bluuebunny/crossref_metadata_2025 huggingface dataset:
Representation of multi-cubic mappings and some approximations in 2-Banach spaces
Authors: Bodaghi Abasalt
Published: September 2024

This study first focuses on defining a new fashion of multi-cubic mappings, and then represent such mapping as an single equation, as the multi-cubic functional equation. Additionally, this work also discusses the Ulam–Hyers stability and generalized Ulam–Hyers–Rassias stability of multi-cubic equations by applying the so-called direct (Hyers) method in the setting of 2-Banach spaces.
Common fixed point theorem in bipolar controlled b-dislocated metric space and its application to some nonlinear equations
Authors: Chauhan Gonder Surjeet Singh , Raturi Akriti , Garg Prachi
Published: September 2024

The existence and uniqueness of common fixed point theorems are demonstrated in this work through the use of [Formula: see text]-cyclic [Formula: see text]-contraction mapping and bipolar controlled b-dislocated metric space. In the scope of an application, we consider the potential for a unique common solution for nonintegral and nonlinear fractional differential equations.
Explaining the Taliban’s Revival: Thomas Spragens’s Crisis Theory
Authors: Ardakani Hossein Fattahi
Published: September 2024

The revival of the Taliban and their rapid domination of Afghanistan shocked the world. It is a response to the chronic historical, political and social crises of the Afghan society, which is still in geopolitical and strategic confusion and disorder. Using the analytical descriptive method, the present study attempts to answer the question related to the causes of the reemergence of the Taliban based on Thomas Spragens’ crisis theory. The research hypothesis states that the conflict between political actors and the creation of a political deadlock has caused successive crises and political, social and security disintegration in the society. Accepting the Taliban, the Afghan people seek to solve the crisis and restore, peace, stability, order and security for themselves and their descendants. It seems that the occupation of the country, nonimplementation of Sharia laws and spread of corruption are signs of a brewing crisis caused by the weakness of the central government, lack of nation-state agreement, the spread of ethnocentrism and overdependence on America. To address these challenges, Afghans increasingly resort to Jihad and the formation of an Islamic Emirate as a possible solution.
Ab Initio Molecular Dynamics Studies of Stacked Adenine–Thymine and Guanine–Cytosine Nucleic Acid Base Pairs in Aqueous Solution
Authors: Banerjee Subhadip , Bhargava B. L.
Published: September 2024

Ab initio MD studies have been performed on stacked adenine–thymine (A–T) and guanine–cytosine (G–C) nucleobase pairs solvated in water using Born–Oppenheimer molecular dynamics. These two systems have been analyzed using RDF, SDF, angle-distance CDF (combined distribution functions), plane projection analysis, hydrogen bond analysis, and non-covalent interaction (NCI) plots. The stacking property studies have shown that the molecular orientation of the A–T pair is completely opposite to that of the G–C pair though the center of mass distance between the two molecules is similar. The G–C pair shows significantly more stability in water than the A–T system does. RDF analyses show that the –NH– group and carbonyl groups show predominant interaction with water molecules. Water molecules are found to be most in numbers around the cytosine molecule and least around the adenine molecule. Hydrogen bonding studies show that the guanine molecule forms the highest number of hydrogen bonds with water molecules. On the other hand, the hydrogen atom attached to the –NH– group of adenine molecule shows the longest mean H-bond lifetime with water oxygen atoms. NCI interactions calculated through the ab initio method help us to visualize the [Formula: see text]-electron stacking and H-bonding between aromatic nucleobases and water molecules. A great shift in bond polarity and interaction intensity in different functional groups is observed for the nucleobases going from individually solvated molecules to paired states.
A Computational Perspective into Binding Mechanism of a potent FAK Inhibitor as Anticancer Drug Candidate: Insights from Molecular Dynamics Simulations
Authors: Shogi F. , Gholamin D. , Razzaghi-Asl N.
Published: September 2024

Focal adhesion kinase (FAK) is an important non-receptor tyrosine kinase (nRTK) with crucial role in primary cell functions. Fundamental cellular processes, such as migration, adhesion, proliferation, and survival, are regulated by FAK. The tumorigenesis of FAK is very important since it is overexpressed in advanced cancers, causes malignant features and induces cancer metastasis. The available evidence proposes FAK as a promising target for cancer therapy. At the moment, there are no FAK inhibitors (FAKIs) in the market but several small molecule FAKIs have been developed and a few of them entered into clinical studies as anticancer agents. In spite of these achievements, development of selective and potent FAKIs may be partly hampered by the lack of crystallographic or structural data. This limitation could be resolved through proposing robust ligand–protein binding models to design new FAKIs. GSK2256098 is a small molecule ATP-competitive FAKI that undergoes clinical trials as a monotherapy or in combination with other medications against advanced solid tumors. GSK2256098 have been proven to be a selective and potent agent (IC[Formula: see text] 0.4 nM) with respect to other clinical candidates. With regard to appropriate characteristics, this molecule is particularly amenable for performing computational modeling studies. In this study, we try to propose an applicable binding model of GSK2256098 inside the FAK kinase domain. For this purpose, molecular docking, all-atom 200-ns molecular dynamics simulations and free-energy-calculation methods were applied as consecutive modeling techniques. Atomic insight and dynamic evolution of the system were used to attain a stable binding mode and infer chemical interactions of GSK2256098 inside the kinase domain of FAK. Although complementary investigations need to be conducted, obtained results may offer a structural basis for the development of potent and selective FAKIs.
Distributed Task Allocation Algorithm for Heterogeneous UAV Cluster Based on Game Theory
Authors: Xue Shuxin , Ma Yajie , Jiang Bin , Lyu Xuan
Published: September 2024

