bluuebunny/crossref_metadata_2025 huggingface dataset:
Modification and Validation of an Autism Observational Assessment Including ADOS-2® for Use with Children with Visual Impairment
Authors: Dale Naomi , Sakkalou Elena , Eriksson Maria H. , Salt Alison
Published: September 2024

Children with visual impairment (VI) are at risk of autism spectrum disorder (ASD); however standard observational diagnostic assessments are not validated for this population. The primary objective of the study is to validate a modified version of the Autism Diagnostic Observation Schedule (ADOS-2®, Module 3), for children with VI. A cross-sectional observational study was undertaken with 100 (mean 5½ years, SD 10.44 months, range 4–7 years; 59 (59%) males) children with congenital disorders of the peripheral visual system with moderate/severe-profound VI. As the primary objective, 83 (83%) who were ‘verbally fluent’ were assessed with the modified ADOS-2® (Module 3). Their scores were investigated for reliability, construct and criterion validity against expert clinician formulation and parent-rated social and communication questionnaires (Social Responsiveness Scale-2, SRS-2; Children’s Communication Checklist-2). The secondary objective with the total sample was to report on frequency and distribution of ASD ratings in this VI population. The modified ADOS-2® (Module 3) was found to have strong internal coherence and construct validity (two factor model) and inter-rater reliability. A new VI diagnostic algorithm was established which showed high sensitivity and specificity against clinician formulation. Using the best cut-off threshold for ‘High Risk for ASD’, strong concurrent criterion validity was found according to parent-rated scores on the SRS-2. The modified ADOS-2® (Module 3) was shown to have promising reliability and validity in establishing children at ‘High Risk of ASD’ in this vulnerable population. Elevated rates of ASD were found across the sample, in line with previous estimates.
Short-term and Long-term Stability of the Autism Diagnostic Observation Schedule (ADOS-2) Calibrated Comparison Scores (CCS) and Classification Scores in Youth with Down Syndrome or Fragile X Syndrome with Intellectual Disability
Authors: Thurman Angela John , Nunnally Amanda Dimachkie , Nguyen Vivian , Berry-Kravis Elizabeth , Sterling Audra , Edgin Jamie , Hamilton Debra , Aschkenasy Jeannie , Abbeduto Leonard
Published: September 2024

Autism diagnosis in individuals with fragile X syndrome (FXS) or Down syndrome (DS) with co-occurring intellectual disability is complex since clinicians often must consider other co-occurring behavioral features. Understanding how best to assess the features of autism in individuals with these conditions is crucial. In this study, we consider the short-term and long-term psychometric consistency of the Autism Diagnostic Observation Schedule-2 (ADOS-2) calibrated comparison scores (CCSs) and ASD classifications in individuals with FXS or DS. 76 individuals with DS (39 males; Mage = 15.27) and 90 individuals with FXS (71 males; Mage = 14.52 years) completed an assessment battery (ADOS-2, abbreviated IQ assessment and semi-structured language sample) at three timepoints (initial visit, short-term stability visit, long-term stability visit). All CCSs were found to have short-and long-term consistency for both groups, with lowest reliability scores for the repetitive behaviors (RRB) CCSs. Decreased reliability of RRB CCSs was found in the DS group than the FXS group. Variable short- and long-term ASD classifications were observed in both groups, with significantly higher variability in the DS group. Across groups, participants with variable classifications had lower ADOS-2 CCSs and higher language scores than those with stable ASD classifications. In the FXS group, those with variable classifications earned higher cognitive scores than did participants with stable ASD classifications. These findings highlight the high incidence of autism symptomatology in individuals with DS or FXS and co-occurring intellectual disability, while elucidating the short- and long-term variability of symptom expression in the context of structured observational tasks such as the ADOS-2.
Impact of Pd2+ and Sn4+ co-doping ZnO nanoflakes toward high-performing Schottky diode based on the generation of intermediate bands within the energy gap
Authors: Elgazzar Elsayed
Published: September 2024

Pd:Sn/ZnO nanohybrid was prepared by chemical co-precipitation route and identified using XRD, EDX, SEM, and TEM techniques. The microstructure analysis emphasized the polycrystalline nature in which Pd and Sn ions were substituted inside ZnO framework to form the nanocomposite. The surface morphology was appeared in 2D nanoflakes with large specific surface area. The optical parameters including Eg, n, and k were deduced from T% and R% spectra through wavelength range 300–1400 nm. The thin film showed strong optical absorption inside the UV region with a value of Eg = 3.10 eV. The Ag/Pd:Sn/ZnO/p-Si/Al Schottky diode was fabricated by thermal evaporation technique, and its electronic and photodetector properties were investigated from I–V and C–V measurements. The fabricated device exhibited non-ideal behavior with high rectification ratio RR = 935 and a relatively small Rs lies between 2365 and 2755 Ω. Under illumination impacts, the photodiode exhibited high photosensitivity and responsivity attributed to the large photo-induced charge carriers.
Martensitic transformations and magnetic properties of Ni50−xMn37Sn13Fex(x = 0.5, 1, 1.5) melt-spun ribbons
Authors: Younsi W. , Louidi S. , Suñol J. J. , Bouaine A. , Daza J.
Published: September 2024

