Fast Process Research Articles

Road Pothole Detection Model Based on Local Attention Resnet18-CNN-LSTM

Abstract. In response to the low detection accuracy and slow speed of existing road pothole detection methods, a road pothole classification detection model based on local attention Resnet18-CNN-LSTM (Long Short-Term Memory network) is proposed. On the basis of Resnet18, a local attention mechanism and a CNN-LSTM combined model are added to propose a road pothole detection model based on local attention Resnet18-CNN-LSTM. The local attention mechanism is used to accurately extract specific target feature values, CNN is used to extract the spatial features of the input data, and LSTM enhances the detection model's extraction of sequential features and performs classification, thereby improving the accuracy of the road and pothole model. Experimental results show that on the training set, the accuracy of the local attention mechanism-based ResNet18-CNN-LSTM model reached 99.2188%, which is an increase of 0.7813% and 2.3438% compared to the ResNet34-CNN-LSTM and ResNet50-CNN-LSTM models under the same conditions, respectively. On the test set, the model's accuracy was 93.4437%, an increase of 0.5437% and 1.9867% compared to the ResNet34-CNN-LSTM and ResNet50-CNN-LSTM models, respectively. After dealing with overfitting issues through early stopping, the detection accuracy of this model has significantly improved compared to the detection models based on ResNet34 and ResNet50, with an increase of 1.2% and 1.49% respectively. The model shows faster processing speed in identification time, effectively retains the correlation and sequence features of the data, overcomes the problem of gradient disappearance in deep networks, and thereby enhances the extraction capability of local target features of road pothole images. The above results indicate that the local attention mechanism-based ResNet18-CNN-LSTM model shows superior performance in road pothole detection.

Comparison of different diagnostic protocols for the detection of Toxocara spp. in faecal samples of cats and dogs

BackgroundToxocara canis and Toxocara cati are parasitic nematodes that occur worldwide. As embryonated Toxocara spp. eggs in the environment pose a zoonotic risk, especially for children, optimal diagnostic approaches are necessary for effective disease response and management, including surveillance. However, little is known about the performance of different diagnostic protocols for detecting Toxocara spp. in the faeces of cats and dogs, hampering movement towards an optimal diagnostic process. This study aimed to compare detection methods, including a newly developed sequential sieving protocol (SF-SSV) and a high-throughput multiplex qPCR-based method to facilitate epidemiological studies.MethodsSpecies-specific Toxocara spp. egg suspensions and canine and feline faecal samples from the field were used to estimate analytical and diagnostic sensitivity of the protocols. The performance of two automated DNA extraction protocols using enzymatic and mechanical lysis were compared by multiplex qPCR, targeting both T. canis and T. cati-specific genomic sequences. All samples were examined by microscopy-based techniques, the sedimentation flotation technique (SF) and a newly developed SF-SSV for the detection, enrichment and purification of parasite eggs. The costs and processing times necessary for all protocols were estimated and compared for both single samples and sets of 100 samples.ResultsTo detect Toxocara spp. eggs, SF-SSV showed the highest analytical sensitivity and a significantly higher diagnostic sensitivity than the DNA detection methods. Mechanical lysis performed better than enzymatic lysis for automated DNA extraction. In automated DNA extraction, 96-well plates performed better than 24-well plates. DNA detection and microscopy-based parasitological methods showed substantial agreement between the results generated by each method. Microscopy-based techniques required the lowest costs and least hands-on time for a single sample. However, when costs and labour were estimated for a set of 100 samples, the DNA detection protocol using 96-well plates for extraction revealed costs similar to SF-SSV and the fastest processing times.ConclusionsSF-SSV was superior in terms of analytical and diagnostic sensitivity for the detection of Toxocara spp. eggs. For larger sets of samples, multiplex qPCR-based DNA detection represents an alternative to microscopy-based methods, based on the possibility of faster sample processing at similar costs to SF-SSV, and the ability to provide species-specific diagnoses.Graphical

Phase change-mediated core-sheath 3D printing of hollow microlattice pseudocapacitive aerogel electrode with favorable electrochemical properties

