bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robust and novel attention guided MultiResUnet model for 3D ground reaction force and moment prediction from foot kinematics
Authors: Faisal Md. Ahasan Atick , Mahmud Sakib , Chowdhury Muhammad E. H. , Khandakar Amith , Ahmed Mosabber Uddin , Alqahtani Abdulrahman , Alhatou Mohammed 
Published: October 2023

AbstractGround reaction force and moment (GRF&M) measurements are vital for biomechanical analysis and significantly impact the clinical domain for early abnormality detection for different neurodegenerative diseases. Force platforms have become the de facto standard for measuring GRF&M signals in recent years. Although the signal quality achieved from these devices is unparalleled, they are expensive and require laboratory setup, making them unsuitable for many clinical applications. For these reasons, predicting GRF&M from cheaper and more feasible alternatives has become a topic of interest. Several works have been done on predicting GRF&M from kinematic data captured from the subject’s body with the help of motion capture cameras. The problem with these solutions is that they rely on markers placed on the whole body to capture the movements, which can be very infeasible in many practical scenarios. This paper proposes a novel deep learning-based approach to predict 3D GRF&M from only 5 markers placed on the shoe. The proposed network “Attention Guided MultiResUNet” can predict the force and moment signals accurately and reliably compared to the techniques relying on full-body markers. The proposed deep learning model is tested on two publicly available datasets containing data from 66 healthy subjects to validate the approach. The framework has achieved an average correlation coefficient of 0.96 for 3D ground reaction force prediction and 0.86 for 3D ground reaction momentum prediction in cross-dataset validation. The framework can provide a cheaper and more feasible alternative for predicting GRF&M in many practical applications.
Assessment of the groundwater recharge processes of a shallow and deep aquifer system (Maggiore Valley, Northwest Italy): a hydrogeochemical and isotopic approach
Authors: Cocca Daniele , Lasagna Manuela , Marchina Chiara , Brombin Valentina , Santillán Quiroga Luis Miguel , De Luca Domenico Antonio 
Published: October 2023

AbstractThe Maggiore Valley well field plays a fundamental role in supplying drinking water to a large territory of the Piedmont Region (northwestern Italy) and has been intensively exploited since the early twentieth century. This water resource is hosted in a deep, multilayered aquifer system. The main purpose of this study was to characterize the recharge processes of the deep aquifer through hydrochemical and isotopic assessments, as well as the water quality in the recharge and drainage areas. For this purpose, 128 physical–chemical analyses (major ions) and 50 isotopic analyses (δ18O and δ2H) were carried out on samples collected in shallow and deep aquifer complexes in two sampling campaigns in 2021. From the results, a hydrogeological conceptual model of recharge processes was developed. The chemical data confirm the presence of bicarbonate–calcium facies in most samples of the shallow and deep aquifer complexes. Clear hydrochemical differences were observed among the investigated sectors. The recharge areas were identified as (1) far zones, namely the shallow aquifer complex of the Cuneo Plain, and (2) the shallow and deep aquifer complexes with groundwater mixing in the riverside sector of Po Plain in the Turin area. The mixing of waters from the Cuneo Plain and Turin Plain was verified in the well field area. The isotopic values of the artesian well water also confirmed contributions from the Turin and Cuneo Alps. This study clarified the recharge processes, thereby defining potential pollutant pathways, and the results provide additional support for groundwater resource management and protection.
Bioremediation of industrial wastewater heavy metals using solo and consortium Enterobacter spp.
Authors: Kelany Mahmoud Saber , El-sawy Mohamed AbdElAziz , El-Gendy Ahmed Rabie , Beltagy Ehab Aly 
Published: October 2023