This paper proposes a distributed task allocation algorithm based on game theory to solve the complex task allocation optimization problem when UAV clusters carry heterogeneous resources and tasks have heterogeneous demands. Considering the heterogeneity of resources, two pre-processing methods are proposed: one is the grouping algorithm that combines greedy algorithm with simulated annealing algorithm, and the other is the improved K-medoids clustering algorithm based on heterogeneous resources. These pre-process methods, through grouping and clustering, can reduce the complexity of task allocation. The entropy weight method is utilized to prioritize tasks based on multiple metrics. Considering task demands, airborne resources and path cost, a coalition formation game model is established, which is proved to be a potential game. Then a distributed task allocation algorithm based on coalition formation game is designed to address the task allocation problem. Finally, the simulation involving 30 tasks with heterogeneous requirements assigned to 100 UAVs validates the effectiveness of the proposed algorithm, showing that it can achieve good task allocation results with great real-time performance.
On Covariance Switch-Based Invariant Extended Kalman Filter for Multi-Source Fusion
Authors: Han Jiale , Ouyang Wei , Zhu Maoran , Wu Yuanxin
Published: September 2024

The good estimation consistency of Invariant Extended Kalman Filter (InEKF) is mainly attributed to its excellent trajectory-independent property. However, when the InEKF is applied to multi-source inertial-based navigation that coexists left-invariant and right-invariant observations, the observation matrix would be unavoidably trajectory-dependent and might lead to the degradation of estimation performance. This paper for the first time performs theoretical analyses on the covariance switch between the left error and the right error in multi-source inertial-based navigation. Furthermore, detailed realizations of the covariance switch-based InEKF are formulated in this work, which are lacked in previous works. Numerical simulations and experiments demonstrate that the covariance switch significantly reduces the attitude errors during the transient phase in contrast with the original method using the incompatible error definition.
Forward Singapore: Strengthening SkillsFuture
Authors: Loh Chelvin , Yeo Wee Siong
Published: September 2024

This practitioner note provides an overview of developments in the SkillsFuture movement. Particularly, it details how innovations in the skills ecosystem are shifting lifelong learning to a higher gear and enabling greater ownership of one’s skills and career health. Frequent tech disruptions, shortened half-life of skills and knowledge, and new job roles emerging every day mean our workforce must retool at scale and at speed. To be nimble and adaptable enough to support the timely reskilling and upskilling of Singapore’s 2.5 million resident workforce, SkillsFuture Singapore is working with training, industry, and tripartite partners to enhance the understanding of what skills we need as a national workforce, and use this knowledge as an advantage to stay ahead of the curve. However identifying skills in demand is not enough in this dynamic job market. To achieve agility and responsiveness of the skills ecosystem, there are collective efforts with industry leaders, training providers, and skills-tech providers to strengthen the skills demand-supply coordination. As part of the Forward Singapore agenda, this collective awareness of skill trends and enhanced demand-supply coordination will ultimately strengthen Singapore’s competitive advantage, and workforce mobility and resilience.
Empowering the Next Generation: Navigating Challenges and Opportunities in the Modern Workforce Through Coaching and Mentorship
Authors: Lim Sok Mui , Ibrahim Yaacob
Published: September 2024

Each workforce generation grapples with distinctive challenges, and the contemporary job market introduces new complexities with the integration of artificial intelligence. The impact of artificial intelligence on organisational productivity is noteworthy, especially as it provides opportunities for lower-skilled workers to enhance their capabilities, albeit with potential implications for the development of tacit knowledge. Despite prevailing generational judgements, insights from various studies and reports reveal that the younger generation in Singapore values workforce acceptance and hard work, and exhibits resilience. Concurrently, the 2022 National Population Health Survey by the Ministry of Health highlighted a significant proportion of individuals aged 18–29 years experiencing poor mental health. Managing the well-being and productivity of the younger workforce becomes crucial, with the introduction of a growth mindset offering a potential solution. A growth mindset refers to the belief in one’s capacity for development and the malleability of human attributes. Three key strategies are identified for fostering a growth mindset and well-being in the workforce: regular constructive feedback, organisational responses to project failures, and adopting a “not yet” approach to unmet goals. Furthermore, the implementation of workplace coaching and mentoring emerges as a strategic solution, targeting individual and organisational performances, and sustainable well-being. Within workplace coaching, bridge mentoring is proposed to address diversity gaps and positively impact employee learning and development.
CrossFormer: Cross-Modal Representation Learning via Heterogeneous Graph Transformer
Authors: Liang Xiao , Yang Erkun , Deng Cheng , Yang Yanhua
Published: September 2024