Channel-interconnected regulation within 3D-printed pseudocapacitive electrode architecture to generate high active material loading/utilization and fast ion transport is pivotal but challenging for implementing high-performance pseudocapacitance system. Herein, we demonstrated an innovative phase change-mediated core-sheath direct ink writing (DIW) 3D printing strategy for controllably constructing pseudocapacitive hollow-microlattice graphene/NiCo2O4 aerogel (HGNA) electrode, with regular hollow channels in printed filaments and abundant well-interconnected hierarchical pores built by jointing tortuous pseudocapacitive graphene nanosheets. The unique architectural features facilitated highly efficient diffusion and infiltration of substance throughout the entire thick filaments from both “interior-exterior” and “exterior-interior” directions, thereby enabling high-level yet effective loading of active materials as well as unimpeded ion transport across the printed bulk-structured electrode. Kinetics analysis revealed that the capacitance of pseudocapacitive HGNA electrode was primarily contributed from fast kinetic process. An asymmetric device assembled with DIW-printed HGNA electrode boasted a high energy storage performance with capacitance of 3.43 F cm−2 and energy density of 1.01 mWh cm−2, while featuring remarkable cycling stability (87% after 8000 cycles) and superior capacity even at large electrode thickness. This work opens a promising route for processing rational pseudocapacitive electrode architectures toward high-capacity, fast-kinetics devices.

Photodiode-based focus monitoring in ultrashort-pulsed laser structuring of graphite anodes for lithium-ion batteries

In recent years, there has been an increased demand for elaborate monitoring techniques in laser material processing. This has been driven by the need for fast and cost-efficient quality assurance processes. At the same time, ultrashort-pulsed (USP) laser radiation has emerged as a promising technology for creating intricate microstructures in lithium-ion battery graphite anodes due to its high precision and negligible thermal impact. However, the integration of process monitoring in USP laser applications for graphite anode structuring is still unexplored. There is a lack of clarity on suitable sensors, observable parameters, and extractable process-relevant insights. The presented study addressed this gap by demonstrating the capability of state-of-the-art photodiode-based monitoring systems in collecting process-relevant data and deriving valuable insights. A sensor equipped with three photodiodes was employed to address these challenges. Exploratory data analysis and machine learning methodologies were leveraged to develop a data pipeline for processing the acquired information. The data were used to train convolutional neural networks that could accurately predict the focal position. At the same time, the limitations of traditional regression approaches could be shown. The findings advanced the understanding of the possibilities of process monitoring in USP laser applications and emphasized the significance of data-driven approaches in optimizing manufacturing processes.

Fast processing of gynecologic cancer tissue in Danish Cancer Biobank makes them well-suited for biomarker studies.

Gynecologic cancers remain a frequent and deadly diagnosis. Historically, treatment has focused on a "one size fits all" approach, but there is an urgent need for more personal medicine. Hence, to enhance personal medicine, new biomarkers are needed. Samples from the Danish Cancer Biobank (DCB) may be well-suited for biomarker studies, as the biobank contains samples from more than 100.000 cancer patients, and the samples are annotated with pre-analytical variables. The aim of this study was to investigate if the recorded pre-analytical variables indicate the gynecologic tissue in DCB are suited for biomarker studies. Data on processing time, transport time, and registration- and verification status were extracted from all patients with a gynecologic tissue sample collected between 2020 and 2022 in DCB. The mean processing time across centers was found to be 1.03 h (SD = 0.71), and the mean transport time was found to be 0.32 h (SD = 0.70). In total, 69% of the tissue samples were pathologically examined, and 91.5% of the pathologically examined samples were found to be concordant with the patient's final diagnosis. While differences were observed, 98% of the samples were processed within 3 h, indicating the majority of gynecologic tissue samples in DCB are of high quality and optimal for biomarker studies.

Eco-friendly flame retardant comprising chitosan-based effectively enhances the flame retardancy of wood with low weight percent gain

Nowadays, there are many types of flame retardants, whether halogenated or halogen-free, that can improve the flame retardancy of wood. However, they continue to pose a significant threat to our environment and cause a substantial increase in the weight gain rates after treatment. It is highly desirable yet challenging to develop an eco-friendly and efficient flame retardant with low weight gain rates. Here, we report a simple and fast process for making eco-friendly flame retardants (chitosan, gelatin, sodium phytate and clay) with weight gain rates of 3.7 %, which form excellent flame retardancy systems. This method can be used to create a 53.5 % reduction in peak heat release rate (pHRR) an 189 % increase in ignition time (cone colorimeter), and a 71.9 % reduction in peak temperature (alcohol spray lamps) compared to raw wood. The results displayed that the effect of flame retardancy (Decreased ratio for pHRR/Weight percent gain) was the best in the past three years. In addition, the flame retardancy mechanism is thoroughly analyzed using the techniques of Raman and so on. This study proposes a novel strategy featured by eco-friendly and simple preparation process for enhancing the flame retardancy of wood in important areas.

