Miracle-dz/UniFAR-FTUs huggingface dataset:
Late Quaternary record of Indian summer monsoon‐induced stratification and productivity collapse in the Andaman Sea

During each summer monsoon, the northeastern Indian Ocean receives a huge amount of rain and river discharge, resulting in strong stratification and prevalence of oligotrophic conditions. These water column changes impact upper ocean productivity which is reflected in the planktonic foraminifera distribution, providing an opportunity to study the effect of monsoon forcing and stratification history. Analogous to modern‐day stratification, very intense water column stratification and productivity collapse were observed associated with Indian summer monsoon (ISM) evolution. This paper reports significant stratification events during MIS 3 (37.0 to 33 and 27 to 24 cal ka), Bølling/Allerød (B/A), early Holocene (10.0 to 8.0 cal ka) and mid‐Holocene (7.0 to 5.0 cal ka) which slowly muted upwelling and productivity. The deglacial intensification of the ISM started in the early stages of the Bølling/Allerød (B/A) followed by slight weakening during the Younger Dryas and regained strength during the early Holocene, coinciding with the highest summer insolation at 30°N. A progressive decline in the abundances of productivity and salinity proxies from 4.2 to 2.0 cal ka suggests a gradual weakening of the ISM. The late Quaternary productivity variations in the Bay of Bengal and the Andaman Sea are primarily controlled by salinity‐related stratification.
Understanding proximity mobile payment continuance usage in Indonesia from a habit perspective

Purpose This study aims to propose a theoretical model to explain mobile payment (MP) continuance usage in a physical store in Indonesia from a habit perspective. In detail, continuance usage was argued to be a consequence of habitual behavior which is related to specific actions conducted automatically, repeatedly and frequently. Therefore, the theoretical model was constructed on the theory of habit establishment. Design/methodology/approach In total, 220 Indonesian respondents were used to examine the theoretical model. Furthermore, a cross-sectional study was used through the use of a descriptive statistical approach to preparing data and descriptive analyses and structural equation modeling method for analysis. Findings Satisfaction was found to have the most substantial direct influence on the establishment of habit to use MP followed by perceived usefulness and perceived compatibility. Meanwhile, deal proneness and social ties were discovered to have a significant indirect effect on habit through the mediation of usefulness. Originality/value This study used the theory of habit formation to understand how user develops repeated behavior in MP usage which leads to continuance usage of the platform. There is limited explicit exploration and development of a theory based on this concept, therefore, this study is a contribution to the body of knowledge with respect to habit formation and its impacts on MP continuance usage.
Prosthodontic Rehabilitation of Missing Molar using Friction Fit Zirconia Crown Over Dual One Piece Implants-Clinical Report and I Year Follow Up

The present patient report describes a missing mandibular molar rehabilitated by two one piece narrow diameter dental implants. Although the gold standard treatment is to place a regular diameter implant, unfortunately due to horizontal bone resorption, this option is not possible without lateral bone augmentation. In this situation narrow diameter implants are a viable alternative. immediate provisional crown is provided after implant placement and three months latter, replaced with partially transparent monolithic friction frit cement free zirconia crown. Follow up til the end of one year revealed healthy hard and soft tissues around implants.
Device customization with novel adhesive electrode

The present research deal with the physical examination and analysis of an instrument that is ankle foot orthotic device. The physics of this device consist of calf piece; calf strap; a muscle stimulator; stimulator suspension including a press button with nylon strap; two adhesive electrodes; electrical wires; hinge joint; JBR outsole; foot piece; ankle strap; forefoot strap; rings; adjustable strap; press button; cold and hot pack pouch; a means to provide upward projection; & shank. The customized AFO device is characteristic in the sense that the adhesive strap being mounted on the rings so as to keep the plantar section of the foot piece in straight position and wherein the adhesive strap being made up by a combination of polyvinyl chloride, polypropylene and polyethylene wherein polyvinyl chloride, polypropylene and polyethylene is 1:1:2 by weight; wherein the cold and hot pack pouch being made up of 40.5 wt% water; 40.5 wt% ammonium nitrate, 4 wt% hydropropylmethyl cellulose and 15 wt% propylene glycol; and wherein the said electrode being made up of a hydrogel comprises of acrylic acid and N-vinylpyrrolidone. The overall result feedback is a feeling of increased muscle control, flexibility, and range of motion on using the device.
Narrowband to Narrowband Frequency Tunable Slotted Dipole Antenna

