Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual space based face recognition using feature fusion

The authors propose a new face recognition technique by combining information from null space and range space of within-class scatter of a face space. The combination of information at feature level poses a problem of optimally merging two eigenmodels obtained separately from null space and range space. The authors use two different methods: covariance sum and Gramm-Schmidt orthonormalization to construct a new combined space, named as dual space, by merging two different set of discriminatory directions obtained separately from null space and range space. The authors employ forward and backward selection techniques to select the best set of discriminative features from dual space and use them for face recognition. Experimental results on three public databases, Yale, ORL and PIE will show the superiority of our method over a face recognition technique called discriminative common vectors (DCV) (Cevikalp et al., 2005), based only on the null space of within-class scatter.
Relationship between Depression and Cognitive Inhibition in Men with Heroin or Methamphetamine Use Disorder in First-Time Mandatory Detoxification

Previous studies have shown that males with substance use disorder (SUD) in their first mandatory detoxification experience high rates of depression. It is unknown whether this high depression incidence contributes to impaired inhibition. In this work, two studies were undertaken to examine the role of depression in cognitive inhibition in heroin and methamphetamine withdrawal. We used the Beck Depression Inventory (BDI) and the self-control scale (SCS) to explore the relationship between depression and impulse inhibition in patients participating in mandatory drug treatment for the first time (Study 1). The results showed that depression negatively predicted impulse inhibition. The Stroop color–word interference task was used to explore the role of patients’ depression in their inhibitory abilities (Study 2). The results showed that the high-depression group had weaker inhibition performances in the Stroop color–word interference task compared to the low-depression group. This study shows that cognitive inhibition is weaker in people with high-depression addiction than in those with low depression. This result suggests that attention should be paid to the role of depressive comorbidity when conducting working memory training treatment for substance addiction.
Farby-Perot observations and new models of the HH 47A and HH 47D bow shocks

We present new models for the HH 47A and HH 47D bow shocks based on line flux and velocity maps obtained with an imaging Fabry-Perot spectrometer. We confirm that HH 47A and HH 47D each show a bow shock/Mach disk morphology, and that velocity variability in the outflow can account for the observed structures. While it was suggested a decade ago that the inner working surface HH 47A appears to be traveling into the wake of HH 47D, we find kinematic evidence that the outer bow shock HH 47D is also not the primary ejection event in the outflow but follows in the wake of previously ejected material. By comparing the observed line ratios and line profiles to those predicted by our bow shock models, we find that both bow shocks have substantially lower shock velocities than their space motions would imply, and that the emission from each bow shock is systematically blueshifted from the rest-frame velocity of the ambient emission, indicating a comoving preshock medium. We derive kinematic ages of approximately 1150 yr for HH 47D and approximately 550 yr for HH 47A, which implies that the stellar driving source may undergo repetitive eruptions similar to FU Orionis-type outbursts every several hundred years. This timescale is similar to estimates made by Reipurth and collaborators for the separation between major outbursts in the HH 34 and HH 111 stellar jets.
Joint UAV Placement Optimization, Resource Allocation, and Computation Offloading for THz Band: A DRL Approach

With the development of internet of things, latency-sensitive applications such as telemedicine are constantly emerging. Unfortunately, due to the limited computation capacity of wireless user devices, the real-time demands can not be met. Multi-access edge computing (MEC), which enables the deployment of edge access points (E-APs) to support computation-intensive applications, has become an effective way to meet the real-time demands. However, the number of WUDs that E-APs can serve are limited. To increase system capacity, the unmanned aerial vehicle (UAV) assisted computation offloading architecture in the terahertz (THz) band is proposed. In this paper, the problem of UAV placement optimization, resource allocation, and computation offloading is investigated considering the quality of service and resource constraints. The joint optimization problem is non-convex and hard to be solved in time by using traditional algorithms, such as successive convex approximation. Therefore, deep reinforcement learning (DRL) based approach is a promising way to solve the formulated non-convex problem of minimizing latency. Double deep Q-learning (DDQN) and deep deterministic policy gradient (DDPG) algorithms are provided to search for near-optimal solutions in highly dynamic environments. The effectiveness of the proposed algorithms is proved by simulation results in different scenarios.
Molecular Dynamics Study of Interdiffusion for Cubic and Hexagonal SiC/Al Interfaces