Improved the Sensitivity and Limit of Detection of Surface Alloying SERS Sensors by Controlling Mixing Ratio of Trimetallic (Ag-Au-Pd) Nanoparticles

In this study, three different types of hybrid structures SERS sensors made from different mixing ratio of trimetallic (Ag-Au-Pd) nanoparticles of [Au1: Ag1: Pd1] , [Au1: Ag2: Pd1] , [Au1: Ag2: Pd2] in surface alloying forms deposited on macro porous silicon (macroPsi) layer were created and extensively tested. By using a simple and fast immersion process, trimetallic (Ag-Au-Pd) nanoparticles were created utilizing ion reduction of numerous metallic salts on a macro porous silicon (macroPsi) layer. The macroPsi layers were created using a laser assisted etching (LAE) technique for 15 minutes with a constant density of approximately (28mA/c.m2). At a constant concentration (10-3 M) of HAu.Cl4, Ag.NO3 and Pd.Cl2 to synthesize Au-NPs, Ag-NPs and Pd-NPs, immersion processes with various mixing ratios were performed. The hybrid structures of SERS sensors were examined using XRD, FE-SEM, and Raman microscopes. The sensors were tested at different concentrations from 10-6 to 10-12 of MB target molecules. The SERS trimetallic sensors demonstrated a considerable reliance on hot spot zones among trimetallic nanoparticles. Higher enhancement factor with lower detection limit of Raman signal was obtained from [Au1: Ag2: Pd2] hybrid structures SERS sensor of about 1.5×1010 and 10-14 respectively, due to extra ordinary specific surface area and high surface density forming trimetallic nanoparticles . The variations of mixing ratio of trimetallic (Ag-Au-Pd) provide an effective pathway to develop the sensors performance towards detection of lower concentrations.

Direct Evidence of Breakdown of Spin Statistics in Ion-Atom Charge Exchange Collisions.

Recent experimental studies have questioned the validity of spin statistics assumptions, particularly in charge exchange processes occurring in atomic MeV collisions. Here, we study spin-resolved single electron capture processes in collisions between C^{3+} ions and helium within an energy range of 1.25-400 keV/u. Using high resolution reaction microscope and multielectronic theoretical approaches, we directly measure and calculate the true population information of the C^{2+}(1s^{2}2s2p ^{1,3}P) states at the time of electron capture, overcoming the previous experimental and theoretical difficulties. At the level of integral and scattering angle differential cross sections, our results demonstrate the breakdown of pure spin statistics arguments, especially at high impact energies where they are traditionally expected to be valid. These novel findings and conclusions raise intriguing questions both in the understanding of the electronic dynamics during such fast collisional processes and in exploring quantum manipulation of atomic and molecular reactivity.

Development of crystal optics for X-ray multi-projection imaging for synchrotron and XFEL sources.

X-ray multi-projection imaging (XMPI) is an emerging experimental technique for the acquisition of rotation-free, time-resolved, volumetric information on stochastic processes. The technique is developed for high-brilliance light-source facilities, aiming to address known limitations of state-of-the-art imaging methods in the acquisition of 4D sample information, linked to their need for sample rotation. XMPI relies on a beam-splitting scheme, that illuminates a sample from multiple, angularly spaced viewpoints, and employs fast, indirect, X-ray imaging detectors for the collection of the data. This approach enables studies of previously inaccessible phenomena of industrial and societal relevance such as fractures in solids, propagation of shock waves, laser-based 3D printing, or even fast processes in the biological domain. In this work, we discuss in detail the beam-splitting scheme of XMPI. More specifically, we explore the relevant properties of X-ray splitter optics for their use in XMPI schemes, both at synchrotron insertion devices and XFEL facilities. Furthermore, we describe two distinct XMPI schemes, designed to faciliate large samples and complex sample environments. Finally, we present experimental proof of the feasibility of MHz-rate XMPI at the European XFEL. This detailed overview aims to state the challenges and the potential of XMPI and act as a stepping stone for future development of the technique.