Transformers have been recognized as powerful tools for various cross-modal tasks due to their superior ability to perform representation learning through self-attention. Existing transformer-based cross-modal models can be categorized into single-stream and dual-stream ones. By performing fine-grained interaction with self-attention on the cross-modal concatenated features, the former can simultaneously learn intra- and inter-modal correlations. However, this simple concatenation treats the inputs of different modalities equally; as a result, the heterogeneous differences between modalities are ignored, leading to a modality gap. The latter process the inputs of different modalities separately, then perform cross-modal interaction on the subsequently fused networks, resulting in a failure to integrate the fine-grained correlations of both intra- and inter-modality in a uniform module. To this end, we propose an effective heterogeneous graph transformer for dual-stream cross-modal representation learning, named CrossFormer, which constructs a heterogeneous graph as a bridge to achieve fine-grained intra- and inter-modal interaction on a dual-stream network. Specifically, we first represent multi-modal data with a heterogeneous graph, then develop a dual-positional encoding strategy that enables the heterogeneous graph to obtain the relative positional information. Finally, a dual-stream self-attention is performed on the heterogeneous graph, bridging the gap between modalities and effectively capturing fine-grained intra- and inter-modal interactions simultaneously. Extensive experiments on various cross-modal tasks demonstrate the superiority of our method.
Compound Logics for Modification Problems
Authors: Fomin Fedor V. , Golovach Petr A. , Sau Ignasi , Stamoulis Giannos , Thilikos Dimitrios M.
Published: September 2024

We introduce a novel model-theoretic framework inspired from graph modification and based on the interplay between model theory and algorithmic graph minors. The core of our framework is a new compound logic operating with two types of sentences, expressing graph modification: the
modulator sentence
, defining some property of the modified part of the graph, and the
target sentence
, defining some property of the resulting graph. In our framework, modulator sentences are in counting monadic second-order logic (
CMSO
) and have models of bounded treewidth, while target sentences express first-order logic (
FO
) properties. Our logic captures problems that are not definable in FO and, moreover, may have instances of unbounded treewidth. Our main result is that, for this compound logic, model-checking can be done in quadratic time on minor-free graphs. The proposed logic can be seen as a general framework to capitalize on the potential of the
irrelevant vertex technique
. It gives a way to deal with problem instances of unbounded treewidth, for which Courcelle’s theorem does not apply. The proof of our meta-theorem combines novel combinatorial results related to the Flat Wall theorem along with elements of the proof of Courcelle’s theorem and Gaifman’s theorem. Our algorithmic meta-theorem encompasses, unifies, and extends the known meta-algorithmic results for
CMSO
and
FO
on minor-closed graph classes.
Few Images, Many Insights
: Illicit Content Detection Using a Limited Number of Images
Authors: Cascavilla Giuseppe , Catolino Gemma , Conti Mauro , Mellios Dimos , Tamburri Damian
Published: September 2024

The anonymity and untraceability benefits of the dark web increased its popularity exponentially. The cost of these technical benefits is that such anonymity has created a suitable womb for illicit activity. Hence—in collaboration with cybersecurity practitioners and law-enforcement agencies—the research community provided approaches for recognizing and classifying illicit activities. Most of these approaches exploit textual content from dark web markets, whereas few used images that originated from them. This article investigates alternative techniques for recognizing illegal activities from images. The significant contributions of our work are threefold: (a) We investigate label-agnostic learning techniques like One-Shot and Few-Shot learning that use Siamese Neural Networks. Our approach manages to handle small-scale datasets with promising accuracy. In particular, the Siamese Neural Network approach reaches 90.9% on 5-Shot experiments over a 10-class dataset. (b) This study’s satisfactory findings facilitate the creation of potent tools to assist authorities in identifying illicit content on the Web. Moreover, our proof-of-concept approach demonstrated the ability to recognize illegal images using a limited number of files, reducing the time constraint in collecting illegal images. (c) We provide a complete labeled dataset of 3,570 images from 55 different categories from dark web markets that can be used for future research activities.
Evaluation and Upscaling of Impregnated La0.20Sr0.25Ca0.45TiO3 Fuel Electrodes for Solid Oxide Electrolysis Cells
Authors: Price R. , Fuente Cuesta A. , Bausinger H. , Longo G. , Naden A. B. , Grolig J. G. , Mai A. , Irvine J. T. S.
Published: September 2024

Recent research into Rh and Ce0.80Gd0.20O1.90-impregnated La0.20Sr0.25Ca0.45TiO3 fuel electrodes for solid oxide fuel cells has demonstrated the high-stability of these material sets to a variety of harsh operating conditions at small scales (1 cm2 active area button cells), as well as commercial scales (100 cm2 cells) in short stacks (5 cells) and full micro-combined heat and power systems (60 cells). In this work, the authors present a comprehensive evaluation of the ability of these novel titanate-based materials to function as fuel electrodes in solid oxide electrolysis cells (SOECs). Short-term and durability testing of button cell scale SOECs highlighted the limited stability of lanthanum strontium manganite-based air electrodes, under CO2 and steam electrolysis conditions, with lanthanum strontium cobaltite ferrite-based air electrodes offering improved degradation characteristics. Upscaling of this optimized cell chemistry to a 16 cm2 active area SOEC and testing under CO2, CO2/H2O and H2O electrolysis conditions demonstrated encouraging performance over a period of ∼600 h, with stable co-electrolysis performance at ∼−7.5 A at 1.47 V for the first 100 h.
Influence of Temperature on the Performance of Metal Semiconductor Metal Photodetector Fabricated by Pure and Cationic Doped (Mg2+ and Cu2+) SnO2 Nanoparticles
Authors: Paul Jipsa , P Puviarasu , P Atheek , Palanisami Sanjeevi
Published: September 2024