In this paper, the slotted dipole antenna structure is proposed to have four narrowband frequencies with ability to be reconfigured. Narrowband reconfiguration can be achieved by controlling the length of slotted dipole by using switches. The narrowband frequency is to be at 1.8 GHz (GSM), 2.4 GHz (WLAN), 2.6 GHz (4G), and 3.5 GHz (5G) respectively. The longest dipole length produced 1.8 GHz, the second-longest dipole length produced 2.4 GHz, the third-longest dipole length produced 2.6 GHz, while the smallest dipole length produced 3.5 GHz. To maintain the stability of the RF current in the system, sixteen capacitors were used. As well eight inductors were used to isolate the RF current and power supply. The PIN diode was used as a switch to allow the induced current to stop and pass into the slot which means that it can be used to select the desired frequency. Depending on switching configuration, the operating frequency is tuned. Good matching is achieved for all configurations. The simulated result of gain for the four operating is higher than 2 dB while the omnidirectional radiation pattern has been obtained thus makes the proposed antenna suitable for wireless application.
Risk Data Analysis of Cross Border E-commerce Transactions Based on Data Mining

At present, China’s foreign trade volume of cross-border e-commerce is still relatively small, the targeted legal system has not been established, and the industry access threshold is relatively low. The development of cross-border e-commerce faces many risks. Relying on data mining technology, data docking and risk control. At the data level, the risk of cross-border e-commerce transaction is processed and analyzed, and the potential risk is predicted, and more targeted risk control methods are proposed to reduce the risk of cross-border e-commerce transaction business. Aiming at this problem, this paper establishes the risk data analysis of cross-border e-commerce transactions based on data mining. In order to further verify the data accuracy of data mining technology, this paper analyzes the test values of neural network algorithm, seizure rate and inspection rate. When the misclassification loss parameter value is increased from 1 to 4, the detection rate of the model increases and the detection rate decreases. When the misclassification loss value is higher than 4, the detection rate increases, but the seizure rate decreases significantly. Therefore, the target inspection rate of the model can be changed by adjusting the misclassification loss parameter value of the model. If we set the parameter value of misclassification loss reasonably, we can achieve the goal of preventing and controlling the maximum risk with the lowest data mining cost. Through the analysis, the research in this paper has achieved ideal results, and made a contribution to data mining in cross-border e-commerce transaction risk data analysis.
Prognostic Value of MUC1 and its Correlation with Tumor-Infiltrating Immune Cells in Breast Cancer

Background: MUC1 is a transmembrane glycoprotein, aberrantly glycosylated and overexpressed in a variety of epithelial cancers, and plays a crucial role in cancer progression, especially in breast cancer. It is also an essential regulator for immune functionality, but the mechanisms whereby it effects immune infiltration in breast cancer remain uncertain. Methods: In this research, MUC1 expression was analyzed by the Oncomine and TIMER database. The association between MUC1 and prognosis was evaluated by Kaplan-Meier plotter database. The correlations of MUC1 with immune infiltration and immunological markers were assessed by TIMER database. Results: We found that MUC1 expression was significantly correlated with outcomes in multiple cancers, with the effect being particularly pronounced in breast cancer. Pathologically, elevated MUC1 expression was related with worse prognosis depending on intrinsic subtypes, ER status, patient stage, lymph node and TP53 mutation status in breast cancer. Specifically, low level of MUC1 seemed to be more favorable to luminal B patients with systemic treatment. MUC1 expression had significant negative correlations with inﬁltrating levels of CD8+ T cells, CD4+ T cells, B cells, macrophages, neutrophils, monocytes and dendritic cells (DCs) in breast cancer. Besides, MUC1 displayed strong regulations on macrophage polarization and diverse immunological gene markers. The patients with lower MUC1 and deeper immune infiltration predicted better prognosis. Conclusions: MUC1 is significantly associated with clinical prognosis and potentially plays an essential role in modulating cytotoxic T lymphocytes (CTLs), tumor associated macrophages (TAMs), natural killer cells (NK cells) and DCs in breast tumors. Collectively, MUC1 could be served as a valuable biomarker of predicting prognosis and immune inﬁltration for breast cancer patients.
HYDROXYETHYL METHACRYLATE BASED NANOCOMPOSITE HYDROGELS WITH TUNABLE PORE ARCHITECTURE