AbstractHeavy metals are considered the most common pollutants in industrial wastewater areas. Out of thirty bacterial isolates, only 3 isolates sighted the highest metal resistance activity for Zn+2, Fe+2, Pb+2, Co+2, Mn+2, Ni+2, and Cd+2. The biochemical and DNA homology identification with similarities 99.58%, 99.79%, and 99.86% of those isolates was identified and deposited in WDCM, respectively, as Enterobacter kobei OM144907 SCUF0000311, Enterobacter cloacae OM180597 SCUF0000312, and Enterobacter hormaechei OM181067 SCUF0000313. The minimum tolerance activity (MIC) of heavy metal concentrations against E. kobei and E. cloacae was 25, 15, and 15 mmol/l for Ni+2, Fe+2, and Mn+2, respectively, and 10 mmol/l for Zn+2, Pb+2, Co+2, and Cd+2, while against E. hormaechei, it is 15 mmol/l for Ni+2, Fe+2, and Mn+2 and 10 mmol/l for Zn+2, Pb+2, Co+2, and Cd+2. The consortium and solitary application of bacterial isolates towards heavy metal removal at 100%, 200%, and 300% industrial wastewater concentrations were conducted and showed that more than 90% removal of Zn+2, Fe+2, Pb+2, Mn+2, Ni+2, and Cd+2 from a non-concentrated polluted sample (100%) was reported by the three strains. With doubling the polluted sample concentration (200%), the highest removal efficiency for Zn+2, Pb+2, Mn+2, Ni+2, and Cd+2 was reported by E. cloacae as 70. 75, 66, 65, and 57%, respectively. Removal efficiency after increasing the polluted sample concentration to 300% showed that E. cloacae removed above 45% of all tested heavy metals except Pb+2. Ultimately, E. cloacae exposed the highest efficiency with recommendations for heavy metals removal under higher concentrations.
Acrylamide toxicity in aquatic animals and its mitigation approaches: an updated overview
Authors: Naiel Mohammed A. E. , Negm Samar S. , Ghazanfar Shakira , Farid Arshad , Shukry Mustafa 
Published: October 2023

AbstractAcrylamide (ACR) is widely applied in various industrial activities, as well as in the water purification process. Furthermore, ACR is synthesized naturally in some starchy grains exposed to high temperatures for an extended time during the cooking process. Because of its widespread industrial usage, ACR might be released into water stream sources. Also, ACR poses a high risk of contaminated surface and ground-water resources due to its high solubility and mobility in water. Furthermore, animal studies have indicated that ACR exposure may cause cancer (in many organs such as lung, prostate, uterus, and pancreas), genetic damage (in both somatic and germ cells), and severe effects on reproduction and development. Recently, numerous studies have shown that ACR has a mild acute cytotoxic impact on aquatic species, particularly during early life stages. Besides, wide-spectrum usage of ACR in many industrial activities presented higher environmental risks as well as major hazards to consumer health. This literature was designed to include all potential and accessible reports on ACR toxicity related with aquatic species. The Preferred Reporting Items for Systematic Reviews were applied to evaluate the risk effects of ACR on aquatic organisms, the ACR sub-lethal concentration in the ecosystem, and the possible protective benefits of various feed additives against ACR toxicity in fish. The major findings are summarized in Tables 2 and 3. The primary aim of this literature was to specify the hazards of ACR toxicity related with fish welfare and possible suggested strategies to reduce its risks.
A critique of transnational research on subjectivation from the perspective of postcolonial epistemology
Authors: Engel Juliane , Hummrich Merle 
Published: October 2023

AbstractThe article shows how modern subject constitutions and postcolonial relations of white dominance are systematically reproduced in school contexts. Postcolonial critique is thus revealed as an analytical strategy to focus on processes of transnationalization in schools (through internationalization and immigration). The empirical foundation of this article is formed by two qualitative research projects that show different variants of interactive and performative entanglement of school actors in colonial knowledge orders and their subjectivizing logics of production in relations of power and recognition. Two case analyses illuminate different dimensions of how racialized subjects are produced and of postcolonial orders. These different projects illustrate the multi-perspectival complexity of how structures of differences are reproduced. The article also underlines the importance of an educational perspective on the dynamics of power, recognition, and subjectification in school orders. It concludes by briefly touching on possibilities for future reflection on perspectives of knowledge within orders characterized by the dominance of one culture and their relationality.
Photocatalytic degradation of non-ionic, anionic, and cationic surfactants: from batch experiments through equilibrium/kinetic study to ecotoxicology analysis
Authors: Wysokowska Klaudia , Cupiał Zuzanna , Staszak Maciej , Zgoła-Grześkowiak Agnieszka , Koziolek Jan , Ławniczak Łukasz , Wysokowski Marcin , Wyrwas Bogdan 
Published: October 2023