Research based on various temperatures always provides beneficial awareness in the fabrication of a vital photodetector for significant applications. Increasing temperature and including dopants in photodetector materials will influence the functioning of the photodetector. This study included the influence of temperature on pure and doped SnO2 photodetectors. The crystal structure of stannic oxide has been modified by adding cationic dopants, namely Mg2+ and Cu2+, through co-precipitation techniques. Various characterization techniques were employed to examine the impact of Mg2+ and Cu2+ on the Sn4+ lattice. The electrical properties of the materials were studied at different temperatures using the Hall effect. Pure SnO2, Mg-doped SnO2, and Cu-doped SnO2 nanoparticles were synthesised separately and used as photodetectors using fluorine-doped tin oxide film as a conductive medium. The fabricated photodetectors are optimized by current-voltage characteristics at different temperatures. The effects of defects in crystal structure, oxygen vacancies, carrier concentration, and temperature on the photodetectors were studied. Comparative studies of pure and doped SnO2 photodetectors revealed that temperature and crystal defects play a significant role in photoconduction.
Sensing at Your Fingertip: On-Glove Electrochemical Sensor for Copper Detection on Vine Leaves
Authors: Raucci Ada , Miglione Antonella , Manganiello Gelsomina , Cimminella Carmen , Moio Luigi , Woo Sheridan L. , Wang Joseph , Cinti Stefano
Published: September 2024

Intensive use of copper-based pesticides in agriculture can impact human health and biodiversity: the accumulation of this metal in soil negatively affects crop yields. There is growing interest in developing new tools that are capable of monitoring copper occurrence in agricultural contexts through the use of quick and user-friendly approaches for non-specialists, e.g., farmers. This work focuses on the development of a glove-based electrochemical sensor, enhanced with gold nanoparticles, for the detection of copper ions on leaves. The developed device proved was capable of detecting copper ions contained in a copper-based pesticide commonly used in agriculture (Cupravit Bio Advanced). The on-glove analytical device was characterized using garden leaf as the model system and subsequently applied to on-site detection of copper ions on vine leaf treated with Cupravit Bio Advanced. The procedure was very facile: sampling was carried out by touching the leaf with the strip and the stripping-voltammetric measurement was performed by adding a few microliters of an acidic solution to the strip. The on-glove approach allowed evaluation of the level of copper-based pesticide used, avoiding complex and time-consuming tasks. Such operation opens up a wide range of possibilities for improving precision agriculture and sustainable development at the point-of-need for the use of non-specialists.
Cost‐Effectiveness Analysis of the Drugs Used in Oncology Department at a Tertiary Care Hospital in India
Authors: Kumar Arvind , Kumar Ranjeet , Saxena Vikas
Published: September 2024

Introduction: Nearly everyone in our society is concerned about the financial cost of healthcare. The aim to reduce health‐care costs motivates us to seek out therapies that deliver the highest possible value, depending in part on comparable economic evaluations. Cost‐effectiveness analysis is a sort of economic research in which the relative costs and outcomes of two or more competing methodologies are examined.

Aim/Objective: To conduct a cost‐effectiveness study of various cancer therapy interventions. To analyze the individual’s demographic details, health parameters, treatment outcomes, and costs.

Methods: This is an observational study that was conducted at Guru Gobind Singh Medical College and Hospital, Punjab, India, for the duration of 6 months (December 2022 to May 2023) according to STROBE guidelines.

Results: This observational study comprised 360 individuals, with the exception of pregnant women as well as patients who declined to participate. During this investigation, it was discovered that the bulk of patients were admitted to the IPD (In‐Patient Department) 238 (66.1%) at Guru Gobind Singh Medical College and Hospital in Faridkot, Punjab, India. The patients’ mean ages and weights were (M = 42.51, SD = 12.31) years and (M = 58.24, SD = 7.96) kg. Female patients scored higher than male patients (60.3%, 217). A linear regression test was performed to determine the link between the total expense of therapy (dependent variable) and each patient’s per capita income each month (independent variable). The result was significant (p = 0.001). A one‐way analysis of variance was used to compare the total expense of treatment with the type of therapy; the test yielded significant results (p = 0.001).

Conclusion: The present research shows the correlation between cost and other dependent variables utilizing various statistical analytic approaches. The cost‐effectiveness of cancer treatment must be evaluated individually, taking into account the patient’s health, choices, and overall prognosis.
Effect of Diets Supplemented With Yeast, Chitin, and Chitosan on the Growth, Immune, and Antioxidant Responses of the Freshwater Prawn Cryphiops (Cryphiops) caementarius
Authors: Reyes-Avalos Walter , Azañero-Díaz Carlos , Melgarejo-Velasquez Gladis , Yzásiga-Barrera Carmen , Alegre-Calvo Brian , Lezama-Salazar Roberto
Published: September 2024