The mechanical properties of the SiC/Al interface are crucial in estimating the overall strength of this ceramic-metal composite. The present work investigates the interdiffusion at the SiC/Al interface using molecular dynamics simulations. One cubic and one hexagonal SiC with a higher probability of orientations in contact with Al are examined as two samples of metal-matrix nanocomposites with whisker and particulate reinforcements. These reinforcements with the Si- and C-terminated surfaces of the SiC/Al interfaces are also studied. The average main and cross-interdiffusion coefficients are evaluated using a single diffusion couple for each system. The effect of temperature and annealing time are analysed on the self- and interdiffusion coefficients. It is found that the diffusion of Al in SiC is similar in cubic and hexagonal SiC and as expected, the interdiffusion coefficient increases as the temperature and annealing time increase. The model after diffusion can be used to evaluate the overall mechanical properties of the interface region in future studies.
Novel Tumor-Targeted Self-Nanostructured and Compartmentalized Water-in-Oil-in-Water Polyurethane-Polyurea Nanocapsules for Cancer Theragnosis

Encapsulation of water-soluble bioactive compounds for enabling specific accumulation in tumor locations, while avoiding premature clearance and/or degradation in the bloodstream, is one of the main hallmarks in nanomedicine, especially that of NIR fluorescent probes for cancer theragnosis. The herein reported technology furnishes water-dispersible double-walled polyurethane-polyurea hybrid nanocapsules (NCs) loaded with indocyanine green (ICG-NCs), using a versatile and highly efficient one-pot and industrially scalable synthetic process based on the use of two different prepolymers to set up the NCs walls. Flow cytometry and confocal microscopy confirmed that both ICG-loaded NCs internalized in monocyte-derived dendritic cells (moDCs). The in vivo analysis of xenograft A375 mouse melanoma model revealed that amphoteric functionalization of NCs’ surface promotes the selective accumulation of ICG-NCs in tumor tissues, making them promising agents for a less-invasive theragnosis of cancer.
Entrepreneurial Marketing Capabilities: A Comparative Study of Male and Female Small and Medium Business Owners

Business challenges in the digital marketing era are getting tougher because competitors don't only come from within the country, but also come from various countries around the world. For this reason, an entrepreneur needs to have a proactive attitude, be innovative, and dare to take risks to improve his business performance. The purpose of this study is to (a) explore entrepreneurial marketing capabilities in female and male entrepreneurs in East Java. (b) Analyze the strengths and weaknesses of male and female entrepreneurs in terms of Proactiveness, Calculated Risk-taking, Innovativeness, Opportunity Focus, Resource Leveraging, Customer Intensity, Value Creation, and Legitimacy. (c) developing an effective entrepreneurial marketing model for MSMEs managed by women and men. This type of research is qualitative phenomenology. The research location is in Greater Malang which consists of Malang city, Malang district and Batu city. The research subjects were 12 SMEs engaged in the food and beverage sector, consisting of 6 SMEs managed by women and 6 SMEs managed by men. The research instruments were interviews, observations and documentation. To increase the level of data accuracy, triangulation is carried out, both method triangulation and source triangulation. While the analysis was carried out using the Miles formula, with stages a) data collection b) data display c) data condensation and d) conclusion drawing/verifying. The output of this research is publication in international journals, and intellectual property rights. The results showed that in implementing entrepreneurial marketing (Entrepreneurial Marketing), male entrepreneurial competencies were more dominant in terms of risk taking, encouraging purchase intentions, creative value and legality. Meanwhile, female entrepreneurs have more dominant competencies in terms of being proactive, innovative, focusing on opportunities and seeking sources of funds. It is recommended that women MSMEs are more suitable for managing food and beverage businesses on a pioneering scale, while men are more suitable for managing businesses that are already experiencing growth.
An Efficient Approach to Predict Eye Diseases from Symptoms Using Machine Learning and Ranker-Based Feature Selection Methods

