical use. This work is particularly relevant for both stereotactic plan evaluation and for assessment of small volume doses in published dose constraint recommendations. We demonstrate that significant errors can occur in DVHs for volumes less than 1 cc, even if the volumes themselves are calculated accurately. Even for large structures, deviations between the outputs of DVH calculators can lead to indicated or reported plan check failures if they do not include appropriate tolerances. We urge caution in the use of DVH metrics for these very small volumes and recommend that appropriate DVH uncertainty tolerances are set in organ dose constraints when using them to evaluate clinical plans.

Inequality and health: Can medical practice address the consequences of inequalities?

BACKGROUND: The extent to which governments provide socioeconomic supports has been highlighted by their spending during the COVID-19 pandemic. This has implications for patterns of inequality, in particular on exacerbating unequal health and well-being. RESULTS: Inequity has expanded due to neoliberalism, a market-based approach that has endured for more than four decades. Together with COVID-19, it has developed and exposed many structural governance differences. DISCUSSION: There are a number of examples presented of the effects of inequalities on health and well-being. The role of general practice in addressing these is discussed and challenges are highlighted, especially those relating to payment systems and workforce constraints.

A Review on Camel Milk Composition, Techno-Functional Properties and Processing Constraints.

Camel milk plays a critical role in the diet of peoples belongs to the semi-arid and arid regions. Since prehistoric times, camel milk marketing was limited due to lacking the processing facilities in the camel-rearing areas, nomads practiced the self-consumption of raw and fermented camel milk. A better understanding of the techno-functional properties of camel milk is required for product improvement to address market and customer needs. Despite the superior nutraceutical and health promoting potential, limited camel dairy products are available compared to other bovines. It is a challenging impetus for the dairy industry to provide diversified camel dairy products to consumers with superior nutritional and functional qualities. The physicochemical behavior and characteristics of camel milk is different than the bovine milk, which poses processing and technological challenges. Traditionally camel milk is only processed into various fermented and non-fermented products; however, the production of commercially important dairy products (cheese, butter, yogurt, and milk powder) from camel milk still needs to be processed successfully. Therefore, the industrial processing and transformation of camel milk into various products, including fermented dairy products, pasteurized milk, milk powder, cheese, and other products, require the development of new technologies based on applied research. This review highlights camel milk's processing constraints and techno-functional properties while presenting the challenges associated with processing the milk into various dairy products. Future research directions to improve product quality have also been discussed.

Alleviating tiling effect by random walk sliding window in high-resolution histological whole slide image synthesis.

Multiplex immunofluorescence (MxIF) is an advanced molecular imaging technique that can simultaneously provide biologists with multiple (i.e., more than 20) molecular markers on a single histological tissue section. Unfortunately, due to imaging restrictions, the more routinely used hematoxylin and eosin (H&E) stain is typically unavailable with MxIF on the same tissue section. As biological H&E staining is not feasible, previous efforts have been made to obtain H&E whole slide image (WSI) from MxIF via deep learning empowered virtual staining. However, the tiling effect is a long-lasting problem in high-resolution WSI-wise synthesis. The MxIF to H&E synthesis is no exception. Limited by computational resources, the cross-stain image synthesis is typically performed at the patch-level. Thus, discontinuous intensities might be visually identified along with the patch boundaries assembling all individual patches back to a WSI. In this work, we propose a deep learning based unpaired high-resolution image synthesis method to obtain virtual H&E WSIs from MxIF WSIs (each with 27 markers/stains) with reduced tiling effects. Briefly, we first extend the CycleGAN framework by adding simultaneous nuclei and mucin segmentation supervision as spatial constraints. Then, we introduce a random walk sliding window shifting strategy during the optimized inference stage, to alleviate the tiling effects. The validation results show that our spatially constrained synthesis method achieves a 56% performance gain for the downstream cell segmentation task. The proposed inference method reduces the tiling effects by using 50% fewer computation resources without compromising performance. The proposed random sliding window inference method is a plug-and-play module, which can be generalized for other high-resolution WSI image synthesis applications. The source code with our proposed model are available at https://github.com/MASILab/RandomWalkSlidingWindow.git.

Maximum Likelihood Estimation for Unrooted 3-Leaf Trees: An Analytic Solution for the CFN Model.