Diagnostic reasoning and cognitive error in emergency medicine: Implications for teaching and learning.

Accurate diagnosis in emergency medicine (EM) is high stakes and challenging. Research into physicians' clinical reasoning has been ongoing since the late 1970s. The dual-process theory has established itself as a valid model, including in EM. It is based on the distinction between two information-processing systems. System 1 rapidly generates one or more diagnostic hypotheses almost instantaneously, driven by experiential knowledge, while System 2 proceeds more slowly and analytically, applying formal rules to arrive at a final diagnosis. We reviewed the literature on dual-process theory in the fields of cognitive science, medical education and emergency medicine. The literature reflects two prominent interpretations regarding the relationship between the fast and slow phases and these interpretations carry very different implications for the training of clinical learners. One interpretation, prominent in the EM community, presents it as a "check-and-balance" framework in which most diagnostic error is caused by cognitive biases originating within System 1. As a result, EM residents are frequently advised to deploy analytical (System 2) strategies to correct such biases. However, such teaching approaches are not supported by research into the nature of diagnostic reasoning. An alternative interpretation assumes a harmonious relationship between Systems 1 and 2 in which both fast and slow processes are driven by underlying knowledge that conditions performance and the occurrence of errors. Educational strategies corresponding to this alternative have not been explored in the EM literature. In this paper, we offer proposals for improving the teaching and learning of diagnostic reasoning by EM residents.

Cognitive functions explain discrete parameters of normal walking and dual-task walking, but not postural sway in quiet stance among physically active older people.

Postural control is dependent on the central nervous system's accurate interpretation of sensory information to formulate and execute adequate motor actions. Research has shown that cognitive functions are associated with both postural control and fall risk, but specific associations are not established. The aim of this study was to explore how specific components of everyday postural control tasks are associated with both general and specific cognitive functions. Forty-six community-dwelling older adults reported their age, sex, physical activity level, falls and fall-related concerns. The following cognitive aspects were assessed: global cognition, executive functions, processing speed and intraindividual variability. Postural control was quantified by measuring postural sway in quiet stance, walking at a self-selected pace, and walking while performing a concurrent arithmetical task. Separate orthogonal projections of latent structures models were generated for each postural control outcome using descriptive and cognitive variables as explanatory variables. Longer step length and faster gait speed were related to faster processing speed and less intraindividual variability in the choice reaction test. Moreover, longer step length was also related to less fall-related concerns and less severe fall-related injuries, while faster gait speed was also related to female sex and poorer global cognition. Lower dual-task cost for gait speed was explained by the executive function inhibition and faster processing speed. Postural sway in quiet stance was not explained by cognitive functions. Cognitive functions explained gait speed and step length during normal walking, as well as the decrease of gait speed while performing a concurrent cognitive task. The results suggest that different cognitive processes are important for different postural control aspects. Postural sway in quiet stance, step time and gait variability seem to depend more on physical and automatic processes rather than higher cognitive functions among physically active older people. The relationships between cognitive functions and postural control likely vary depending on the specific tasks and the characteristics of different populations.

A novel approach to enhancing performance and endurance in GeS2 OTS devices using amorphous carbon doped W2N electrodes