The present study investigates the influence of iron (Fe) doping on the martensitic transformation and magnetic properties of Ni50−xMn37Sn13Fex(x = 0.5, 1, 1.5) magnetic shape memory alloys in ribbon form. The ribbons were prepared using arc-melting followed by melt-spinning processes and were characterized using X-ray diffraction, scanning electron microscopy, differential scanning calorimetry, and vibrating sample magnetometry. Our findings demonstrate that the addition of Fe shifts the martensitic transformation to lower temperatures and increases the Curie point of the austenitic phase, $$T_{c}^{\text A}$$

T

c

A

, leading to an enhanced magnetism in the austenitic phase. Moreover, a significant increase in the magnetization jump $$(\Delta M)$$

(
Δ
M
)

is observed, from $$ 3.3\;{\text{emu\ g}}^{-1} $$

3.3

emu\ g

-
1

for $$x=1$$

x
=
1

to $$17 \, {\text{emu\ g}}^{-1} $$

17

emu\ g

-
1

for $$x=1.5$$

x
=
1.5

under a $$50 \, \text {Oe}$$

50

Oe

applied magnetic field. The structural transformations are also found to be sensitive to the external applied magnetic field. The isothermal magnetization curves exhibit the exchange bias effect, which confirms the coexistence of antiferromagnetic and ferromagnetic coupling in the samples. Furthermore, the exchange bias effect increases with the Fe content.
Between Delivery and Luck: Projectification of Academic Careers and Conflicting Notions of Worth at the Postdoc Level
Authors: Nästesjö Jonatan
Published: September 2024

This paper investigates how early career academics interpret and respond to institutional demands structured by projectification. Developing a ‘frame analytic’ approach, it explores projectification as a process constituted at the level of meaning-making. Building on 35 in-depth interviews with fixed-term scholars in political science and history, the findings show that respondents jointly referred to competition and delivery in order to make sense of their current situation. Forming what I call the project frame, these interpretive orientations were legitimized by various organizational routines within the studied departments, feeding into a dominant regime of valuation and accumulation. However, while the content of the project frame is well-defined, attempts to align with it vary, indicating the importance of disciplines and academic age when navigating project-based careers. Furthermore, this way of framing academic work and careers provokes tensions and conflicts that junior scholars try to manage. To curb their competitive relationship and enable cooperation, respondents emphasized the outcome of project funding as ‘being lucky.’ They also drew on imagined futures to envision alternative scripts of success and worth. Both empirically and conceptually, the article contributes to an understanding of academic career-making as a kind of pragmatic problem-solving, centered on navigating multiple career pressures and individual aspirations.
Efficient compressed storage and fast reconstruction of large binary images using chain codes
Authors: Strnad Damjan , Žlaus Danijel , Nerat Andrej , Žalik Borut
Published: September 2024

Large binary images are used in many modern applications of image processing. For instance, they serve as inputs or target masks for training machine learning (ML) models in computer vision and image segmentation. Storing large binary images in limited memory and loading them repeatedly on demand, which is common in ML, calls for efficient image encoding and decoding mechanisms. In the paper, we propose an encoding scheme for efficient compressed storage of large binary images based on chain codes, and introduce a new single-pass algorithm for fast parallel reconstruction of raster images from the encoded representation. We use three large real-life binary masks to test the efficiency of the proposed method, which were derived from vector layers of single-class objects – a building cadaster, a woody vegetation landscape feature map, and a road network map. We show that the masks encoded by the proposed method require significantly less storage space than standard lossless compression formats. We further compared the proposed method for mask reconstruction from chain codes with a recent state-of-the-art algorithm, and achieved between $$12\%$$

12
%

and $$33\%$$

33
%

faster reconstruction on test data.
Distance Enhanced Hypergraph Learning for Dynamic Node Classification
Authors: Liu Dengfeng , Pan Zhiqiang , Hu Shengze , Cai Fei
Published: September 2024

Dynamic node classification aims to predict the labels of nodes in the dynamic networks. Existing methods primarily utilize the graph neural networks to acquire the node features and original graph structure features. However, these approaches ignore the high-order relationships between nodes and may lead to the over-smoothing issue. To address these issues, we propose a distance enhanced hypergraph learning (DEHL) method for dynamic node classification. Specifically, we first propose a time-adaptive pre-training component to generate the time-aware representations of each node. Then we utilize a dual-channel convolution module to construct the local and global hypergraphs which contain the corresponding local and global high-order relationships. Moreover, we adopt the K-nearest neighbor algorithm to construct the global hypergraph in the embedding space. After that, we adopt the node convolution and hyperedge convolution to aggregate the features of neighbors on the hypergraphs to the target node. Finally, we combine the temporal representations and the distance enhanced representations of the target node to predict its label. In addition, we conduct extensive experiments on two public dynamic graph datasets, i.e., Wikipedia and Reddit. The experimental results show that DEHL outperforms the state-of-the-art baselines in terms of AUC.
Infinitesimal and infinite numbers in applied mathematics
Authors: Bryzgalov Aleksandr , Islami Kevin , Giordano Paolo
Published: September 2024