AbstractSurface-active compounds constitute a group of important and widespread environmental pollutants. Among different methods used for their treatment, photocatalytic degradation is a promising and efficient solution. Nevertheless, the exact outcome of photodegradation of surfactants may be difficult to predict in case of concentrations used at the industrial scale and considering that the associated mechanism involves radicals which may potentially result in the formation of toxic by-products. In consequence, the aim of this study was to analyze the catalytic photodegradation of three groups of surfactants (three structurally diverse representatives of cationic, anionic, and non-ionic surfactants). Nanoparticles of zinc oxide were synthesized and used as a photocatalyst. The efficiency of photodegradation ranged from 93 to 100% at 10 mg/L, from 38 to 94% at 100 mg/L, and from 15 to 66% when the surfactants were supplied at 1000 mg/L, and the results depended on the structure of the compound subjected to treatment. Subsequent investigation of kinetics revealed that Freundlich, Langmuir or Dubinin-Radushkevich isotherms may be used to describe the adsorption of surfactants (1–65%) and allowed to establish the following order of reactivity: cationic > non-ionic > anionic. Subsequent LC–MS/MS studies of the residues were the basis for identification of photodegradation products for each respective compound. Ultimately, due to the fact that treated graywater is often used as potable water, the phytotoxicity of the degradation products was tested toward sorghum. It was established that in the majority of cases the treatment was efficient (in some cases stimulation of plant growth compared to control samples was observed), whereas an increase in toxicity was observed in case of two cationic surfactants (CTAB and benzalkonium chloride). Overall, the results presented in this study support the application of photocatalytic degradation as an efficient solution for treatment of surfactant-rich effluents.
Novel Therapeutic Options for Small Cell Lung Cancer
Authors: Canova Stefania , Trevisan Benedetta , Abbate Maria Ida , Colonese Francesca , Sala Luca , Baggi Alice , Bianchi Sofia Paola , D’Agostino Anna , Cortinovis Diego Luigi 
Published: October 2023

Abstract
Purpose of Review
The aim of this review is to focus on the recent advances in the molecular knowledge of small cell lung cancer (SCLC) and potential promising new treatment strategies, like targeting the DNA damage pathway, epigenetics, angiogenesis, and oncogenic drivers.

Recent Findings
In the last few years, the addition of immunotherapy to chemotherapy has led to significant improvements in clinical outcomes in this complex neoplasia. Nevertheless, the prognosis remains dismal. Recently, numerous genomic alterations have been identified, and they may be useful to classify SCLC into different molecular subtypes (SCLC-A, SCLC-I, SCLC-Y, SCLC-P).

Summary
SCLC accounts for 10-20% of all lung cancers, most patients have an extensive disease at the diagnosis, and it is characterized by poor prognosis. Despite the progresses in the knowledge of the disease, efficacious targeted treatments are still lacking. In the near future, the molecular characterisation of SCLC will be fundamental to find more effective treatment strategies.
Energy Demand Reduction: supply chains and risk analysis
Authors: Axon C. J. , Darton R. C. 
Published: October 2023

AbstractDemand Reduction is a strategy with the potential to make a significant contribution to the energy supply/demand balance. Its two major themes are improving the energy efficiency of devices (appliances and processes) and changing people’s behaviour towards using less energy. In our analysis of a nation’s energy security, we treat Demand Reduction as an additional fuel which delivers ‘negafuel’, allowing a particular level of energy services to be met at a lower volume of supply than would be possible in its absence. In common with other fuels, negafuel is delivered by a supply chain with linked stages, all encountering risks of various types. A comprehensive survey of these risks in a case study of the UK shows that Demand Reduction belongs to a middle-ranking group of fuels in terms of overall risk. High-level risks encountered include the difficulty of assessing and delivering potential energy savings, the rate of building construction at the highest energy efficiency standards, optimism bias, changing policy and regulation, and operational failure (both of technology and policy). Assessing the risk of Demand Reduction as a supplied negafuel focuses attention on specific risks requiring mitigation, facilitating design of better policy, and more effective commercial products.
Mapping Tree Water Deficit with UAV Thermal Imaging and Meteorological Data
Authors: Krause Stuart , Sanders Tanja GM 
Published: October 2023