Hydroxyethyl methacrylate (HEMA) based hydrogels have found increasing number of applications in areas such as chromatographic separations, controlled drug release, biosensing, and membrane separations. In all these applications, the pore size and pore interconnectivity are crucial for successful application of these materials as they determine the rate of diffusion through the matrix. 2-Hydroxyethyl methacrylate is a water soluble monomer but its polymer, polyHEMA, is not soluble in water. Therefore, during polymerization of HEMA in aqueous media, a porous structure is obtained as a result of phase separation. Pore size and interconnectivity in these hydrogels is a function of several variables such as monomer concentration, cross-linker concentration, temperature etc . In this study, we investigated the effect of monomer concentration, graphene oxide addition or clay addition on hydrogel pore size, pore interconnectivity, water uptake, and thermal properties. PolyHEMA hydrogels have been prepared by redox initiated free radical polymerization of the monomer using ethylene glycol dimethacrylate as a cross-linker. As a nanofiller, a synthetic hectorite Laponite® XLG and graphene oxide were used. Graphene oxide was prepared by the Tour Method. Pore morphology of the pristine HEMA based hydrogels and nanocomposite hydrogels were studied by scanning electron microscopy. The formed hydrogels were found to be highly elastic and flexible. A dramatic change in the pore structure and size was observed in the range between 22 to 24 wt/vol monomer at 0.5 % of cross-linker. In this range, the hydrogel morphology changes from typical cauliflower architecture to continuous hydrogel with dispersed water droplets forming the pores where the pores are submicron in size and show an interconnected structure. Such controlled pore structure is highly important when these hydrogels are used for solute diffusion or when there’s flow through monolithic hydrogels. These robust hydrogels may be useful in separation and biomedical applications.
Smart Cementitious Composites for Road Traffic Monitoring and Weighing in Motion

The addition of electrically conductive materials at micro scale, such as carbon fibres (CF) or steel fibres (SF), to conventional cementitious materials makes piezo-resistive behaviours possible in terms of changes in electrical resistivity due to applied stresses. Smart cementitious composites (SCCs) may thus be able to detect traffic density and sense weight in motion thanks to such piezo-resistive property. Three types of cement-based sensors, with CF, SF, or a hybrid of CF and SF, were experimentally evaluated by applying quasi-static and dynamic load cycles after seven days of curing in different load directions reflecting the electrodes and different circuit type connections of the specimens. The performance of each type of sensor was assessed based on measuring the changes in electrical resistivity (ER) under compressive and flexure stresses, with test results revealing that the use of CF in these composites was the best choice because this generated more sensitivity to applied loads in terms of the change in ER compared with other types. These results were achieved when the applied load was parallel to the electrode direction. The findings also indicated arrangement of specimens as an electric series circuit type was the best setup configuration for traffic monitoring and weight in motion measurement.
Increasing Synchronous Fire Danger in Forests of the Western United States

