Miracle-dz/UniFAR-FTUs huggingface dataset:
Business Resilience and Quality of Life of Timber Smes During the COVID-19 Pandemic in Bandung Regency

Purpose: This knows the influence of business ethics, spiritual behavior, external support and information technology on business resilience and quality of life of logging SMEs during the Covid-19 pandemic in Badung District. Theoretical framework: The number of wood SMEs during the Covid-19 pandemic in Badung District shows the low business resilience of wood SMEs, which may affect their quality of life. small and medium-sized wood enterprises. Business ethics of small and medium enterprises in the wood industry based on local wisdom in rural areas, the importance of spiritual behavior, external support and the development of information technology are Important studies affecting business resilience and quality of life of small and medium-sized enterprises in the wood industry during the Covid-19 pandemic in Badung. Regent. Design/Methodology/Approach: This study is quantitative and uses structural equation modeling (SEM) analysis. The respondents of this study are 804 medium-sized industrial small and medium enterprises. And the location of this study is in Bandung Regency. Findings: This shows that, through experiments, it can be seen that the variable of business resilience has a significant influence, each increase in the value of business resilience will improve the quality of life of medium-sized enterprises. and small wood industry, both in terms of social and psychological support. and mental conditions. health, safety and income levels during the COVID-19 pandemic. Research, Practical & Social implications: This shows that, through experiments, it can be seen that the variable of business resilience has a significant influence, each increase in the value of business resilience will improve the quality of life of medium-sized enterprises. and small wood industry, both in terms of social and psychological support. and mental conditions. health, safety and income levels during the COVID-19 pandemic. Originality/Value: The performance of wood SMEs will gradually begin to improve thanks to various initiatives undertaken both operationally and commercially.
CONSIDERATION OF "GENTRIFICATION" IN CONTEMPORARY CHINESE URBAN RENEWAL

In recent years due to the establishment of socialist market econom system and urban land lease system, the renewal of Chinese cities has accelerated rapidly.Although some great achievements have been gained, there exist some problems. "Gentrification" is the major form of urban renewal in western countries. It first occurred in 1960s. Generally "gentrification" occurs in one or two communities not far from the CBD of the city, which usually have good landscape and long history. "Gentrification" has its own dynamic mechanism and has much influence on the original residents. They have to move out due to gentrification. The municipal government should pay attention to gentrification and should improve urban renewal plan from the perspective view of gentrification. In the urban renewal plan the interest of the original residents should be harmonized for social equity.
Multi-Cat Monitoring System Based on Concept Drift Adaptive Machine Learning Architecture

In multi-cat households, monitoring individual cats’ various behaviors is essential for diagnosing their health and ensuring their well-being. This study focuses on the defecation and urination activities of cats, and introduces an adaptive cat identification architecture based on deep learning (DL) and machine learning (ML) methods. The architecture comprises an object detector and a classification module, with the primary focus on the design of the classification component. The DL object detection algorithm, YOLOv4, is used for the cat object detector, with the convolutional neural network, EfficientNetV2, serving as the backbone for our feature extractor in identity classification with several ML classifiers. Additionally, to address changes in cat composition and individual cat appearances in multi-cat households, we propose an adaptive concept drift approach involving retraining the classification module. To support our research, we compile a comprehensive cat body dataset comprising 8934 images of 36 cats. After a rigorous evaluation of different combinations of DL models and classifiers, we find that the support vector machine (SVM) classifier yields the best performance, achieving an impressive identification accuracy of 94.53%. This outstanding result underscores the effectiveness of the system in accurately identifying cats.
Modeling surfzone to inner-shelf tracer exchange