The need to describe abrupt changes or response of nonlinear systems to impulsive stimuli is ubiquitous in applications. Also the informal use of infinitesimal and infinite quantities is still a method used to construct idealized but tractable models within the famous J. von Neumann reasonably wide area of applicability. We review the theory of generalized smooth functions as a candidate to address both these needs: a rigorous but simple language of infinitesimal and infinite quantities, and the possibility to deal with continuous and generalized function as if they were smooth maps: with pointwise values, free composition and hence nonlinear operations, all the classical theorems of calculus, a good integration theory, and new existence results for differential equations. We exemplify the applications of this theory through several models of singular dynamical systems: deduction of the heat and wave equations extended to generalized functions, a singular variable length pendulum wrapping on a parallelepiped, the oscillation of a pendulum damped by different media, a nonlinear stress–strain model of steel, singular Lagrangians as used in optics, and some examples from quantum mechanics.
The Use of Systemically Absorbed Drugs to Explore An In Vitro Bioequivalence Approach For Comparing Non-Systemically Absorbed Active Pharmaceutical Ingredients in Drug Products For Use in Dogs
Authors: Martinez Marilyn N. , Fahmy Raafat , Li Linge , Herath Kithsiri , Hollenbeck R. Gary , Ibrahim Ahmed , Hoag Stephen W. , Longstaff David , Gao Shasha , Myers Michael J.
Published: September 2024

Purpose

Currently, for veterinary oral formulations containing one or more active pharmaceutical ingredient (API) that are not systemically absorbed and act locally within the gastrointestinal (GI) tract, the use of terminal clinical endpoint bioequivalence (BE) studies is the only option for evaluating product BE. This investigation explored the use of a totality of evidence approach as an alternative to these terminal studies.

Methods

Three formulations of tablets containing ivermectin plus praziquantel were manufactured to exhibit distinctly different in vitro release characteristics. Because these APIs are highly permeable, plasma drug concentrations served as a biomarker of in vivo dissolution. Tablets were administered to 27 healthy Beagle dogs (3-way crossover) and the rate and extent of exposure of each API for each formulation was compared in a pairwise manner. These results were compared to product relative in vitro dissolution profiles in 3 media. In vivo and in vitro BE predictions were compared.

Results

In vivo/in vitro inconsistencies in product relative performance were observed with both compounds when considering product performance across the 3 dissolution media. Formulation comparisons flagged major differences that could explain this outcome.

Conclusions

The finding of an inconsistent in vivo/in vitro relationship confirmed that in vitro dissolution alone cannot assure product BE for veterinary locally acting GI products. However, when combined with a comparison of product composition and manufacturing method, this totality of evidence approach can successfully alert scientists to potential therapeutic inequivalence, thereby supporting FDA’s efforts to Replace, Reduce, and/or Refine terminal animal studies.
Prioritisation of indicators in SDG 4: Voluntary national reviews as a tool of soft governance
Authors: Smith William C. , Susu Adriana , Jackaria Ijaaz , Martinez Johanna Bohorquez , Qu Meihui , Niwa Misaki
Published: September 2024

Voluntary national reviews (VNRs) are an important component of the follow-up and review process for the Sustainable Development Goals (SDGs). Presented by countries at the annual United Nations High-Level Political Forum on Sustainable Development (HLPF), VNRs detail a country’s self-reported progress to peers. This voluntary process has been criticised for its weak accountability. Global governance literature, however, points to an increase in these “soft” governance mechanisms as well as the potential strategic benefits of this approach. Using a mix of logistic regression and document analysis, this study examined VNRs as a soft governance tool and a reflection of the governance mechanism of the SDGs. The authors examined the scope and content of VNR submissions from 2016 to 2022, with a deeper review of 2022, which focused on the global goal for education (SDG 4). Three types of soft governance – governing by goal-setting, by numbers and by morality – were used as lenses to make sense of the results. The authors’ findings demonstrate the ability of soft governance tools to bring together diverse actors around a broad set of goals, and how the power of numbers can influence which indicators countries report on in their VNR.
Project finance or corporate finance for renewable energy? an agent-based insight
Authors: Baldauf Thomas , Jochem Patrick
Published: September 2024

State-of-the-art macroeconomic agent-based models (ABMs) include an increasing level of detail in the energy sector. However, the possible financing mechanisms of renewable energy are rarely considered. In this study, an investment model for power plants is conceptualized, in which energy investors interact in an imperfect and decentralized market network for credits, deposits and project equity. Agents engage in new power plant investments either through a special purpose vehicle in a project finance (PF) structure or via standard corporate finance (CF). The model portrays the growth of new power generation capacity, taking into account technological differences and investment risks associated with the power market. Different scenarios are contrasted to investigate the influence of PF investments on the transition. Further, the effectiveness of a simple green credit easing (GCE) mechanism is discussed. The results show that varying the composition of the PF and CF strategies significantly influences the transition speed. GCE can recover the pace of the transition, even under drastic reductions in PF. The model serves as a foundational framework for more in-depth policy analysis within larger agent-based integrated assessment models.
Real-world analysis on the use of gamma-hydroxybutyric acid for alcohol withdrawal syndrome in hospitalized patients with diagnosis of cirrhosis
Authors: Salomoni Monica , Missanelli Andrea , Crescioli Giada , Lanzi Cecilia , Totti Arianna , Losso Lorenzo , Gitto Stefano , Bonaiuti Roberto , Vannacci Alfredo , Lombardi Niccolò , Mannaioni Guido
Published: September 2024