AbstractThe mapping of forest stands and individual trees affected by drought stress is a crucial step in targeted forest management, aimed at fostering resilient and diverse forests. Unoccupied aerial vehicle (UAV)-based thermal sensing is a promising method for obtaining high-resolution thermal data. However, the reliability of typical low-cost sensors adapted for UAVs is compromised due to various factors, such as internal sensor dynamics and environmental variables, including solar radiation intensity, relative humidity, object emissivity and wind. Additionally, accurately assessing drought stress in trees is a complex task that usually requires laborious and cost-intensive methods, particularly in field settings. In this study, we investigated the feasibility of using the thermal band of theMicasense Altummultispectral sensor, while also assessing the potential for modelling tree water deficit (TWD) through point dendrometers and UAV-derived canopy temperature. Our indoor tests indicated that using a limited number of pixels (< 3) could result in temperature errors exceeding 1 K. However, enlarging the spot-size substantially reduced the mean difference to 0.02 K, validated against leaf temperature sensors. Interestingly, drought-treated (unwatered) leaves exhibited a higher root mean squared error (RMSE) (RMSE = 0.66 K and 0.73 K) than watered leaves (RMSE = 0.55 K and 0.53 K), likely due to lower emissivity of the dry leaves. Comparing field acquisition methods, the mean standard deviation (SD) for tree crown temperature obtained from typical gridded flights was 0.25 K with a maximum SD of 0.59 K (n= 12). In contrast, a close-range hovering method produced a mean SD of 0.09 K and a maximum SD of 0.1 K (n= 8). Modelling the TWD from meteorological and point dendrometer data for the 2021 growth season (n= 2928) yielded anR2= 0.667 using a generalised additive model (GAM) with vapor pressure deficit (VPD), wind speed, and solar radiation as input features. A point dendrometer lag of one hour was also implemented. When predicting individual tree TWD with UAV-derived tree canopy temperature, relative humidity, and air temperature, an RMSE of 4.92 (μm) andR2of 0.87 were achieved using a GAM. Implementing leaf-to-air pressure deficit (LVPD) as an input feature resulted in an RMSE of 6.87 (μm) and anR2of 0.71. This novel single-shot approach demonstrates a promising method to acquire thermal data for the purpose of mapping TWD of beech trees on an individual basis. Further testing and development are imperative, and additional data from drought periods, point dendrometers, and high-resolution meteorological sources are required.
Characteristics and Mitigation Measures of Candida auris Infection: Descriptive Analysis from a Quaternary Care Hospital in Saudi Arabia, 2021–2022
Authors: Amer Hala A. , AlFaraj Sarah , Alboqami Kholoud , Alshakarh Faleh , Alsalam Mona , Kumar Deva , Altayieb Juhaina , Alsunid Antisar , Khanum Nazia , Dar Nadeem Gul , Badawi Muhammad , Abdallah Hassan , Memish Ziad A. 
Published: October 2023

Abstract
Objective
To analyze the characteristics of C. auris cases, and to describe the interventions applied for improving the diagnosis and controlling the transmission.

Method
Medical records of C. auris cases reported between January 2021 until June 2022 at King Saud Medical City (KSMC), Riyadh, Kingdom of Saudi Arabia have been reviewed. We analyzed the demographic and clinical characteristics of the cases to illustrate the possible contributing factors with C. auris infection. A multidisciplinary committee has been formulated to investigate the potential source of the outbreak among clusters of cases in the intensive care units (ICU). A bundle of mitigation measures has been applied which was successful to contain the outbreak.

Results
During the study period, a total of 129 cases of C. auris were identified, their mean age is 47 ± 22.3 SD, and 72.1% are males. 57% of cases were colonized, all of them were identified through active screening. A number of comorbidities were present including 27.9% were having hypertension, 27.1% with diabetes, 22.5% with COVID-19 and 20.2% with respiratory diseases. The average length of stay before reported positive was 36.23 days. 78.3% of those patients were in the critical care unit, 73.6% with vascular catheter, 88% with urinary catheters and 66.7% with mechanical ventilation. The vast majority of patients were using multiple antibiotics (86%). As per the univariate logistic model, risk factors significantly associated with mortality were (Age, Trauma RTA, ICU, Vascular Access, Foley Catheters, Mechanical Ventilation, Tracheostomy and Endotracheal Tubes) with p values (0.0038, 0.0159, 0.0108, 0.0122, 0.0071, &lt;.0001, 0.0148 and 0.0107), respectively. Multivariate logistic regression showed that having a Foley Catheter was the only statistically significant factor associated with mortality.