Maximum likelihood estimation is among the most widely-used methods for inferring phylogenetic trees from sequence data. This paper solves the problem of computing solutions to the maximum likelihood problem for 3-leaf trees under the 2-state symmetric mutation model (CFN model). Our main result is a closed-form solution to the maximum likelihood problem for unrooted 3-leaf trees, given generic data; this result characterizes all of the ways that a maximum likelihood estimate can fail to exist for generic data and provides theoretical validation for predictions made in Parks and Goldman (Syst Biol 63(5):798-811, 2014). Our proof makes use of both classical tools for studying group-based phylogenetic models such as Hadamard conjugation and reparameterization in terms of Fourier coordinates, as well as more recent results concerning the semi-algebraic constraints of the CFN model. To be able to put these into practice, we also give a complete characterization to test genericity.

Discontinuous Deformation Monitoring of Smart Aerospace Structures Based on Hybrid Reconstruction Strategy and Fiber Bragg Grating.

A hybrid enhanced inverse finite element method (E-iFEM) is proposed for real-time intelligent sensing of discontinuous aerospace structures. The method can improve the flight performance of intelligent aircrafts by feeding back the structural shape information to the control system. Initially, the presented algorithm combines rigid kinematics with the classical iFEM to discretize the aerospace structures into elastic parts and rigid parts, which will effectively overcome structural complexity due to fluctuating bending stiffness and a special aerodynamic section. Subsequently, the rigid parts provide geometric constraints for the iFEM in the shape reconstruction method. Meanwhile, utilizing the Fiber Bragg grating (FBG) strain sensor to obtain real-time strain information ensures lightweight and anti-interference of the monitoring system. Next, the strain data and the geometric constraints are processed by the iFEM for monitoring the full-field elastic deformation of the aerospace structures. The whole procedure can be interpreted as a piecewise sensing technology. Overall, the effectiveness and reliability of the proposed method are validated by employing a comprehensive numerical simulation and experiment.

Full prescribed performance trajectory tracking control strategy of autonomous underwater vehicle with disturbance observer.

This paper investigates trajectory tracking control of the Autonomous Underwater Vehicle (AUV) with the general uncertainty consisting of model uncertainties and unknown ocean current disturbances. A full prescribed performance control strategy based on disturbance observer is developed, which ensures that the tracking error, the velocity error, and the observation error are all constrained. First, under the case of unmeasurable AUV acceleration, a fixed-time observer is constructed to estimate the general uncertainty, which constrains the observation error within the prescribed accuracy by a prescribed performance observer. Then, based on the performance function and corresponding error transformation, a prescribed performance protocol is designed to realize the trajectory tracking control, so that the observation error, the tracking error, and the velocity error are all constrained within the prescribed accuracy range. Simulation results demonstrate the efficiency of the full prescribed performance control strategy while the AUV tracking control with full state constraints is feasible. Moreover, compared with the other two relevant works, this study improves the observation performance by at least 10 %, both in case of deepwater disturbances and near-surface disturbances.

Locomotor and Physiological Demands of Small-Sided Soccer Games in Wildcard and Regular Players: Effects of Goalkeepers and Type of Wildcard.

BACKGROUND: Small-sided games (SSGs) are frequent training drills in soccer. This study investigated whether type of game (ie, with/without goalkeepers) and wildcard ( without vs internal vs external wildcard) impact the physiological (heartrate [HR]) and locomotor (total distance [TD] covered) demands in regular and wildcard players and to evaluate between-player and within-player variability. HYPOTHESIS: Demands are influenced by wildcard and game type, with higher demand (distance covered at high intensities and sprint speed) in regular players and with higher variability in SSG with wildcard players. STUDY DESIGN: Descriptive/comparative study. LEVEL OF EVIDENCE: Level 4. METHODS: Twenty-four soccer players completed 6 SSG as 3 versus 3 without (NG) or with (GK) goalkeepers, and with internal (NG+IW and GK+IW) and external (NG+EW and GK+EW) wildcard. Average HR (HRavg), rate of perceived exertion, and locomotor demands (TD, medium [MID = 7.0-13.9 km h-1], high [HID = 14.0-20.9 km h-1] and sprint [SPD >21.0 km h-1] distance and peak speed [PS]) were registered. RESULTS: The inclusion of GK and internal wildcard led to decreased HRavg and TD in regular players. Wildcard players positioned internally exhibited higher TD, PS, and lower HRavg than externally positioned wildcards. Regular players demonstrated higher TD, PS, MID, HID, HRavg and time spent in Z3 (>90% HRmax) compared with wildcard players in SSG played with external wildcard. Regular and wildcard players displayed great between- and within-player variability in high-intensity metrics. CONCLUSION: Specific game type and wildcard inclusion impact the physiological and locomotor demands in SSG, with variations observed between regular and wildcard players. CLINICAL RELEVANCE: This study provides comprehensive information on the physiological and locomotor demands of SSG depending on the inclusion and position of goalkeepers and wildcards, which can be useful for strength and conditioning coaches when designing specific training tasks, individualizing training load and applying return-to-play programs.