Three–dimensional (3D) cross-point (X–point) memory has gathered interest for its fast data processing and high density, achieved by stacking memory with a selector device to prevent misinterpretation. Ovonic threshold switching (OTS) is a promising selector due to its reversible switching behavior. Although, OTS devices typically employ transition metal nitrides (TMN) such as TiNx, TaNx, and WNx for electrodes owing to their good stability, high melting points, and low resistivity, TMNs can diffuse and degrade device performance by recrystallizing with chalcogenide alloys. Amorphous carbon (a–C) can be a good alternative electrode material due to its low roughness, cost–effectiveness, high work function (WF), and excellent thermal stability. However, the high resistivity of a–C (∼ 150 mΩ–cm) increases threshold voltage (Vth), causing high power consumption. Therefore, combining both a–C and TMN materials can effectively obtain their advantages. This study explores the effect of varying a–C content in W2N electrodes on GeS2–based OTS selectors. The (W2N)1-xCx (0 ≤ x ≤ 0.25) electrodes were deposited using DC magnetron co–sputtering. The phase of (W2N)1-xCx (0 ≤ x ≤ 0.25) films transformed from polycrystalline to amorphous with increasing x. Devices with (W2N)1-xCx/GeS2/W2N structure showed decreased Vth and off current, improving from 4.8 to 3.8 V and 8.0–4.17 nA, respectively. The subthreshold slope, distance between traps, and interface trap density (Nit) were extracted using the Pool–Frenkel model. The reduced Vth may be attributed to a higher WF and lower Nit with increasing x. The device’s lifetime improved up to 1.0 × 109 pulses for the highest a–C content in (W2N)1-xCx (0 ≤ x ≤ 0.25) electrodes.

Awareness and Attitudes Towards Open Access Predatory Publications Among the Academic Staff Members of Faculty of Management Studies and Commerce, University of Jaffna, Sri Lanka

The scholarly community is now dealing with a serious issue with predatory journals. It might be difficult for authors to identify predatory publications apart from reputable ones. The purpose of this study is to investigate the academic staff members of the Faculty of Management Studies and Commerce, University of Jaffna, Sri Lanka on awareness of predatory publications and open access. The research methodology used in this study to gauge participants' knowledge of "open access" and "predatory publishing" was a questionnaire survey. Data collection involved the use of a pretested questionnaire. The permanent academic staff members affiliated with the Faculty of Management Studies and Commerce, university of Jaffna comprised the study's population. A link to an online survey was shared with every one of the faculty's fifty-two academic staff members. The response rate of the study was 67.30 %. MS Excel was used for the data analysis to describe the data in frequencies, percentages and rank orders of responses.Socio demographic details shows that, highest number of respondents are female (57.14%), completed master/MPhil (51.42%), senior lecturer (57.14%) and interested in marketing (28.57%) as their research discipline. Respondents expressed their priority order for the factors considered to select journal to submit manuscript for publications, journal indexing is the highest priority. All the respondents have an idea about the open access publishing system. Respondents are expected to publish in open access journals because of high visibility, increasing citation number, prestigious journals and fast publication process in a frequency order. The result of the survey shows that, 97.15% of the respondents are knowledgeable about predatory publishing. Majority of the respondents are characterized, the predatory journals are, no insufficient peer review process, and Beall’s list of predatory journals used by the high number of respondents to differentiate legitimate journals from predatory journals. More than half of the respondents are satisfied with the services provided by the library to avoid publishing in predatory journals. Responses are summarized for each of the 8 statements about the impact of publishing in predatory journals. Almost all the statements are agreed by the respondents other than the statement of “Articles published in predatory journals are poor in quality”. Highest agreement found for the statement 3 which is “Predatory publications are not considered for any academic reward” in which 14out of 35 were strongly agreed and followed by the statement 2 “many researchers published articles due to lack of awareness about predatory publication” (13 out of 35). Finally respondents are suggested to organize more awareness session on open access publishing and journal selection to avoid predatory publishing.

Molecular Engineering of a Tumor-Targeting Thione-Derived Diketopyrrolopyrrole Photosensitizer to Attain NIR Excitation Over 850 nm for Efficient Dual Phototherapy.

Photosensitizers with near-infrared (NIR) excitation, especially above 800 nm which is highly desired for phototherapy, remain rare due to the fast nonradiative relaxation process induced by exciton-vibration coupling. Here, a diketopyrrolopyrrole-derived photosensitizer (DTPA-S) is developed via thionation of carbonyl groups within the diketopyrrolopyrrole skeleton, which results in a large bathochromic shift of 81 nm, endowing the photosensitizer with strong NIR absorption at 712 nm. DTPA-S is then introduced with a functional biomolecule (N3-PEG2000-RGD) via click reaction for the construction of integrin αvβ3 receptor-targeted nano-micelles (NanoDTPA-S/RGD), which endows the photosensitizer with a further superlarge absorption redshift of 138 nm, thus extending the absorption maxima to ≈850 nm. Remarkably, thiocarbonyl substitution increases the nonbonding characters in frontier molecular orbitals, which can effectively suppress the nonradiative vibrational relaxation process via reducing the reorganization energy, enabling efficient reactive oxygen species (ROS) generation under 880 nm excitation. Screened by in vitro and in vivo assays, NanoDTPA-S/RGD with high water solubility, excellent tumor-targeting ability, and photodynamic/photothermal therapy synergistic effect exhibits satisfactory phototherapeutic performance. Overall, this study demonstrates a new design of efficient NIR-triggered diketopyrrolopyrrole photosensitizer with facile installation of functional biomolecules for potential clinical applications.