The purpose of the present research was to evaluate the effect of diets supplemented with activated yeast, crude chitin, and chitosan on the growth, immune, and antioxidant response of freshwater prawn Cryphiops (Cryphiops) caementarius. Adult male prawns were kept in individual culture vessels installed in aquarium tanks. The basal diet (control) was supplemented with activated Saccharomyces cerevisiae yeast (60 g/kg), crude chitin (20 g/kg), and chitosan (1 g/kg). Each dietary treatment consisted of three replicates. The diet supplemented with activated yeast causes greater growth, as well as a greater number of total hemocytes (82.54 × 105 cells/mL), semigranular (59 × 105 cells/mL), and granular (18.67 × 105 cells/mL) hemocytes and without atypical hemocytes. Furthermore, a higher number of hemocytes positive for prophenoloxidase (98%), a shorter hemolymph clotting time (42.87 s), a higher activity of acid phosphatase (12.50 U/mL) and glutathione‐S‐transferase (GST) (0.186 U/mL) were also observed in dietary yeast group. On the contrary, there were no differences in the activity of superoxide dismutase (SOD) enzyme in prawns from any dietary treatment. Results from this research demonstrate for the first time that the diet containing activated yeast increases the growth and immune response of the freshwater prawn through a significant increase in hemocyte and acid phosphatase levels, a decrease in hemolymph clotting time, and a greater number of proPO‐positive hemocytes. However, activated yeast is not effective in increasing the activity of antioxidant enzymes SOD and GST. Therefore, the activated yeast diet can be useful to improve the aquaculture production of C. (C.) caementarius and possibly of other commercially important crustaceans.
The Substitution of Fish Meal or Chicken Meal With Yeast Culture in Diets of Bullfrogs (Lithobates catesbeianus): Growth Performance, Serum Biochemical Indices, Intestinal Digestive Enzyme, Hepatic Antioxidant, and Hepatic and Intestinal Histology
Authors: Chen Yun-Feng , Sun Zhong-Chao , Yang Xu , Zheng Yu-Fei , Wang Yuan-Yuan , Li Xiao-Qin , Leng Xiang-Jun
Published: September 2024

The aim of this study was to reveal the effects of yeast culture replacing fish meal (FM) or chicken meal (CM) on the growth performance, serum biochemical indexes, intestinal digestive enzyme activities, hepatic antioxidant, and hepatic and intestinal histology of bullfrog (Lithobates catesbeianus). The basal diet contained 100 g/kg FM and 100 g/kg CM, and then yeast culture was used to decrease FM or CM level to 75 and 50 g/kg with yeast culture inclusion of 32 and 64 g/kg, respectively, resulting in five groups of isonitrogenous diets (control, FM75, FM50, CM75, and CM50). A total of 450 bullfrogs (45.5 ± 0.4 g initial weight) were fed the five diets for 50 days. (1) The FM50 group presented significantly lower weight gain, condition factor, hind leg index, and higher feed conversion ratio than the control group, while the other three groups of FM75, CM75, and CM50 showed no significant difference in growth performance when compared to the control group. (2) The serum triglyceride content of FM50 group was significantly lower, while the alkaline phosphatase activity was significantly higher than those of the control group. The serum total cholesterol levels were significantly lower in the CM50 group compared to the control group. (3) In intestinal digestive enzyme activities, the trypsin and α‐amylase activities in the CM75 and CM50 groups, the trypsin activity in the FM75 group, and lipase activity in the CM50 group were all significantly higher than those in the other groups. (4) The replacement of 50% FM with yeast culture (FM50 and CM50 groups) promoted the total antioxidant capacity in the liver, but compared to the control group, the intestinal villi height and muscularis propria thickness in the FM50 group were significantly lower. There was no difference (P > 0.05) in liver histology among all the groups. In conclusion, in a basal diet containing 100 g/kg FM and 100 g/kg CM, 32.0 and 64.0 g/kg yeast cultures could successfully replace 25% of dietary FM and 50% of dietary CM without negative effects on the growth performance, serum biochemical indexes, and hepatic and intestinal health of bullfrogs.
Image Super‐Resolution Reconstruction Based on the Lightweight Hybrid Attention Network
Authors: Yuezhong Chu , Kang Wang , Xuefeng Zhang , Heng Liu
Published: September 2024

In order to solve the problem that the current image super‐resolution model has too many parameters and high computational complexity, this paper proposes a lightweight hybrid attention network (LHAN). LHAN consists of three parts: shallow feature extraction, lightweight hybrid attention block (LHAB), and upsampling module. LHAB combines multiscale self‐attention and large‐core attention. In order to make the network lightweight, multiscale self‐attention block (MSSAB) improves the self‐attention mechanism and uses windows of different sizes for group calculations. At the same time, in large‐core attention, we use depth‐based attention. Separate convolutions are used to reduce parameters. While keeping the receptive field unchanged, a normal convolution and a dilated convolution are used to replace the large kernel convolution. The four times super‐resolution experimental results on five data sets, including Set5 and Set14, show that our proposed method performs well in peak signal‐to‐noise ratio (PSNR) and structural similarity (SSIM). Specifically, in the benchmark data set on Urban, compared with SwinIR, the PSNR index of our method is improved by 0.10 dB. In addition, the parameter amount and calculation amount (floating point operations (FLOPs)) of our method are reduced by 315K and 16.4 G, respectively. Our proposed LHAN not only reduces the number of parameters and calculations but also achieves excellent performance in reconstruction quality.
Hierarchical Deep Learning for Bearing Fault Detection in BLDC Motors Using Time‐Frequency Analysis
Authors: Ali Ahmed K. , Rafa Abed Wathiq
Published: September 2024