A generalized Udwadia-Kalaba control design for uncertain belt conveyor systems with inequality constraints.

Uncertainty can lead to jitter or overshoot in mechanical systems, necessitating the design of multiple constraints to stabilize them. This paper proposes a control structure based on the generalized Udwadia-Kalaba equation to address these constraints simultaneously. An uncertain dynamical model is developed, incorporating both equality and inequality constraints. By integrating diffeomorphism theory, a robust control strategy is designed to ensure compliance with these constraints. Utilizing the Lyapunov approach, the uniform boundedness and uniform ultimate boundedness of the dynamical system are demonstrated. Finally, the feasibility of the proposed control method is validated through its application to a belt conveyor system.

Response to von Schmalensee et al.

Von Schmalensee et al. present two concerns about our study. While the first stems from a general disagreement about our simulation methodology, the second is a useful observation of a modelling choice we made that affected simulation outcomes, but in ways that do not invalidate our original conclusions.

A developmental constraint model of cancer cell states and tumor heterogeneity.

Cancer is a disease that stems from a fundamental liability inherent to multicellular life forms in which an individual cell is capable of reneging on the interests of the collective organism. Although cancer is commonly described as an evolutionary process, a less appreciated aspect of tumorigenesis may be the constraints imposed by the organism's developmental programs. Recent work from single-cell transcriptomic analyses across a range of cancer types has revealed the recurrence, plasticity, and co-option of distinct cellular states among cancer cell populations. Here, we note that across diverse cancer types, the observed cell states are proximate within the developmental hierarchy of the cell of origin. We thus posit a model by which cancer cell states are directly constrained by the organism's "developmental map." According to this model, a population of cancer cells traverses the developmental map, thereby generating a heterogeneous set of states whose interactions underpin emergent tumor behavior.

How does green finance impact carbon emissions in China: Evidence from the fintech perspective.

In light of China's objectives for carbon peak and carbon neutrality, there is an opportunity for fintech to leverage its technological advantages and enhance its integration with green finance (GF). This can bring about enhanced coverage and precision of financial services for green industries, facilitating the transformation towards a sustainable, greener, and low-carbon real economy. We investigate how fintech development influences the carbon emission reduction effects of GF utilizing a two-way fixed effects model with a panel dataset covering 30 provinces in China from 2011 to 2020. Our findings indicate that the negative impact of GF on carbon emissions (CE) is heightened in areas with high levels of fintech development. Furthermore, we notice regional disparities in how fintech development impacts the effectiveness of GF in reducing CE. Specifically, fintech has a statistically significant impact in the central and western regions, whereas its significance is absent in the eastern region. Lastly, our mechanism analysis reveals that fintech plays a vital role in enhancing GF's capacity to mitigate CE, which is achieved through channels of promoting green technology innovation (GTI), alleviating corporate financing constraints (FC), and optimizing energy structure (ES). These findings provide compelling evidence for the positive effect of fintech on the environment and offer justification for promoting the development of fintech and GF.

Using theoretical constraints and the TASI taxonomy to delineate predictably replicable findings.

The focus of the present article is not on failures to replicate but on the more optimistically framed and more fruitful question: What stable findings can be reproduced reliably and can be trusted by decision makers, managers, health agents, or politicians? We propagate the working hypothesis that a twofold key to stable and replicable findings lies in the existence of theoretical constraints and, no less important, in researchers' sensitivity to metatheoretical, auxiliary assumptions. We introduce a hierarchy of four levels of theoretical constraints-a priori principles, psychophysical, empirical, and modelling constraints-combined with the TASI taxonomy of theoretical, auxiliary, statistical, and inferential assumptions Trafimow, Journal for the Theory of Social Behaviour, 52, 37-48, (2022). Although theoretical constraints clearly facilitate stable and replicable research findings, TASI reminds us of various reasons why even perfectly valid hypotheses need not always be borne out. The presented framework should help researchers to operationalize conditions under which theoretical constraints render empirical findings most predictable.

Exploring the Effects of Instruction and Game Design on Youth Soccer Players' Skill Involvement and Cooperative Team Behaviour.