An Inverse recursive algorithm to retrieve the shape of the inaccessible dielectric objects

A regularized electromagnetic iterative inverse algorithm is formulated and implemented to reconstruct the shape of 2D dielectric objects using the far-field pattern of the scattered field data. To achieve this, an integral operator that maps the unknown boundary of the object onto the far-field pattern of the scattered field is defined and solved for the unknown boundary. The addressed inverse problem has an ill-posed nature and inherits nonlinearity. To overcome these, the proposed solution is linearized via Newton and regularized by Tikhonov in the sense of least squares. Besides, the dominance of the shadow region in the inverse-imaging process is exceeded by considering the superposition of multi-incoming plane waves, leading to less computational cost and a very fast inversion process. Comprehensive numerical analyses are carried out to ascertain the algorithm's feasibility, revealing that it is very efficient and promising.

Examining motor evidence for the pause-then-cancel model of action-stopping: insights from motor system physiology.

Stopping initiated actions is fundamental to adaptive behavior. Longstanding, single-process accounts of action-stopping have been challenged by recent, two-process, "pause-then-cancel" models. These models propose that action-stopping involves two inhibitory processes: 1) a fast Pause process, which broadly suppresses the motor system as the result of detecting any salient event, and 2) a slower Cancel process, which involves motor suppression specific to the cancelled action. A purported signature of the Pause process is global suppression, or the reduced corticospinal excitability (CSE) of task-unrelated effectors early on in action-stopping. However, unlike the Pause process, few (if any) motor system signatures of a Cancel process have been identified. Here, we used single- and paired-pulse transcranial magnetic stimulation (TMS) methods to comprehensively measure the local physiological excitation and inhibition of both responding and task-unrelated motor effector systems during action-stopping. Specifically, we measured CSE, short-interval intracortical inhibition (SICI), and the duration of the cortical silent period (CSP). Consistent with key predictions from the pause-then-cancel model, CSE measurements at the responding effector indicated that additional suppression was necessary to counteract Go-related increases in CSE during action-stopping, particularly at later timepoints. Increases in SICI on Stop-signal trials did not differ across task-related and task-unrelated effectors, or across timepoints. This suggests SICI as a potential source of global suppression. Increases in CSP duration on Stop-signal trials were more prominent at later timepoints and were related to individual differences in CSE. Our study provides further evidence from motor system physiology that multiple inhibitory processes influence action-stopping.NEW & NOTEWORTHY Current debate surrounds whether single- or dual-process models better account for human action-stopping ability. We show that motor suppression of a successfully stopped muscle follows a distinct time course compared with when that same muscle is unrelated to the stopping task. Our results further suggest that distinct local inhibitory neuron populations contribute to these unique sources of suppression. Our study provides evidence from motor system physiology that multiple inhibitory processes influence action-stopping.

Hybrid learning-based visual path following for an industrial robot

Abstract This study proposes a novel hybrid learning approach for developing a visual path-following algorithm for industrial robots. The process involves three steps: data collection from a simulation environment, network training, and testing on a real robot. The actor network is trained using supervised learning for 500 epochs. A semitrained network is then obtained at the $250^{th}$ epoch. This network is further trained for another 250 epochs using reinforcement learning methods within the simulation environment. Networks trained with supervised learning (500 epochs) and the proposed hybrid learning method (250 epochs each of supervised and reinforcement learning) are compared. The hybrid learning approach achieves a significantly lower average error (30.9 mm) compared with supervised learning (39.3 mm) on real-world images. Additionally, the hybrid approach exhibits faster processing times (31.7 s) compared with supervised learning (35.0 s). The proposed method is implemented on a KUKA Agilus KR6 R900 six-axis robot, demonstrating its effectiveness. Furthermore, the hybrid approach reduces the total power consumption of the robot’s motors compared with the supervised learning method. These results suggest that the hybrid learning approach offers a more effective and efficient solution for visual path following in industrial robots compared with traditional supervised learning.