This paper presents new hierarchical image‐based time‐frequency convolutional neural network (HTFICNN) for sorted bearing fault detection in brushless DC (BLDC) motors. The HTFICNN combines three different time‐frequency visualisation methods: scalogram, spectrogram, and Hilbert spectrum for the transformation of current and vibration signals into time‐frequency information (TFI). We use three different convolutional layers to extract features from three generated TFIs. We detect the targets using three patterns generated by the convolutional layers, utilizing three deep network structures, each containing a softmax classifier that identifies one pattern out of three. Using a three‐pattern approach, the hierarchical fusion classification method then realizes the final target decision. We tested the proposed HTFICNN with data from BLDC motors and found that it works better than other deep learning models to detect bearing faults. Moreover, this work contributes to the advancement of fault diagnosis and predictive maintenance for BLDC motors, with potential applications in other fault detection scenarios.
Disparities in Plasma Homocysteine Levels Between Early‐Onset and Late‐Onset Depression
Authors: Wang Tianle , Wang Qiang , Zhou Huarong , Zhong Xiaomei , Dai Ying-Chun , Zhao Jiubo , Li Zezhi , Ning Yuping
Published: September 2024

Background: Elevated homocysteine levels and late‐life depression are risk factors for cognitive decline: a comparative study highlighted the association of late‐onset depression (LOD) with more significant cognitive deficits and brain pathology than early‐onset depression (EOD). Limited research has explored the possible interaction between homocysteine levels and their correlation with cognitive performance in patients with EOD and LOD.

Methods: Fifty‐seven individuals with EOD, 56 with LOD, and 89 matched healthy controls (HC) were recruited. Global cognition, memory, execution, language, attention, visuospatial skills, and plasma homocysteine levels were examined.

Results: Compared with HC and patients with EOD, patients with LOD had higher plasma homocysteine levels (p < 0.05), with no significant difference between HC and patients with EOD (p > 0.05). Furthermore, homocysteine levels and diagnosis groups showed significant main effects on depression and cognition, with no significant interaction effects being observed. Additionally, plasma homocysteine levels were negatively correlated with global cognition, attention, visuospatial skills, and executive function in patients with LOD (p < 0.05).

Conclusions: Compared with HC and patients with EOD, elevated homocysteine levels in patients with LOD were independently associated with cognitive performance. The potential therapeutic efficacy of homocysteine‐lowering B‐vitamin supplementation could be explored as a viable intervention to mitigate the documented debilitating effects of cognitive deficits in this population.
Körperbezogene repetitive Verhaltensstörungen: Ein unterdiagnostiziertes und unterbehandeltes Störungsbild – Diagnostik, Klassifikation und Behandlung
Authors: Hoyer Luca Noemi , Schmotz Stella , Jelinek Lena , Moritz Steffen
Published: September 2024

Hintergrund: Die körperbezogenen repetitiven Verhaltensweisen (body focused repetitive behaviors; BFRBs) subsumieren eine Gruppe von Störungsbildern an der Schnittstelle von klinischer Psychologie/Psychiatrie, Dermatologie und Zahnheilkunde. Ohne entsprechende Behandlung neigen BFRBs zur Chronizität und können zu gravierenden körperlichen und psychischen Folgeproblemen führen. Ungeachtet der hohen Prävalenz (ca. 24 % der Erwachsenen in der allgemeinen Bevölkerung berichten Fälle mit Leidensdruck und/oder sichtbaren körperlichen Folgen im Laufe ihres Lebens) gibt es weiter große Wissenslücken aufseiten Behandelnder. Zusammenfassung: Aufgrund der körperlichen Folgeerscheinungen sind überwiegend Allgemeinmediziner:innen und Dermatolog:innen die erste Anlaufstelle für Betroffene. In den aktuellen Klassifikationssystemen sind Trichotillomanie (pathologisches Ausreißen der Haare) und Dermatillomanie (pathologisches Manipulieren der Haut) als eigenständige Diagnosen gelistet und werden entweder als zwangsverwandte Störungen (DSM-5) oder als Störungen der Impulskontrolle (ICD-10) klassifiziert. Weitere Verhaltensweisen, die zu den BFRBs gerechnet werden, sind Cavitadaxia (Lippen-Wangen-Beißen), Nägelkauen, Wach-Bruxismus sowie Daumenlutschen im Erwachsenenalter. Verhaltenstherapeutische Maßnahmen sind aktuell die Behandlung der Wahl. Den Goldstandard stellt das Habit-Reversal-Training (HRT) dar, dessen Wirksamkeit mehrfach empirisch nachgewiesen wurde. Effektive Selbsthilfeverfahren sind neben der Selbsthilfeadaption des HRT, die Entkopplung, die Entkopplung in sensu und das Habit Replacement. Kernaussage: Der Artikel vermittelt einen Überblick über die einzelnen Störungsbilder von BFRBs, differenzialdiagnostische Schwierigkeiten sowie Behandlungsmöglichkeiten.
Effectiveness of Digital Interventions in Reducing Occupational Stress: A Systematic Review
Authors: Indra Bima , Palmasutra Valie , Setyawan Febry Afrianto
Published: September 2024