A near-shoreline, continuous dye release at an approximately alongshore-uniform beach (IB09 experiment) is simulated with the wave-resolving Boussinesq model funwaveC. The model generates surfzone eddies and transient rip currents but does not resolve inner-shelf vertical variation or stratification. The funwaveC model reproduces well the observed surfzone and inner-shelf dye observations over roughly 350 m cross-shore and 2 km alongshore. Dye is advected alongshore by waveand winddriven currents similarly in the observations and model. Near-shoreline mean dye concentration decays downstream as a power law with similar observed (20.33) and modeled (20.38) exponents. Observed and modeled cross-shore mean dye profiles are similar, though modeled inner-shelf dye is somewhat elevated. Observed and modeled alongshore dye transports agree, though with compensating surfzone and inner-shelf errors later in the release. For times <3.5 h (before observed and modeled dye advects beyond the model alongshore domain), observed and modeled dye budgets are similar to each other and close to within 10%, and half the observed and modeled dye is exported to the inner-shelf. Later in the release, surfzone and inner-shelf dye masses are under and overpredicted, respectively. Model-data differences may be due to the model’s lack of vertical variation, stratification, or tide. The good overall model-data agreement indicates that nearshore tracer transport and dispersion are realistically simulated over 5 h and 2 km alongshore, and that the model transient rip currents accurately induce cross-shore exchange between the surfzone and inner-shelf.
A Rarely Reported Crustacean Species, Rissoides pallidus (Giesbrecht, 1910) (Stomatopoda, Squillidae), Caught in the Strait of Sicily Waters (Central Mediterranean Sea)

The mantis shrimp Rissoides pallidus (Giesbrecht, 1910) is a rarely reported crustacean species in the central Mediterranean Sea. In December 2020, during a trawl survey off Mazara del Vallo harbor (Strait of Sicily), two specimens of R. pallidus were captured on coastal detritus and coastal terrigenous mud bottoms at about 132 and 152 m depths. Additional information specific to biometrics, bottom types, depth preference, habitats, and geographic distribution of this crustacean species are provided.
FAST ESTIMATION OF SPACECRAFT ANGULAR VELOCITY FROM SEQUENTIAL GEOMAGNETIC FIELD OBSERVATIONS

A new, fast method is presented for estimating the angular rate of a tumbling, momentum wheel-equipped spacecraft in a low-Earth orbit from sequential readings of Earth's magnetic field using a three-axis magnetometer (TAM). Based on a recently introduced method for angular rate estimation from Sun vector measurements, the new estimator comprises two stages, a deterministic algorithm that provides a coarse angular velocity estimate, and an extended Kalman filter, which is initialized using the first stage's crude estimate. This initialization renders the filter accurate and robust. A simulation study assuming conservative TAM noise values is used to demonstrate the performance of the method.
Human CD79b+ neutrophils in the blood are associated with early-stage melanoma

Purpose Due to their abundance in the blood, low RNA content, and short lifespan, neutrophils have been classically considered to be one homogenous pool. However, recent work has found that mature neutrophils and neutrophil progenitors are composed of unique subsets exhibiting context-dependent functions. In this study, we ask if neutrophil heterogeneity is associated with melanoma incidence and/or disease stage. Experimental design Using mass cytometry, we profiled melanoma patient blood for unique cell surface markers among neutrophils. Markers were tested for their predictiveness using flow cytometry data and random forest machine learning. Results We identified CD79b+ neutrophils (CD3-CD56-CD19-Siglec8-CD203c-CD86LoCD66b+CD79b+) that are normally restricted to the bone marrow in healthy humans but appear in the blood of subjects with early-stage melanoma. Further, we found CD79b+ neutrophils present in tumors of subjects with head and neck cancer. AI-mediated machine learning analysis of neutrophils from subjects with melanoma confirmed that CD79b expression among peripheral blood neutrophils is highly important in identifying melanoma incidence. We noted that CD79b+ neutrophils possessed a neutrophilic appearance but have transcriptional and surface-marker phenotypes reminiscent of B cells. Compared to remaining blood neutrophils, CD79b+ neutrophils are primed for NETosis, express higher levels of antigen presentation-related proteins, and have an increased capacity for phagocytosis. Conclusion Our work suggests that CD79b+ neutrophils are associated with early-stage melanoma.
Developments of additive manufacturing and 5D printing in tissue engineering