The present real-world analysis aimed to evaluate and describe the use of gamma-hydroxybutyric acid (GHB) for alcohol withdrawal syndrome (AWS) in hospitalized patients with diagnosis of liver cirrhosis. An 11-year observational retrospective study on patients affected by liver cirrhosis and alcohol use disorder (AUD) was performed using data from the Medical Toxicology Unit of Careggi University Hospital in Florence (Italy). A multivariate logistic regression was performed to estimate the probability of having a CIWA-Ar Max 3–4 during hospitalization, an AWS length  > 36 h, a hospitalization > 9 days, and the probability of developing drowsiness. A total of 166 AUD patients were included, of these 77 received GHB (70.13% within the first day of hospitalization) and 89 were treated without GHB. The majority were  ≥ 40 years of age (87.35%) and males (80.12%). GHB patients were more likely to have a CIWA-Ar Max 3–4 during hospitalization (OR 3.76 [CI 95% 1.02–13.85]), and a longer hospitalization (OR 3.08 [95% CI 1.23–7.71]). Early GHB administration decreased the probability of CIWA-Ar Max worsening (OR 0.06 [95% CI 0.01–0.49]). GHB dose  ≥ 100 mg/kg was not associated with the occurrence of drowsiness. Patients exposed to other sedative agents were more likely to experience drowsiness (OR 7.22 [95% CI 1.46–35.61]). The present real-world analysis underlines that GHB could be a valuable and safe option for the management of AWS in AUD patients affected by liver cirrhosis, also when administered early and even at higher than recommended dosages.
System Design, Modelling, Energy Analysis, and Industrial Applications of Ohmic Heating Technology
Authors: Javed Tasmiyah , Oluwole-ojo Oluwaloba , Zhang Hongwei , Akmal Muhammad , Breikin Timofei , O’Brien Alexander
Published: September 2024

The food and drink industry is gradually gaining sustainability pressure due to the high carbon emissions rate and limited availability of traditional energy supplies. Thus, it is essential to consider energy efficiency and decarbonisation of the ever-expanding food and drink industry. Ohmic heating technology is a highly energy-efficient and quick method of electrically heating food products. It uses the resistance of the food material to convert electrical energy into heat. However, the heating rate of ohmic heating depends on several process variables, such as electrical conductivity, voltage gradient, and voltage frequency. Therefore, it is important to study and understand the effects of these process variables to optimise the modelling and control of ohmic heating systems to obtain desirable output from food products. Hence, this study presents a review of the effects of process parameters on nutritional and organoleptic qualities, product yields, and energy efficiency of ohmic heating, along with its various industrial applications. The technology shows promising advancements in colour and nutritional quality, increasing energy efficiency, shorter processing times, and higher product yields compared to conventional heating processes.
Unveiling the Potential of Agrifood By-products: a Comprehensive Review of Phytochemicals, Bioactivities and Industrial Applications
Authors: Fernandes Filipe , Delerue-Matos Cristina , Grosso Clara
Published: September 2024

The agrifood systems produce a vast amount of food every year and yet, a large portion of that production is directly wasted. The valorisation of the by-products resulting from this sector is of the utmost importance for a full application of circular economy and the sustainability of the world in general. The residual biomass resulting from the agrifood systems can be used in a variety of ways, such as fuel, electricity or solvent production, or the extraction of phytochemicals. Phytochemicals are secondary metabolites that have health benefits in humans, namely antioxidant, antibacterial, anticancer, among many others. As such, these are highly sought after in the fight against many diseases, including cancer and neuronal diseases such as Alzheimer’s and Parkinson’s. Here, we review the main types of phytochemicals present in agrifood by-products, along with their potential bioactivities, and some industrial applications in which these phytochemicals are already being used.

Graphical Abstract
A comprehensive analysis of the advantages and disadvantages of pulsed electric fields during soil electrokinetic remediation
Authors: Abou-Shady A. , El-Araby H.
Published: September 2024

Soil electrokinetic remediation (SEKR) is considered an effective method for removing pollutants by integrating chemical, physical, and biological treatments. It has multiple applications in fields such as dewatering, consolidation, sedimentation, seed germination, etc. This work builds upon a series of recent publications on SEKR, covering topics like electrode approaches, reverse polarity-based SEK, SEK design modifications, installation of perforated materials, and chemical-based SEK. This review focuses on the role of pulsed electric field (PEF) in enhancing the performance of SEKR. There are several other names for the PEF, including periodic, interval, “ON” and “OFF”, intermittent, and breaking electric fields. PEF is proposed as a solution to overcome certain obstacles in SEKR. The review evaluates PEF's impact on (a) remediating organic and inorganic hazards, anions, and salt, (b) integrating with other processes (reverse polarity, phytoremediation, and bioremediation), and (c) electro-dewatering and consolidation. PEF offers several advantages, such as reducing energy consumption, converting the residual fractions into weakly bound fractions, achieving satisfactory remediation, avoiding the voltage drop in the area across the cation exchange membrane, enhancing desorption and/or migration of charged species, permits the exchange of contaminant from solid to the liquid phase (interstitial fluid), allows contaminant diffusion through the soil pores during the off time, generate high electroosmotic flow, avoiding electrode corrosion, decreasing concentration polarization, etc. However, it may also prolong the remediation period and cause contaminant diffusion through the soil pores, which are considered obstacles for SEKR. This review also describe different techniques related to PEF and highlights the potential use of solar cells as a renewable energy source for SEKR.