Widespread fire activity taxes suppression resources and can compound wildfire hazards. We examine the geographic synchronicity of fire danger across western United States forests as a proxy for the strain on fire suppression resource availability. Interannual variability in the number of days with synchronous fire danger, defined as fire weather indices exceeding the local 90th percentile across ≥40% of forested land, was strongly correlated (r = 0.85) with the number of days with high strain on national fire management resources. A 25‐day increase in the annual number of days with synchronous fire danger was observed during 1979–2020. Climate projections show a doubling of such days by 2051–2080. Such changes will escalate the likelihood of years with extended periods of synchronous fire danger that have historically strained suppression efforts and contributed to additional burned area, therein requiring additional management strategies for coping with anticipated surges in fire suppression demands.
Harmony search Hawks optimization-based Deep reinforcement learning for intrusion detection in IoT using nonnegative matrix factorization

With the advent of the Internet of Things (IoT), the security of the network layer in IoT is getting more attention in recent decades. Various intrusion detection methods were developed in the existing research works, but the capability to detect malicious and intrusion activities in the complex Internet environment poses a challenging task in IoT. Hence, an effective and optimal intrusion detection mechanism, named Harmony Search Hawks Optimization-based Deep Reinforcement Learning (HSHO-based Deep RL), is proposed in this research to detect malicious network activities. The proposed Harmony Search Hawks Optimization (HSHO) algorithm is designed by integrating Harmony Search (HS) with the Harris Hawks Optimization (HHO) algorithm. However, the optimal detection result that is effectively achieved through the fitness measures such that the minimum fitness value is only declared as the optimal solution. The Deep Reinforcement Learning (Deep RL) classifier effectively detects the malicious or intruder behaviors and generates a satisfactory result. By reducing the dimensionality of data using nonnegative matrix factorization, the data is optimally fit to perform intrusion detection process in the IoT environment. The proposed HSHO-based Deep RL obtained better performance in terms of the metrics like accuracy (96.925%), True Positive Rate (TPR; 96.90%), and True Negative Rate (TNR; 97.920%) with respect to [Formula: see text]-fold.
Exploring the links between secondary metabolites and leaf spectral reflectance in a diverse genus of Amazonian trees

Plant defense chemistry is often hypothesized to drive ecological and evolutionary success in diverse tropical forests, yet detailed characterizations of plant secondary metabolites in tropical plants are logistically challenging. Here, we explore a new integrative approach that combines visible-to-shortwave infrared (VSWIR) spectral reflectance data with detailed plant metabolomics data from 19 Protium (Burseraceae) tree species. Building on the discovery that different Protium species have unique chemistries yet share many secondary metabolites, we devised a method to test for associations between metabolites and VSWIR spectral data. Given species-level variation in metabolite abundance, we correlated the concentration of particular chemicals with the reflectance of the spectral bands in a wavelength band per secondary metabolite matrix. We included 45 metabolites that were shared by at least 5 Protium species and correlated their per-species foliar abundances against each one of 210 wavelength bands of field-measured VSWIR spectra. Finally, we tested whether classes of similar metabolites showed similar relationships with spectral patterns. We found that many secondary metabolites yielded strong correlations with VSWIR spectra of Protium. Furthermore, important Protium metabolite classes such as procyanidins (condensed tannins) and phytosterols were grouped together in a hierarchical clustering analysis (Ward’s algorithm), confirming similarity in their associations with plant spectral patterns. We also found a significant correlation in the phenolics content between juvenile and canopy trees of the same species, suggesting that species-level variation in defense chemistry is consistent across life stages and geographic distribution. We conclude that the integration of spectral and metabolic approaches could represent a powerful and economical method to characterize important aspects of tropical plant defense chemistry.
Characterization and Buckling Investigation of Composite Materials to be used in the Prosthetic Pylon Manufacturing