Additive manufacturing, popularly known as “3D printing”, enables us to fabricate advanced scaffolds and cell-scaffold constructs for tissue engineering. 4D printing makes dynamic scaffolds for human tissue regeneration, while bioprinting involves living cells for constructing cell-laden structures. However, 3D/4D printing and bioprinting have limitations. This article provides an up-to-date review of 3D/4D printing and bioprinting in tissue engineering. Based on 3D/4D printing, 5D printing is conceptualized and explained. In 5D printing, information as the fifth dimension in addition to 3D space and time is embedded in printed structures and can be subsequently delivered, causing change/changes of the environment of 5D printed objects. Unlike 3D/4D printing that makes passive/inactive products, 5D printing produces active or intelligent products that interact with the environments and cause their positive changes. Finally, the application of 5D printing in tissue engineering is illustrated by our recent work. 3D/4D/5D printing and bioprinting are powerful manufacturing platforms for tissue engineering.
A 0.75 to 1.5 GHz Reconfigurable Diplexer With Independently Controllable Center Frequency and Insertion Phase

A novel reconfigurable diplexer with independently controllable center frequency and insertion phase is proposed in this brief. It simply consists of six coupled resonators and two non-resonating-nodes (NRNs). These six resonators are arranged in two triplet topologies and construct two typical third-order filters, forming the lower and upper channels in the diplexer, respectively. The NRNs are loaded at the receiver (RX) and transmitter (TX) ports. With the utilization of NRNs, the insertion phases of the upper and lower channels in the diplexer can be independently controlled. Optimization technique is used to obtain the coupling matrix of the diplexer, in which the NRN is considered to achieve a prespecified insertion phase. To validate the proposed idea, a microstrip prototype is fabricated and measured. Experiment results show that the center frequencies of lower and upper channels can be tuned from 0.75 GHz to 0.98 GHz, and from 1.23 GHz to 1.5 GHz, respectively. The insertion phases of both channels can be independently tuned from 0 to 120 degrees at each frequency tuning state.
A comprehensive analysis of the simulation, optimization, corrosion and design
 aspects of crude distillation units

The primary function of a crude distillation unit (CDU) within a petroleum refinery is to effectively segregate crude oil into its constituent fractions or products based on their respective boiling points. The Crude Distillation column often serves as the primary processing unit within most refineries, pivotal in producing a wide range of refinery products. This study examines research articles published between 2013 and 2023 that specifically investigate issues related to crude distillation units. The research endeavours to produce innovative designs and construct mathematical models to enhance production efficiency within this context. The research primarily centres on developing a mathematical model that accurately characterizes the distillation tower. This is achieved using either an Artificial Neural Network or a nonlinear model predictive control approach. The primary objective of simulation and optimization research is identifying optimal operating conditions, typically employing software tools such as Aspen HYSYS or PRO II. The corrosion treatment outcomes conducted at the tower's upper section were satisfactory. The study focused on the issue of corrosion in the overhead lines and pumps around exchangers. This design research aims to investigate potential modifications to the distillation tower's design or preflash process to optimize production outcomes.
ON STOCHASTIC EQUATIONS AND INCLUSIONS WITH BACKWARD MEAN DERIVATIVES

The paper is devoted to investigation of stochastic diﬀerential equations and inclusions with backward mean derivatives. We deal with the property of global in time existence of solutions of “inverse” Cauchy problem for such equations and inclusions having lowers semicontinuous right-hand sides. A condition that guarantees the global in time existence of such solutions is obtained. For inclusions with backward mean derivatives having upper semi-continuous right-hand sides we prove the existence of optimal solution minimizing a certain cost criterion.
Increased Levels of Galectin-3 in Critical COVID-19