Graphic abstract
Alkali-activated materials containing mine tailings and zeolite for seepage water treatment in a closed nickel mine
Authors: Laukkanen J. , Runtti H. , Lancellotti I. , Luukkonen T. , Leonelli C. , Lassi U.
Published: September 2024

In the present study, alkali-activated materials were assessed as adsorbents for mine water treatment. The composition of alkali-activated materials, involving mixtures of metakaolin, blast-furnace slag, mine tailings, and zeolite, was optimized based on their leaching behavior and adsorption performance. The most effective adsorbent contained solely blast furnace slag as an aluminosilicate precursor and was selected for a pilot-scale study at a closed nickel mine in Finland. In the pilot, seepage water from a gangue area with an influent flow rate of 0.5 m3/d was treated using a permeable reactive barrier set-up containing 10 kg of slag-based adsorbent prepared by a granulation-alkali activation process. During a one-week experiment, the adsorbent granules were capable of effectively uptaking Ni, Fe, and Mn from the seepage water; the removal percentages of Ni, Fe, and Mn were 82.4%, 81.6%, and 82.5%, respectively. The results indicated the feasibility of blast furnace slag-based adsorbents for toxic element removal in a potentially sustainable approach.
“I Felt Like There Was Something Wrong in My Brain”: Growing Up with Trauma – How Young People Conceptualise, Self-Manage and Seek Help for Mental Health Problems
Authors: Lynch Louise , Moorhead Anne , Long Maggie , Steele Isobel Hawthorne
Published: September 2024

Background

Youth mental health is an important global healthcare topic and early interventions that are timely and evidence-based to support young people can increase quality of life and lower deaths by suicide. Research exploring young people’s mental health experiences and how they manage can further understanding into help-seeking processes.

Objective

This study aimed to explore young people’s experiences of living with and managing mental health problems and how this impacts professional help-seeking.

Methods

Eighteen young people were recruited, aged 16–25 years, with experiences of help-seeking to services for mental health problems (N = 18). Data were analysed using Constructivist Grounded Theory methods (Charmaz, Constructing grounded theory, 2014).

Findings

The findings were presented across three sub-categories: (1) “Early experiences”; (2) “Conceptualising mental health” and (3) “Managing mental health”. Findings expand understanding on the resource pressures that young people experience whilst managing persistent mental distress emanating from early experiences of trauma, life stressors, and developmental tasks. Findings also report lived experiences of pain, loneliness and stigma, and how individual conceptualisations of mental health are informed. The preference for self-reliance can be rooted in developmental needs or learned behaviours and how this impacts self-management and help seeking is discussed.

Conclusion

Through an enhanced understanding about how young people experience mental distress, developmental pressure points, marginalisation and stigma, mental health providers can prioritise individualised approaches to healthcare that can both respect a young person’s individual conceptualizations and positively leverage self-management strategies, which can contribute positively to young people’s development, quality of life, and healthcare outcomes.
Core–Shell Semiconductor-Graphene Nanoarchitectures for Efficient Photocatalysis: State of the Art and Perspectives
Authors: Lan Jinshen , Qu Shanzhi , Ye Xiaofang , Zheng Yifan , Ma Mengwei , Guo Shengshi , Huang Shengli , Li Shuping , Kang Junyong
Published: September 2024

Semiconductor photocatalysis holds great promise for renewable energy generation and environment remediation, but generally suffers from the serious drawbacks on light absorption, charge generation and transport, and structural stability that limit the performance. The core–shell semiconductor-graphene (CSSG) nanoarchitectures may address these issues due to their unique structures with exceptional physical and chemical properties. This review explores recent advances of the CSSG nanoarchitectures in the photocatalytic performance. It starts with the classification of the CSSG nanoarchitectures by the dimensionality. Then, the construction methods under internal and external driving forces were introduced and compared with each other. Afterward, the physicochemical properties and photocatalytic applications of these nanoarchitectures were discussed, with a focus on their role in photocatalysis. It ends with a summary and some perspectives on future development of the CSSG nanoarchitectures toward highly efficient photocatalysts with extensive application. By harnessing the synergistic capabilities of the CSSG architectures, we aim to address pressing environmental and energy challenges and drive scientific progress in these fields.
Unmasking gender disparities in cocoa farming: the case of female land ownership in the Ashanti and Western North regions of Ghana
Authors: Buabeng Kwabena , Löhr Katharina , Asare Richard , Sieber Stefan
Published: September 2024