Objectives: The relationship between task constraints and player behaviors is of interest to coaches tasked with designing practice to optimize learning. This study aims to compare the skill involvements and cooperative team behavior of teams of youth soccer players engaged in a goal exaggeration and/or a prescriptive coach instruction condition compared to a free-play control condition. Methods: Twenty male soccer players aged 12-15 participated in small-sided games under four conditions: free-play, goal exaggeration, prescriptive coach instruction, and combination over four weeks. Using video footage, teams' collective skill involvements (shot, pass, dribble) and passing network characteristics (closeness, density, and betweenness) were measured for each game. Results: A Friedmans rank test identified that playing conditions resulted in significant differences in attempted dribbles (p < .001), goals scored (p < .001), network density (p = .001), closeness (p < .001) and betweenness (p = .002). Teams attempted to dribble the most in the free-play and goal-exaggeration conditions, and the most goals were scored in the goal-exaggeration and combination conditions. Additionally, teams exhibited more well-connected passing networks (i.e. higher density, higher closeness, and lower betweenness values) in the combination condition and higher network density in the explicit instruction condition. Conclusions: The results of this study indicate that coach instruction may be more associated with cooperative team behavior, whereas free-play or manipulating task constraints in the absence of instruction may be associated with players attempting more individual actions.

Digital transformation and environmental, social, and governance greenwashing: Evidence from China.

This paper examines the relationship between digital transformation(DT) and environmental, social, and governance(ESG) greenwashing using Chinese listed companies as a sample from 2012 to 2022. Furthermore, it analyzes the enterprise and regional heterogeneity as well as the influencing mechanisms on this relationship. The research results indicate that corporate digital transformation significantly inhibits ESG greenwashing, with a more pronounced effect on companies in non-high-pollution industries, high-tech industries, and the eastern region. In addition, mechanism tests reveal that internal control and financing constraints play a partial mediating role. Digital transformation suppresses ESG greenwashing by enhancing the quality of internal control and alleviating financing constraints. The primary contribution of this paper lies in demonstrating that digital transformation can serve as a strategic tool to mitigate ESG greenwashing. This enriches the research on the outcomes of digital transformation as well as the factors influencing ESG greenwashing. The conclusions of this paper provide theoretical foundations and policy recommendations for better ESG development by enterprises and governments in emerging markets. At the same time, this paper has a certain guiding role for the introduction and implementation of policies to encourage digital transformation.

Physical constraints during Snowball Earth drive the evolution of multicellularity.

Molecular and fossil evidence suggests that complex eukaryotic multicellularity evolved during the late Neoproterozoic era, coincident with Snowball Earth glaciations, where ice sheets covered most of the globe. During this period, environmental conditions-such as seawater temperature and the availability of photosynthetically active light in the oceans-likely changed dramatically. Such changes would have had significant effects on both resource availability and optimal phenotypes. Here, we construct and apply mechanistic models to explore (i) how environmental changes during Snowball Earth and biophysical constraints generated selective pressures, and (ii) how these pressures may have had differential effects on organisms with different forms of biological organization. By testing a series of alternative-and commonly debated-hypotheses, we demonstrate how multicellularity was likely acquired differently in eukaryotes and prokaryotes owing to selective differences on their size due to the biophysical and metabolic regimes they inhabit: decreasing temperatures and resource availability instigated by the onset of glaciations generated selective pressures towards smaller sizes in organisms in the diffusive regime and towards larger sizes in motile heterotrophs. These results suggest that changing environmental conditions during Snowball Earth glaciations gave multicellular eukaryotes an evolutionary advantage, paving the way for the complex multicellular lineages that followed.

Entropy and the Limits to Growth.

In its business-as-usual scenario, the 1972 Club-of-Rome report-The Limits to Growth-describes the collapse of the world economy around the year 2030, either because of the scarcity of natural resources or because of pollution. Mainstream economists, the high priests of secular societies, condemned it fiercely. Their gospel of perpetual economic growth, during which technological progress would solve all problems, promises a bright future for all mankind. On the other hand, engineers, natural scientists, and mathematicians realized that the breakdown scenario is due to the inclusion of the First and the Second Law of Thermodynamics in the Club-of-Rome's world model. According to these laws, nothing happens in the world without energy conversion and entropy production. In 1865, Rudolph Clausius, the discoverer of entropy, published the laws as the constitution of the universe. Entropy is the physical measure of disorder. Without a proper understanding of energy and entropy in the economy, all efforts to achieve sustainability will fail.