Conclusion
This retrospective analysis highlights the main characteristics associated with C. auris-infected patients. In addition, it highlights the effectiveness of the bundle of mitigation strategies applied to limit the spread of C. auris in healthcare facilities.
Visual-semantic network: a visual and semantic enhanced model for gesture recognition
Authors: Wang Yizhe , Cao Congqi , Zhang Yanning 
Published: October 2023

AbstractGesture recognition has attracted considerable attention and made encouraging progress in recent years due to its great potential in applications. However, the spatial and temporal modeling in gesture recognition is still a problem to be solved. Specifically, existing works lack efficient temporal modeling and effective spatial attention capacity. To efficiently model temporal information, we first propose a long- and short-term temporal shift module (LS-TSM) that models the long-term and short-term temporal information simultaneously. Then, we propose a spatial attention module (SAM) that focuses on where the change primarily occurs to obtain effective spatial attention capacity. In addition, the semantic relationship among gestures is helpful in gesture recognition. However, this is usually neglected by previous works. Therefore, we propose a label relation module (LRM) that takes full advantage of the relationship among classes based on their labels’ semantic information. To explore the best form of LRM, we design four different semantic reconstruction methods to incorporate the semantic relationship information into the class label’s semantic space. We perform extensive ablation studies to analyze the best settings of each module. The best form of LRM is utilized to build our visual-semantic network (VS Network), which achieves the state-of-the-art performance on two gesture datasets, i.e., EgoGesture and NVGesture.
Commercial Casualties: Political Boycotts and International Disputes
Authors: Weiss Jessica Chen , Barwick Panle Jia , Li Shanjun , Wallace Jeremy L. 
Published: October 2023

Abstract
We explore whether international disputes harm commerce by galvanizing consumer boycotts of foreign products. Boycotts increase the social penalty of owning goods associated with a foreign adversary, offsetting individual incentives to free ride or discount the utility of participation. By harming international commerce, boycotts can help reveal information about resolve and avoid more costly forms of conflict. Using administrative data on the universe of new passenger vehicle registration records in China from 2009 to 2015, we demonstrate that consumer boycotts that arose amid tensions between China and Japan over a territorial dispute in 2012 had significant and persistent effects on vehicle sales, especially in cities that witnessed anti-Japanese street demonstrations. The market share of Japanese brands dropped substantially during and after the boycott with long lasting effects. Our analysis provides concrete evidence of the short- and long-term impacts of international tensions on economic activities.
The Conventionality of Real-Valued Quantities
Authors: Bennett Marissa , Miller Michael E. 
Published: October 2023

AbstractThe original architects of the representational theory of measurement interpreted their formalism operationally and explicitly acknowledged that some aspects of their representations are conventional. We argue that the conventional elements of the representations afforded by the theory require careful scrutiny as one moves toward a more metaphysically robust interpretation by showing that there is a sense in which the very number system one uses to represent a physical quantity such as mass or length is conventional. This result undermines inferences which impute structure from the numerical representational structure to the quantity it is used to represent.
Dark Energy or Modified Gravity?
Authors: Smeenk Chris , Weatherall James Owen 
Published: October 2023

AbstractWe consider some of the epistemic benefits of exploring “theory space” in the context of modifications of general relativity with intended applications in cosmology. We show how studying modifications of general relativity can help in assessing the robustness of empirical inferences, particularly in inaccessible regimes. We also discuss challenges to sharply distinguishing apparently distinct directions in theory space.
Compulsory civic duty and turnout: evidence from a natural experiment
Authors: Artes Joaquin , Jurado Ignacio 
Published: October 2023

AbstractWe study the effect of compulsory civic duty on turnout. We take advantage of a natural experiment in Spain, where electoral officers are selected through a lottery and being an electoral officer is compulsory for those drafted. We analyze whether acting as an officer changes turnout and attitudes in subsequent elections. Our findings show that compulsory civic duty has a strong short-term and positive effect on electoral participation, but has no impact on political attitudes. The positive effect of the civic duty treatment, however, fades after a few months. Our results have implications for theories about civic duty and the formation of political habits.