Ghana's economy relies heavily on agriculture, with subsistence farming being the primary source of income for rural households. Over 50% of the food grown worldwide is produced by women. Land ownership is paramount to be recognized as a cocoa farmer in Ghana, as most land is owned by men following traditional inheritance. This gives men access to, and control over, land for agriculture, thus creating structural gender inequalities. Thereby, women's contribution to agriculture is minimized and roles undermined. This study analyses the challenges faced by women cocoa farmers in the context of land ownership and how they are influenced by social and demographic factors. We focus on ownership including sole ownership. The study, conducted in seven communities across the Ashanti and Western North regions of Ghana, comprises 160 females and 40 males. Results indicate that ownership of cocoa plots, in general, is mostly male dominated, but when female farmers make farmland decisions, they are likely to be sole owners. Marital status and the mode of acquiring lands are very important factors that dictate ownership and sole ownership of land. While the results show the importance of land as a resource that can enhance women's agricultural productivity, it also highlights that policies to reduce gender inequality in agriculture by advancing land rights are needed.
Microbiological aspects of sewage odor problems in the urban environment - a review
Authors: Felföldi Tamás
Published: September 2024

Growing human population and increasing urbanization call for the need for proper wastewater treatment to reduce environmental pollution and reduce the excess use of natural resources. During the collection of municipal wastewater, the rapid aerobic respiration often causes oxygen depletion and anaerobic conditions in the sewer system resulting in the production of malodorous compounds. The odor problems may lead to public complaints, or in the case of the sewage workers the released volatile compounds even cause serious health hazards. Therefore, microbes have a dual contribution in the urban water cycle, since they have a decisive role in wastewater treatment and the removal of pollutants, but they can also cause problems in the artificial environment. In this review, I would like to summarize the processes underlying the generation of the bad smell associated with sewage and wastewater or with the collection and treatment infrastructure, tracking the way from the households to the plants, including the discussion of processes and possible mitigation related to the released hydrogen sulfide, volatile organics and other compounds.
Fast Algorithms for Computing Fixed-Length Round Trips in Real-World Street Networks
Authors: Lewis Rhyd , Corcoran Padraig
Published: September 2024

This paper proposes and evaluates algorithms for calculating round trips of a prescribed length on directed street networks. This problem has several real-world applications, such as designing jogging routes and cycling tours. In this work, we focus specifically on methods that avoid the need to download, process, and store large map databases. At the same time, we aim for our methods to be fast, accurate, and capable of handling a wide range of prescribed distances, from just a few meters to many kilometres. To achieve this, our overall strategy involves using a small number of calls to a suitable online mapping service to collect relevant structural information for the problem at hand. All remaining computations are then performed locally on the client. Empirically, we demonstrate that our suggested techniques outperform existing open-source algorithms in terms of both accuracy and runtime requirements. Our most successful approach is based on multi-objective local search, utilizing specialized neighbourhood operators that exploit the underlying graph-theoretical properties of this problem, resulting in runtimes of around 2–3 s on a typical desktop computer.
Geospatial insights into open defecation vulnerability in Gulumbe, Nigeria
Authors: Muktar Abdullahi , Ibrahim Sa’ad , Yelwa Sadiq A.
Published: September 2024

Open defecation (OD) poses a serious public health risk by exposing communities to diseases and compromising the well-being of people. One potential approach to mitigating its impact is the application of spatial planning techniques. However, spatial data paucity is one of the major problems in addressing open defecation issues in Nigeria. This study employed spatial analysis to identify areas particularly susceptible to OD using Geographical Information System (GIS) including Merginmap applications on Android and QGIS software, which were used with field observations to georeferenced residential areas, public toilets, and instances of open defecation. Proximity analysis and local indicators of spatial autocorrelation, based on Moran’s I, were employed to assess vulnerability. Buffer analysis was conducted to identify residential areas within 100 m of an OD site, and the findings indicated residential areas at high risk of experiencing negative impacts from OD. The LISA analysis revealed a high-to-high clustering pattern (p < 0.05) in the southern region of the study area, which aligns with the results of the buffer analysis and further suggests consistent spatial patterning. Furthermore, OD was more prevalent near water bodies and inner residential areas, increasing the risk of water and air pollution. This pollution could facilitate the spread of harmful bacteria, such as E. coli and Salmonella, from OD sites to nearby households, increasing the risk of disease. This study stresses the potential of GIS in evaluating areas vulnerable to OD and highlights the need to expand awareness campaigns regarding proper hygiene and sanitation practices in rural communities.
RvXmBlendNet: A Multi-architecture Hybrid Model for Improved Skin Cancer Detection
Authors: Prity Farida Siddiqi , Hasan Ahmed Jabid , Anik Md Mehedi Hassan , Hossain Rakib , Hossain Md. Maruf , Bhuiyan Sazzad Hossain , Islam Md. Ariful , Lavlu Md Tousif Hasan
Published: September 2024