The eye is generally considered to be the most important sensory organ of humans. Diseases and other degenerative conditions of the eye are therefore of great concern as they affect the function of this vital organ. With proper early diagnosis by experts and with optimal use of medicines and surgical techniques, these diseases or conditions can in many cases be either cured or greatly mitigated. Experts that perform the diagnosis are in high demand and their services are expensive, hence the appropriate identification of the cause of vision problems is either postponed or not done at all such that corrective measures are either not done or done too late. An efficient model to predict eye diseases using machine learning (ML) and ranker-based feature selection (r-FS) methods is therefore proposed which will aid in obtaining a correct diagnosis. The aim of this model is to automatically predict one or more of five common eye diseases namely, Cataracts (CT), Acute Angle-Closure Glaucoma (AACG), Primary Congenital Glaucoma (PCG), Exophthalmos or Bulging Eyes (BE) and Ocular Hypertension (OH). We have used efficient data collection methods, data annotations by professional ophthalmologists, applied five different feature selection methods, two types of data splitting techniques (train-test and stratified k-fold cross validation), and applied nine ML methods for the overall prediction approach. While applying ML methods, we have chosen suitable classic ML methods, such as Decision Tree (DT), Random Forest (RF), Naive Bayes (NB), AdaBoost (AB), Logistic Regression (LR), k-Nearest Neighbour (k-NN), Bagging (Bg), Boosting (BS) and Support Vector Machine (SVM). We have performed a symptomatic analysis of the prominent symptoms of each of the five eye diseases. The results of the analysis and comparison between methods are shown separately. While comparing the methods, we have adopted traditional performance indices, such as accuracy, precision, sensitivity, F1-Score, etc. Finally, SVM outperformed other models obtaining the highest accuracy of 99.11% for 10-fold cross-validation and LR obtained 98.58% for the split ratio of 80:20.
Real-World Evidence on Disease Burden and Economic Impact of Sickle Cell Disease in Italy

A real-world analysis was conducted in Italy among sickle cell disease (SCD) patients to evaluate the epidemiology of SCD, describe patients’ characteristics and the therapeutic and economic burden. A retrospective analysis of administrative databases of various Italian entities was carried out. All patients with ≥1 hospitalization with SCD diagnosis were included from 01/2010-12/2017 (up to 12/2018 for epidemiologic analysis). The index date corresponded to the first SCD diagnosis. In 2018, SCD incidence rate was 0.93/100,000, the prevalence was estimated at 13.1/100,000. Overall, 1816 patients were included. During the 1st year of follow-up, 50.7% of patients had one all-cause hospitalization, 27.8% had 2, 10.4% had 3, and 11.1% had ≥4. Over follow-up, 6.1–7.2% of patients were treated with SCD-specific, 58.4–69.4% with SCD-related, 60.7–71.3% with SCD-complications-related drugs. Mean annual number per patient of overall treatments was 14.9 ± 13.9, hospitalizations 1.1 ± 1.1, and out-patient services 5.3 ± 7.6. The total mean direct cost per patient was EUR 7918/year (EUR 2201 drugs, EUR 3320 hospitalizations, and EUR 2397 out-patient services). The results from this real-world analysis showed a high disease burden for SCD patients with multiple hospitalizations during the follow-up. High healthcare resource utilization and costs were associated with patient’ management and were most likely underestimated since indirect costs and Emergency Room admissions were not included.
Phonon dispersion curves in indium phosphide

Phonon frequencies of indium phosphide have been determined along the principal symmetry directions (by inelastic neutron scattering). The shapes of the dispersion curves are discussed. The phonon frequencies at the critical points are: Gamma point, 10.3 and 9.2; X point, 9.95, 9.70, 5.8, 2.05; L point, 10.2, 9.5, 5.00, 1.65 THz. In all cases the longitudinal vibrations have a higher frequency than the transverse vibrations, i.e. the surfaces do not cross.
IndShaker: A Knowledge-Based Approach to Enhance Multi-Perspective System Dynamics Analysis