Occupational stress is the response people may have when presented with work demands and pressures that are not matched to their knowledge and abilities, challenging their ability to cope. It is a pervasive concern in modern work environments, impacting workers’ well-being and organizational productivity. Current available methods to manage workers’ stress include providing psychologist consultations and using digital intervention. Digital interventions, including smartphone apps and website programs, have emerged as accessible tools for stress reduction. However, there is a need to assess their effectiveness systematically. A systematic review encompassed randomized controlled trials (RCTs) from the inception to May 2024. A comprehensive search in four electronic databases identified 15 eligible RCTs. Of a total of 15 included studies, all studies demonstrated a significant reduction in occupational stress with the use of digital interventions. Interventions varied in duration, frequency, and delivery platforms, with smartphone-based applications being predominant. Common intervention components included meditation, coping stress management, and nutritional and exercise content. Positive effects on worker mental health were observed to persist for up to 3–12 months post-intervention. The findings underscore the potential of digital interventions to promote employee well-being and contribute to healthier and more productive work environments. Digital interventions offer promising avenues for addressing occupational stress and promoting worker well-being.
Tranilast Treatment Prevents Chronic Radiation-Induced Colitis in Rats by Inhibiting Mast Cell Infiltration
Authors: Seo Kyung Jin , Alam Mohammad Rizwan , Abdul-Ghafar Jamshid , Kim Sang Woo , Kim Hyung Keun , Choi Hyun Ho , Sin Seung Ho , Lee Hae Kyung , Chae Hiun Suk
Published: September 2024

Introduction: Mast cells are the principal cells involved in acute and chronic colitis due to radiation, known as radiation-induced colitis (RIC). In this study, we investigated whether pretreatment with tranilast, a mast cell inhibitor, could alleviate chronic RIC. Methods: A total of 23 Sprague-Dawley rats were randomly divided into three groups: control group (n = 5), radiation group (RG, n = 9), and tranilast-pretreated radiation group (TG, n = 9). The rats in the RG and the TG were irradiated in the pelvic area (1.5 cm from the anus) with a single dose of 20 Gy under general anesthesia. Tranilast (100 mg/kg) was administered intraperitoneally to the rats of the TG for 10 days, starting from the day of pelvic radiation. Ten weeks after radiation, the rats were euthanized. Rectal tissue samples were histologically evaluated for the total inflammation score (TIS) and mast cell count. The expression of MUC2, MUC5AC, and matrix metalloproteinase-9 (MMP-9) was also assessed immunohistochemically. Results: Both the TIS and specific components of TIS such as epithelial atypia, vascular sclerosis, and colitis cystica profunda (CCP) were significantly higher in the RG than in the TG (p = 0.02, 0.038, 0.025, and 0.01, respectively). Thein number of infiltrating mast cells was significantly higher in the RG than in the TG (median [range]: 20 [3−54] versus 6 [3−25], respectively; p = 0.034). Quantitatively, the number of MMP-9-positive cells was significantly higher in the RG (23.67 ± 19.00) than in the TG (10.25 ± 8.45) (mean ± standard deviation; p < 0.05). TIS and MMP-9 exhibited a strong association (correlation coefficient r = 0.56, p < 0.05). Immunohistochemically, the mucin-lake of CCP showed no staining for MUC5AC but was stained positive for MUC2. Conclusion: Tranilast pretreatment of chronic RIC showed an anti-inflammatory effect associated with the reduction of mast cell infiltration and MMP-9 expression.
Prognostic Value of Shock Index Creatinine in Patients with Severe Aortic Stenosis Undergoing Transcatheter Aortic Valve Replacement
Authors: Yang Bangyuan , Wang Changjin , Zhou Ting , Sun Yinghao , Zheng Shengneng , Chen Jiaohua , Luo Songyuan , Luo Jianfang , Li Jie
Published: September 2024

Introduction: Shock index (SI) and its derivatives have been reported to have prognostic value in various cardiovascular diseases. This study aims to ascertain the utility of shock index creatinine (SIC) in predicting mid-term mortality among patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Methods: We conducted a retrospective analysis of 555 patients with severe AS who underwent TAVR from April 2016 to March 2023. SIC was calculated as (SI × 100) – estimated creatinine clearance (CCr). The primary endpoint was all-cause mortality during the follow-up period, and secondary endpoints included in-hospital complications as defined by the Valve Academic Research Consortium-3 (VARC-3) criteria. Patients were stratified into two groups based on the optimal cutoff value determined by the receiver-operating characteristic (ROC) curve. Cox regression analysis was employed to identify independent predictors of all-cause mortality. Additionally, restricted cubic spline (RCS) was deployed to illustrate the relationship between SIC and mortality risk. The predictive performance of risk scores was evaluated using the area under the ROC curve (AUC). Results: Over a mean follow-up period of 21.5 months, there were 51 cases of all-cause mortality. Patients with a high SIC, identified by a cutoff of 16.5, exhibited a significantly higher cumulative all-cause mortality compared to those with a low SIC (18.3% vs. 5.2%, p < 0.001; adjusted HR = 2.188; 95% CI 1.103–4.341, p = 0.025). Patients with a high SIC were older (p = 0.002) and exhibited a higher prevalence of frailty (p < 0.001). Furthermore, they exhibited a heightened probability of moderate or severe mitral regurgitation (p < 0.001), tricuspid regurgitation (p < 0.001), and pulmonary hypertension (p < 0.001) compared to those with a low SIC. In terms of perioperative complications, acute kidney injury (10.1% vs. 3.9%, p = 0.008) and bleeding (13.6% vs. 6.7%, p = 0.014) were more prevalent in patients with a high SIC. The RCS demonstrated a positive correlation between SIC and all-cause mortality rate. Furthermore, incorporating high SIC into the STS score improved its predictive value for 1-year all-cause mortality (AUC: 0.731 vs. 0.649, p = 0.01). Conclusion: Patients with a high SIC are more likely to experience frailty and cardiac damage and exhibit an increased in-hospital and mid-term mortality rate. SIC may provide additional information for risk stratification of patients undergoing TAVR.
Novel 10q21.1-q22.1 Duplication in a Boy with Minor Facial Dysmorphism, Mild Intellectual Disability, Autism Spectrum Disorder-Like Phenotype, and Short Stature
Authors: Toral-López Jaime , González-Huerta Luz María
Published: September 2024