Skin cancer, one of the most dangerous cancers, poses a significant global threat. While early detection can substantially improve survival rates, traditional dermatologists often face challenges in accurate diagnosis, leading to delays in treatment and avoidable fatalities. Deep learning models like CNN and transfer learning have enhanced diagnosis from dermoscopic images, providing precise and timely detection. However, despite the progress made with hybrid models, many existing approaches still face challenges, such as limited generalization across diverse datasets, vulnerability to overfitting, and difficulty in capturing complex patterns. As a result, there is a growing need for more robust and effective hybrid models that integrate multiple architectures and advanced mechanisms to address these challenges. Therefore, this study aims to introduce a novel multi-architecture hybrid deep learning model called "RvXmBlendNet," which combines the strengths of four individual models: ResNet50 (R), VGG19 (v), Xception (X), and MobileNet (m), followed by "BlendNet" to signify their fusion into a unified architecture. The integration of these models is achieved through a synergistic combination of architectures, incorporating self-attention mechanisms using attention layers and adaptive content blocks. This study used the HAM10000 dataset to refine dermoscopic image preprocessing and enhance deep learning model accuracy. Techniques like OpenCV-based hair removal, min–max scaling, and adaptive histogram equalization were employed to improve image quality and feature extraction. A comparative study between the proposed hybrid "RvXmBlendNet" and individual models (CNN, ResNet50, VGG19, Xception, and MobileNet) demonstrated that "RvXmBlendNet" achieved the highest accuracy of 98.26%, surpassing other models. These results suggest that the system can facilitate earlier interventions, improve patient outcomes, and potentially lower healthcare costs by reducing the need for invasive diagnostic procedures.
Super-resolution reconstruction of hydrate-bearing CT images for microscopic detection of pore
Authors: Ye Wangquan , Chen Yu , Chen Liang , Li Chengfeng , Liu Shuo , Hou Guohua , Chen Qiang , Hu Gaowei , Sun Jianye , Zheng Ronger
Published: September 2024

The pore structure of marine natural gas-hydrate-bearing sediments is a key factor related to the physical properties of reservoirs. However, the resolution of micro-computed tomography (micro-CT) images is unsuitable for the analysis of pore structures in fine-grained sediments. In this regard, super-resolution (SR) reconstruction technology is expected to improve the spatial resolution of micro-CT images. We present a self-supervised learning method that does not require high-resolution datasets as input images to complete the training and reconstruction processes. This method is an end-to-end network consisting of two subnetworks: an SR network and a downscaling network. We trained on a self-built dataset of hydrate samples from three different particle sizes. Compared with typical methods, the SR results indicate that our method provides high resolution while improving clarity. In addition, it has the highest consistency with the liquid saturation method with the subsequent calculation of porosity parameters. This study contributes to the investigation of seepage and energy transfer in sediments containing natural gas hydrates, which is particularly important for the exploration and development of marine natural gas hydrate resources.
Predicting antibiotic resistance in Enterobacterales to support optimal empiric treatment of urinary tract infections in outpatient veterans
Authors: Brintz Ben J. , Madaras-Kelly Karl , Nevers McKenna , Echevarria Kelly L. , Goetz Matthew B. , Samore Matthew H.
Published: September 2024

Objective:

Bacterial resistance is known to diminish the effectiveness of antibiotics for treatment of urinary tract infections. Review of recent healthcare and antibiotic exposures, as well as prior culture results is recommended to aid in selection of empirical treatment. However, the optimal approach for assessing these data is unclear. We utilized data from the Veterans Health Administration to evaluate relationships between culture and treatment history and the subsequent probability of antibiotic-resistant bacteria identified in urine cultures to further guide clinicians in understanding these risk factors.

Methods:

Using the XGBoost algorithm, a retrospective cohort of outpatients with urine culture results and antibiotic prescriptions from 2017 to 2022 was used to develop models for predicting antibiotic resistance for three classes of antibiotics: cephalosporins, fluoroquinolones, and trimethoprim/sulfamethoxazole (TMP/SMX) obtained from urine cultures. Model performance was assessed using Area Under the Receiver Operating Characteristic curve (AUC) and Precision-Recall AUC (PRAUC)

Results:

There were 392,647 prior urine cultures identified in 214,656 patients. A history of bacterial resistance to the specific treatment was the most important predictor of subsequent resistance for positive cultures, followed by a history of specific antibiotic exposure. The models performed better than previously established risk factors alone, especially for fluoroquinolone resistance, with an AUC of .84 and PRAUC of .70. Notably, the models’ performance improved markedly (AUC = .90, PRAUC = .87) when applied to cultures from patients with a known history of resistance to any of the antibiotic classes.

Conclusion:

These predictive models demonstrate potential in guiding antibiotic prescription and improving infection management.
A novel approach for safe and automated implementation of far ultraviolet-C light decontamination in clinical areas
Authors: Memic Samir , Cadnum Jennifer L. , Osborne Andrew , Rutala William A. , Donskey Curtis J.
Published: September 2024

A novel wall-mounted far ultraviolet-C (UV-C) light technology providing automated delivery of far UV-C only when people are not present reduced methicillin-resistant Staphylococcus aureus in a patient room and equipment room. The safety feature that discontinues far UV-C output when people are detected was effective in preventing far UV-C exposure.
Predictors of postpandemic preparedness for special pathogens
Authors: Kuhnly Morgan M. , Adams Barker Caitlin M. , Stewart Kathleen O. , Kim Justin J.
Published: September 2024