Severe COVID-19 is related to hyperinflammation and multiple organ injury, including respiratory failure, thus requiring intensive care unit (ICU) admission. Galectin-3, a carbohydrate-binding protein exhibiting pleiotropic effects, has been previously recognized to participate in inflammation, the immune response to infections and fibrosis. The aim of this study was to evaluate the relationship between galectin-3 and the clinical severity of COVID-19, as well as assess the prognostic accuracy of galectin-3 for the probability of ICU mortality. The study included 235 COVID-19 patients with active disease, treated in two different Greek hospitals in total. Our results showed that median galectin-3 serum levels on admission were significantly increased in critical COVID-19 patients (7.2 ng/mL), as compared to the median levels of patients with less severe disease (2.9 ng/mL, p = 0.003). Galectin-3 levels of the non-survivors hospitalized in the ICU were significantly higher than those of the survivors (median 9.1 ng/mL versus 5.8 ng/mL, p = 0.001). The prognostic accuracy of galectin-3 for the probability of ICU mortality was studied with a receiver operating characteristic (ROC) curve and a multivariate analysis further demonstrated that galectin-3 concentration at hospital admission could be assumed as an independent risk factor associated with ICU mortality. Our results were validated with galectin-3 measurements in a second patient cohort from a different Greek university hospital. Our results, apart from strongly confirming and advancing previous knowledge with two patient cohorts, explore the possibility of predicting ICU mortality, which could provide useful information to clinicians. Therefore, galectin-3 seems to establish its involvement in the prognosis of hospitalized COVID-19 patients, suggesting that it could serve as a promising biomarker in critical COVID-19.
Improving Depression Severity Prediction from Passive Sensing: Symptom-Profiling Approach

Depression is a significant mental health issue that profoundly impacts people’s lives. Diagnosing depression often involves interviews with mental health professionals and surveys, which can become cumbersome when administered continuously. Digital phenotyping offers an innovative approach for detecting and monitoring depression without requiring active user involvement. This study contributes to the detection of depression severity and depressive symptoms using mobile devices. Our proposed approach aims to distinguish between different patterns of depression and improve prediction accuracy. We conducted an experiment involving 381 participants over a period of at least three months, during which we collected comprehensive passive sensor data and Patient Health Questionnaire (PHQ-9) self-reports. To enhance the accuracy of predicting depression severity levels (classified as none/mild, moderate, or severe), we introduce a novel approach called symptom profiling. The symptom profile vector represents nine depressive symptoms and indicates both the probability of each symptom being present and its significance for an individual. We evaluated the effectiveness of the symptom-profiling method by comparing the F1 score achieved using sensor data features as inputs to machine learning models with the F1 score obtained using the symptom profile vectors as inputs. Our findings demonstrate that symptom profiling improves the F1 score by up to 0.09, with an average improvement of 0.05, resulting in a depression severity prediction with an F1 score as high as 0.86.
Postseismic Deformation near the İzmit Earthquake (17 August 1999, M 7.5) Rupture Zone

We present and interpret the results of postseismic, Global Positioning System monitoring of the first 298 days following the 17 August 1999 Izmit earth- quake. Whereas the data suggest some spatial and temporal complexity in the post- seismic motions, the overall pattern can be characterized by time-dependent relaxa- tion functions and suggests exponential decay with an estimated 57-day relaxation time. The very rapid deformation during the first few weeks following the mainshock suggests rapid afterslip on and below the coseismic rupture segments. The exponen- tial decay of the postseismic deformations through the end of the observation period suggests contributions from the lower crustal viscoelastic relaxation.
A deep learning–based system for mediastinum station localization in linear EUS (with video)