A prosthetic pylon is a part of an artificial lower limb, which is a very interesting area of biomedical engineering today. The research aims to show the hung innovations and developments of new suggested composite material, to modify the prosthetic pylon (which is generally made of lightweight metal such as aluminum, titanium, stainless steel, or an alloy of these), extends its life and increase the comfort of its user. Vacuum bagging technique was used to manufacture the samples which consist of constant perlon layers and a different number of composite material (Carbon or Glass) fiber layers as reinforcement materials at (0°/90°) orientation relative to the applied load and polymethyl methacrylate (PMMA) as a resin. The work included two major parts; theoretical and experimental tests for the real case. The theoretical and experimental results showed that the modulus of elasticity, tensile strength, and critical buckling load increase with the increasing the number of composite fiber layers. The percentage of increase in modulus of elasticity, tensile strength and critical buckling load for the specimen with three carbon layers and perlon layers in PMMA matrix was compared with three glass layers and perlon layers in PMMA matrix specimen and it was (12.5%, 5% & 17%) respectively, at (0°/90°) fibers orientation relative to the applied force. Validation of the results is conducted by comparing with results in other literature, a good agreement between them was found.
Mobile application to optimize care for ST-segment elevation myocardial infarction patients in a large healthcare system, STEMIcathAID: rationale and design

Abstract Aims Technological advancements have transformed healthcare. System delays in transferring patients with ST-segment elevation myocardial infarction (STEMI) to a primary percutaneous coronary intervention (PCI) centre are associated with worse clinical outcomes. Our aim was to design and develop a secure mobile application, STEMIcathAID, streamlining communication, and coordination between the STEMI care teams to reduce ischaemia time and improve patient outcomes. Methods and results The app was designed for transfer of patients with STEMI to a cardiac catheterization laboratory (CCL) from an emergency department (ED) of either a PCI capable or a non-PCI capable hospital. When a suspected STEMI arrives to a non-PCI hospital ED, the ED physician uploads the electrocardiogram and relevant patient information. An instant notification is simultaneously sent to the on-call CCL attending and transfer centre. The attending reviews the information, makes a video call and decides to either accept or reject the transfer. If accepted, on-call CCL team members receive an immediate push notification and begin communicating with the ED team via a HIPAA compliant chat. The app provides live GPS tracking of the ambulance and frequent clinical status updates of the patient. In addition, it allows for screening of STEMI patients in cardiogenic shock. Prior to discharge, important data elements have to be entered to close the case. Conclusion We developed a novel mobile app to optimize care for STEMI patients and facilitate electronic extraction of relevant performance metrics to improve allocation of resources and reduction of costs.
Public Debt Management and Macroeconomics Policies Coordination: Evidence from Jordan

This study aimed to analyze the effects of fiscal and monetary policies interactions on public debt in Jordan during (1970 – 2019). Using Vector Error Correction Model (VECM) derived from VAR (Vector Auto regression), and examine dynamic interactions between economic variables over time, by Appling Impulse Response Function, and Variance Decomposition. The results indicated that the fiscal policy instruments affect public debt in two different directions, the expansion of government expenditure positively affect public debt, while tax revenues reduce indebtedness. The monetary policy instruments affect public debt in the same directions, as the results indicated that the central bank in controlling money supply and managing interest rate helps the fiscal authority in reducing the public debt in Jordan. The results confirm the strongest impact of government expenditure on public debt in Jordan. The study recommends the necessity of rationalizing government expenditures and combating tax evasion. In addition, more coordination between fiscal and monetary policies.
Discriminative locality-constrained sparse representation for robust face recognition

In this paper, a new joint sparse representation method called discriminative locality-constrained sparse representation (DLSR) is proposed for robust face recognition. DLSR incorporates locality and label information of training samples into the framework of sparse representation. Locality information can distinguish dissimilarity between samples and plays an important role in image classification. Compared with the existing methods, DLSR contains more discriminative information of samples and can obtain more discriminative recognition results. Due to the use of l2-norm regularization, DLSR can obtain a closed-form solution. This makes it computationally very efficient. Experimental results based on the benchmark face databases ORL have shown that DLSR can achieve more promising performance than some state-of-the-art methods.