In this survey of 31 hospitals, large metropolitan facilities had a 9.5-fold odds of reporting preparedness for special pathogens; hospitals with special pathogens teams had a 14.3-fold odds of reporting preparedness for special pathogens. In the postpandemic world, healthcare institutions must invest in special pathogen responses to maximize patient safety.
Local parameters of supercuspidal representations
Authors: Gan Wee Teck , Harris Michael , Sawin Will , Beuzart-Plessis Raphaël
Published: September 2024

For a connected reductive group G over a nonarchimedean local field F of positive characteristic, Genestier-Lafforgue and Fargues-Scholze have attached a semisimple parameter

${\mathcal {L}}^{ss}(\pi )$

to each irreducible representation

$\pi $

. Our first result shows that the Genestier-Lafforgue parameter of a tempered

$\pi $

can be uniquely refined to a tempered L-parameter

${\mathcal {L}}(\pi )$

, thus giving the unique local Langlands correspondence which is compatible with the Genestier-Lafforgue construction. Our second result establishes ramification properties of

${\mathcal {L}}^{ss}(\pi )$

for unramified G and supercuspidal

$\pi $

constructed by induction from an open compact (modulo center) subgroup. If

${\mathcal {L}}^{ss}(\pi )$

is pure in an appropriate sense, we show that

${\mathcal {L}}^{ss}(\pi )$

is ramified (unless G is a torus). If the inducing subgroup is sufficiently small in a precise sense, we show

$\mathcal {L}^{ss}(\pi )$

is wildly ramified. The proofs are via global arguments, involving the construction of Poincaré series with strict control on ramification when the base curve is

${\mathbb {P}}^1$

and a simple application of Deligne’s Weil II.
Linguistic synesthesia detection: Leveraging culturally enriched linguistic features
Authors: Zhao Qingqing , Long Yunfei , Jiang Xiaotong , Wang Zhongqing , Huang Chu-Ren , Zhou Guodong
Published: September 2024

Linguistic synesthesia as a productive figurative language usage has received little attention in the field of Natural Language Processing (NLP). Although linguistic synesthesia is similar to metaphor concerning involving conceptual mappings and showing great usefulness in the NLP tasks such as sentiment analysis and stance detection, the well-studied methods of metaphor detection cannot be applied to the detection of linguistic synesthesia directly. This study incorporates comprehensive linguistic features (i.e., character and radical information, word segmentation information, and part-of-speech tagging) into a neural model to detect linguistic synesthetic usages in a sentence automatically. In particular, we employ a span-based boundary detection model to extract sensory words. In addition, a joint model is proposed to detect the original and synesthetic modalities of the sensory words collectively. Based on the experiments, our model is shown to achieve state-of-the-art results on the dataset for linguistic synesthesia detection. The results prove that leveraging culturally enriched linguistic features and joint learning are effective in linguistic synesthesia detection. Furthermore, as the proposed model leverages non-language-specific linguistic features, the model would be applied to the detection of linguistic synesthesia in other languages.
Letting Beethoven’s Hair Down: Dancing and Musicking in Vienna
Authors: LOGES NATASHA
Published: September 2024

It feels fitting to have worked on this review in Baden bei Wien, in which Beethoven spent many summers. This pretty town southwest of Vienna boasts not only a Beethoven-Haus, but also a Beethoven-Panoramaweg, Beethoven-Rundwanderweg, Beethoven-Spazierweg, and even an imposing Beethoven-Tempel, offering a scenic view; notions of decentring, decolonizing, or even critically engaging with Beethoven’s canonic status feel not only remote, but also faintly inappropriate in this, as many other, Beethoven-designated spaces. Moreover, at the time of writing, the international press is reporting that Beethoven’s skull fragments are being returned to Vienna, as though they are holy relics.1 Such material traces of Beethoven’s canonicity seem to mock attempts to rattle the ideological cage, yet two recent books by Erica Buurman and Nancy November make significant contributions.2 The former indirectly poses questions about Beethoven’s relationship to Viennese dance culture, while the latter is a deeply impressive account of the chamber music arrangements of Beethoven’s symphonies. Both left me a touch nostalgic for the now marginal cultures of formal dancing and musical arrangement, which dominated the soundscape of early nineteenth-century Vienna.
Solid bases and functorial constructions for (p-)Banach spaces of analytic functions
Authors: Cheng Guozheng , Fang Xiang , Liu Chao , Lu Yufeng
Published: September 2024

Motivated by new examples of functional Banach spaces over the unit disk, arising as the symbol spaces in the study of random analytic functions, for which the monomials $\{z^n\}_{n\geq 0}$ exhibit features of an unconditional basis yet they often don’t even form a Schauder basis, we introduce a notion called solid basis for Banach spaces and p-Banach spaces and study its properties. Besides justifying the rich existence of solid bases, we study their relationship with unconditional bases, the weak-star convergence of Taylor polynomials, the problem of a solid span and the curious roles played by c0. The two features of this work are as follows: (1) during the process, we are led to revisit the axioms satisfied by a typical Banach space of analytic functions over the unit disk, leading to a notion of $\mathcal{X}^\mathrm{max}$ (and $\mathcal{X}^\mathrm{min}$), as well as a number of related functorial constructions, which are of independent interests; (2) the main interests of solid basis lie in the case of non-separable (p-)Banach spaces, such as BMOA and the Bloch space instead of VMOA and the little Bloch space.