Decision making as a result of system dynamics analysis requires, in practice, a straightforward and systematic modeling capability as well as a high-level of customization and flexibility to adapt to situations and environments that may vary very much from each other. While in general terms a completely generic approach could be not as effective as ad hoc solutions, the proper application of modern technology may facilitate agile strategies as a result of a smart combination of qualitative and quantitative aspects. In order to address such complexity, we propose a knowledge-based approach that integrates the systematic computation of heterogeneous criteria with open semantics. The holistic understanding of the framework is described by a reference architecture and the proof-of-concept prototype developed can support high-level system analysis, as well as being suitable within a number of applications contexts—i.e., as a research/educational tool, communication framework, gamification and participatory modeling. Additionally, the knowledge-based philosophy, developed upon Semantic Web technology, increases the capability in terms of holistic knowledge building and re-use via interoperability. Last but not least, the framework is designed to constantly evolve in the next future, for instance by incorporating more advanced AI-powered features.
Calibration of incremental temperature fluctuations at high temperatures

Both absolute and differential temperature measurements were simultaneously performed as a function of time for a pixel on a high-temperature, multi-spectral, spatially and temporally varying infrared target simulator. A scanning laser beam was used to maintain a pixel at an on-the-average constant temperature of 520 K. The laser refresh rate of up to 1 kHz resulted in small-amplitude temperature fluctuations with the peak-to-peak amplitude of less than 1 K. The experimental setup to measure accurately the differential and the absolute temperature as a function of time is described.
Piezo mechanosensory channels regulate centrosome integrity and mitotic entry

Significance Piezo1 and 2 are mechanosensory channels known to be responsible for sensing mechanical stimuli on the cell membrane. They are widely expressed, play important roles in developmental and homoeostatic processes and are involved in human diseases such as anemia, musculoskeletal disorders and cancer. Piezo proteins are involved in migration, invasion, and proliferation of cancer cells, due to upregulation or downregulation of Piezo in different cancer types. Our study proposes a new intracellular role for Piezo proteins in cell cycle progression by regulating centrosome integrity. We show that either up- or downregulation of Piezo channels results in supernumerary centrosomes, a hallmark of cancer. Thus, Piezo proteins may serve as potential biomarkers and important targets for therapeutic intervention in cancer.
‘Should I stay or should I go?’: A mixed methods study on nurse retention during challenging times

Background The World Health Organization estimates that between 80,000 and 180,000 medical personnel perished as a result of COVID-19. Although studies about nurses’ organizational commitment during the COVID-19 pandemic have been conducted, the sources of motivations and resilience strategies of nurses in providing a quality healthcare service amidst the COVID-19 pandemic have yet to be explored. Objective This study aimed to investigate how motivation and resilience influence nurses to serve and cater to patients during the COVID-19 pandemic. Methods A sequential exploratory mixed approach was used in this study between July and August 2022. The Connor-Davidson Resilience Scale (CD-RISC-10), Work Extrinsic and Intrinsic Motivations scale (WEIMS), and Garbee and Killacky’s Intent to Stay Scale (GKISS) were used to measure resilience, motivation, and intention to stay, among 50 nurses within Metro Manila. Quantitative data were analyzed using quantile regression, while qualitative data from eight participants were analyzed using thematic analysis. Results The majority of the nurses were working 12 hours and above (52%) and earning a bi-weekly income of PHP 15,001 to 20,000 (96%). The GKISS scores of most respondents indicated their likelihood of remaining in their current profession was moderately low (Mdn = 12.5; IQR = 12-14). It was also found that there was no sufficient statistical evidence to conclude that intention to stay was associated with resilience (p = 0.914) and work motivation (p = 0.560). The qualitative strand of this study explored the significant influences of motivation, resilience strategies, and sources of intention to stay among Filipino nurses while facing the COVID-19 pandemic. The primary motivations of nurses lie in family, passion for work, and career development, while the resilience strategies include adaptiveness, time management skills, and self-fulfillments. On the other hand, the intent to stay greatly lies in serving the people and the country. Conclusion This study concludes that positive and negative resilience and motivations from different facets of the social life of Filipino nurses, including passion, familial ties, patient care, and faith are the antecedents influencing the intention to serve in the healthcare service. In terms of staying for an extended period in a nursing career, the study found that institutionalized interventions, adequate compensation and benefits, and a good workplace are determinants of staying longer in the Philippines as Filipino nurses.
Effects of the Interference of Sensory Systems on Postural Control in Congenitally Blind Subjects