The Strategy and Effectiveness of Baitul Maal wa Tamwil in Eradicating Loan Shark Practices in Java and Sumatra

This study aims to analyze the role of Baitul Maal wa Tamwil (BMT) as an Islamic microfinance institution in eliminating loan shark practices in communities, particularly in Java and Sumatra. Loan shark practices persist due to the ease and speed of loan disbursement, despite the high interest rates that entrap small communities in difficult-to-escape debt cycles. BMT offers a fair and interest-free Islamic financing solution based on profit-sharing principles and a more inclusive approach. This study discusses BMT’s financing strategies, such as lenient requirements, fast processing, and financial education programs designed to compete with loan sharks. The main findings indicate that BMT plays a significant role in providing fairer financing access to small communities and helping reduce their dependence on loan sharks. However, this study also reveals several challenges BMT faces, such as limited capital, strict regulations, and low financial literacy among the public. These challenges hinder BMT's ability to effectively compete with loan sharks in terms of speed and accessibility. The results of this study emphasize the importance of strengthening BMT’s capital, developing human resources, and innovating Islamic financing products so that BMT can play a more prominent role in eradicating loan shark practices in the community. With the right strategy and support from various stakeholders, BMT has great potential to continue growing as a more equitable and empowering financing solution.

Multiscale simulations of amorphous and crystalline AgSnSe2 alloy for reconfigurable nanophotonic applications

AbstractChalcogenide phase‐change materials (PCM) have been explored in novel nonvolatile memory and neuromorphic computing technologies. Upon fast crystallization process, the conventional PCM undergo a semiconductor–to–semiconductor transition. However, some PCM change from a semiconducting amorphous phase to a metallic crystalline phase with low conductivity (“bad metal”). In this work, we focus on new “bad metal” PCM, namely, AgSnSe2, and carry out multiscale simulations to evaluate its potential for reconfigurable nanophotonic devices. We study the structural features and optical properties of both crystalline and amorphous AgSnSe2 via density functional theory (DFT) calculations and DFT‐based ab initio molecular dynamic (AIMD) simulations. Then we use the calculated optical profiles as input parameters for finite difference time domain (FDTD) modeling of waveguide and metasurface devices. Our multiscale simulations predict AgSnSe2 to be a promising candidate for phase‐change photonic applications.

Modification of solar energy and photoelectrochemical water splitting properties: using FTO/Er-TiO2/MAPbI3/CuPc/Au as modified photoelectrode

In the past decades, converting solar energy into hydrogen through photoelectrochemical water splitting has been attracted. Here, we designed a new FTO/Er-TiO2/MAPbI3/CuPc/Au photoanode with n-i-p structure for using in solar water splitting. Accourding to obtained PEC results, the FTO/Er-TiO2/MAPbI3/CuPc/Au photoanode has a photocurrent density of ∼9.8 mA cm−2 ( under a visible lamp with intensity of 100 mW cm−2 irradiation) compared to FTO/Er-TiO2/Au and FTO/Er-TiO2/MAPbI3/Au photoanodes with photocurrent density of 0.7 and 6.12 mA cm−2, respectively. This important enhancement is refered to the light absorption feature of Er-TiO2/MAPbI3 and a fast electron and hole transfer process in the Er-TiO2 and CuPc, respectively. The photoelectrochemical action of the photoelectrode is increased using erbium doping due to creation of oxygen vacancies and titanium (III) ions. Furthermore, in this research, we studided the power conversion efficiency (PCE) of FTO/Er-TiO2/MAPbI3/Au and FTO/Er-TiO2/MAPbI3/CuPc/Au solar cells. The results shown that the significant enhancement in photovoltaic properties can be observed by utilizing spin-coated CuPc nanoparticles (as hole transport layer) at least by 1.39% compared to the FTO/Er-TiO2/MAPbI3 perovskite solar cell.