Introduction: Duplications reported in 10q21-q22 include borderline to moderate intellectual disability, growth retardation, autism, attention deficit hyperactivity disorder, and minor craniofacial dysmorphism. Case Presentation: We present a patient with a novel 14.7-Mb de novo interstitial duplication at 10q21.1-q22.1 delineated by a high-definition (HD) single nucleotide polymorphism (SNP) array. The boy had minor facial dysmorphism, mild intellectual disability, an autism spectrum disorder-like phenotype, and short stature. Conclusion: This is the first case in which a novel 10q21.1-q22.1 duplication was detected by the HD SNP array, expanding the spectrum of duplications seen in 10q21-q22. This report provides a detailed clinical examination of a patient with a 10q21.1-q22.1 duplication and suggests that brain development and cognitive function may be affected by an increased dosage sensitivity of the involved JMJD1C and EGR2 genes. This case contributes to the understanding of the genotype-phenotype relationship for genetic counseling and provides further evidence for the identification of a novel microduplication syndrome in 10q21-q22.
Business intelligence for decision-making in the collection area of a municipality
Authors: Daza Alfredo , Salazar Casas Daniela Belen , Alarcón Cajas Yohan Roy
Published: September 2024

The large volume of data in systems in the collection area leads to the lack of adequate management of information, as well as dissatisfaction on the part of the user. The purpose of the study is to implement business intelligence (BI) technology to improve the effectiveness of the information and the satisfaction of the attention of the users of a municipality of Lima in the area of collection; therefore, the phases of the Ralph Kimball method with the following phases: project planning; definition of requirements; design of technological architecture; in the dimensional modeling a snowflake scheme was made with 9 dimensions and 1 table made, in the physical design it was implemented in the MySQL management system and in the extract, transform, and load (ETL) development the migration, transformation and cleaning of the data from the online transaction processing (OLTP) database to online analytical processing (OLAP) was executed; obtaining as results that BI managed to increase the level of information efficiency by 53.32%, as well as the level of user satisfaction (LUS) by 1.90%, concluding that BI allows to meet the needs of the user since it maintains a clean, secure and reliable data structure.
Speech emotion recognition with optimized multi-feature stack using deep convolutional neural networks
Authors: Fadhil Muhammad Farhan , Zahra Amalia
Published: September 2024

The human emotion in communication plays a significant role that can influence how the context of the message is perceived by others. Speech emotion recognition (SER) is one of a field study that is very intriguing to explore because human-computer interaction (HCI) related technologies such as virtual assistant that are implemented nowadays rarely considered the emotion contained in the information relayed by human speech. One of the most widely used ways to perform SER is by extracting features of speech such as mel frequency cepstral coefficient (MFCC), mel-spectrogram, spectral contrast, tonnetz, and chromagram from the signal and using a one-dimensional (1D) convolutional neural network (CNN) as a classifier. This study shows the impact of implementing a combination of an optimized multi-feature stack and optimized 1D deep CNN model. The result of the model proposed in this study has an accuracy of 90.10% for classifying 8 different emotions performed on the ryerson audio-visual database of emotional speech and song (RAVDESS) dataset.
A study on the impact of layout change to knowledge distilled indoor positioning systems
Authors: Mazlan Aqilah , Ng Yin Hoe , Tan Chee Keong
Published: September 2024

Convolutional neural networks (CNN)-based indoor positioning systems (IPS) have gained significant attention over the past decade due to their ability to provide precise localization accuracy. However, the use of CNNs in these systems comes with a higher computational cost. To tackle this issue, recent studies have introduced knowledge distilled positioning schemes to mitigate the computational burden. Despite the clear possibility of performance degradation due to signal fluctuations, there remains a lack of investigation into the performance of knowledge distilled and CNN based indoor positioning schemes in dynamic indoor environment. To fill this research gap, this paper investigates the practicality of implementing knowledge distilled-based indoor positioning schemes in real-world by analyzing the impact of indoor layout change on these schemes. Results demonstrate that in the case of layout change, the knowledge distilled-based indoor positioning schemes without teaching assistant can still achieve good performance, with an improvement of 11.56% in average positioning error compared to simple CNN model, while taking only 49.05% of the complex CNN model’s execution time. However, the knowledge distilled-based indoor positioning scheme with teaching assistant fails under the same condition as the inclusion of teacher assistant leads to increased error in modeling the received signal strengths (RSS) and locations relationship.