Abstract The postural system requires the sensory systems to maintain postural control (PC). Blind subjects use the somatosensory system to keep PC whereas sighted subjects use the visual system. So what happens to PC when challenging the sensory systems? We analyzed the center of pressure (COP) in ten blind and 10 sighted subjects under conditions: eyes open/closed (interference of visual system) and on firm/foam surfaces (interference of somatosensory system). We found that under the condition of eyes open on a firm surface, the blind subjects relied on the somatosensory system, whereas sighted subjects relied on the visual system. However, when eyes closed and on foam surface, similar behavior was found in both groups for all COP variables. In general blind subjects use their somatosensory system as the main sensory input to maintain PC.
Organic Rice Production Practices: Effects on Grain End-Use Quality, Healthfulness, and Safety

Demand for rice labeled as organic is growing globally. Consumers state that foods labeled as organic are nutritionally superior and safer than their conventionally produced equivalent. The research question for this systematic review is as follows: is there a difference between the effects of sustainable agriculture and conventional farming methods on rice grain end-use quality, healthfulness, and safety? The studies (n = 23) examined for this review suggest that organic production practices don’t influence most end-use quality (e.g., chalk, milling yield, pasting properties) and healthfulness (e.g., gamma-oryzanol fraction and tocols) traits studied, or if it does, it will be to a small degree. If differences in end-use quality traits are found, they will be associated with grain protein content, which varies along with the dose of nitrogen applied during rice growth. We conclude that the studies evaluated in this review found that organically produced rice grain was less likely to contain residues of the pesticides (e.g., organochlorine) examined in the study than the rice is grown using conventional methods. There was some evidence that organically grown rice is more likely to be contaminated with mycotoxin-producing fungi and some mycotoxins. Common shortcomings of the studies were that they were poorly designed, with limited to no details of the cultural management practices used to grow the rice studied, the length of time fields was under organic management not stated, cultivars were not named, and the data wasn’t analyzed statistically.
Whole-Exome Sequencing Identifies Genetic Variants for Severe Adolescent Idiopathic Scoliosis in a Taiwanese Population

Adolescent idiopathic scoliosis (AIS) is a three-dimensional spinal curvature deformity that appears in the adolescent period. In this study, we performed whole-exome sequencing on 11 unrelated Taiwanese patients with a Cobb’s angle greater than 40 degrees. Our results identified more than 200 potential pathogenic rare variants, however, most of which were carried only by one individual. By in silico pathogenicity annotation studies, we found that TTN, CLCN1, and SOX8 were the most important genes, as multiple pathogenic variants were within these genes. Furthermore, biological functional annotation indicated critical roles of these AIS candidate genes in the skeletal muscle. Importantly, a pathogenic variant on SOX8 was shared by over 35% of the patients. These results highlighted TTN, CLCN1, and SOX8 as the most likely susceptibility genes for severe AIS.
Solving Multispecies Lotka-Volterra Equations by the Daftardar-Gejji and Jafari Method

In this article, we apply the Daftardar-Gejji and Jafari method (DJM) to solve the multispecies Lotka–Volterra equation. A comparison between the DJM, differential transformation method (DTM), the variational iteration method (VIM), and Adomian decomposition method (ADM) shows that the DJM is a reliable and powerful method for solving nonlinear equations. The efficiency and applicability of this method are confirmed by considering some examples. The proposed procedure provides better results in comparison to some existing methods.