ABSTRACT Background and Objectives EUS is a crucial diagnostic and therapeutic method for many anatomical regions, especially in the evaluation of mediastinal diseases and related pathologies. Rapidly finding the standard stations is the key to achieving efficient and complete mediastinal EUS imaging. However, it requires substantial technical skills and extensive knowledge of mediastinal anatomy. We constructed a system, named EUS-MPS (EUS–mediastinal position system), for real-time mediastinal EUS station recognition. Methods The standard scanning of mediastinum EUS was divided into 7 stations. There were 33 010 images in mediastinum EUS examination collected to construct a station classification model. Then, we used 151 videos clips for video validation and used 1212 EUS images from 2 other hospitals for external validation. An independent data set containing 230 EUS images was applied for the man-machine contest. We conducted a crossover study to evaluate the effectiveness of this system in reducing the difficulty of mediastinal ultrasound image interpretation. Results For station classification, the model achieved an accuracy of 90.49% in image validation and 83.80% in video validation. At external validation, the models achieved 89.85% accuracy. In the man-machine contest, the model achieved an accuracy of 84.78%, which was comparable to that of expert (83.91%). The accuracy of the trainees' station recognition was significantly improved in the crossover study, with an increase of 13.26% (95% confidence interval, 11.04%–15.48%; P < 0.05). Conclusions This deep learning–based system shows great performance in mediastinum station localization, having the potential to play an important role in shortening the learning curve and establishing standard mediastinal scanning in the future.
Worse Survival of Patients With T1 Stage II Gastric Cancer Following Radical Gastrectomy

Purpose Lymph node (LN) metastasis is a crucial factor in the prognosis of patients with gastric cancer (GC) and is known to occur more frequently in cases with an advanced T stage. This study aimed to analyze the survival data of patients with advanced LN metastasis in T1 GC. Materials and Methods From January 2008 to June 2018, 677 patients with pathological stage II GC who underwent radical gastrectomy were divided into an early GC group (EG: T1N2 and T1N3a, n=103) and an advanced GC (AGC) group (AG: T2N1, T2N2, T3N0, T3N1, and T4aN0, n=574). Short- and long-term survival rates were compared between the 2 groups. Results A total of 80.6% (n=83) of the patients in the EG group and 52.8% (n=303) in the AG group had stage IIA AGC. The extent of LN dissection, number of retrieved LNs, and short-term morbidity and mortality rates did not differ between the 2 groups. The 5-year relapse-free survival (RFS) of all patients was 87.8% and the overall survival was 84.0%. RFS was lower in the EG group than in the AG group (82.2% vs. 88.7%, P=0.047). This difference was more pronounced among patients with stage IIA (82.4% vs. 92.9%, P=0.003). Conclusions T1 GC with multiple LN metastases seems to have a worse prognosis compared to tumors with higher T-stages at the same level. Adjuvant chemotherapy is highly recommended for these patients, and future staging systems may require upstaging T1N2-stage tumors.
PERIGLACIAL MODIFICATION OF THE COX TOR—STAPLE TORS AREA OF WESTERN DARTMOOR, ENGLAND

The Pleistocene periglacial legacy to the geomorphology of Dartmoor has been substantial. This paper examines some of these relict features in an area of western Dartmoor. The major features are tors, altiplanation terraces, boulder accumulations in a variety of patterns, and earth mounds. The tors and altiplanation terraces indicate the degree of slope modification created by frost action. The block-fields (clitter) are arranged into stripes, runs and garlands. Narrow stripes start and finish in midslope positions, while boulder runs converge and diverge, apparently at random. The long axis orientation of boulders in stripes is roughly in accord with the direction of the steepest slope, whereas orientation of boulders in blockfields is more variable. The altiplanation terraces and earth mounds occur on Cox Tor, which is composed of diabase. This contrast in rock type seems to explain the lack of similar features on the granite areas. The diabase is very closely jointed and weathers to a silt grade. The e.
Dynamic core-satellite investing using higher order moments: an explicit solution

The goal of core-satellite investing is to optimally balance the portfolio allocation between a core and satellite investment. This paper provides an explicit solution when the investor's optimality criterion is the third-order and fourth-order expansion of the expected utility function, respectively. Based on a numeric example, we document the sensitivity of the proposed weights to coskewness and cokurtosis components. Finally, we use ETFs to examine the portfolio performance of the core-satellite strategy with higher order moments. We document that integrating the higher order moment in core-satellite investing can improve the financial performance of a portfolio.