Miracle-dz/UniFAR-FTUs huggingface dataset:
Fully Programmable Collective Behavior of Light‐Powered Chemical Microrobotics: pH‐Dependent Motion Behavior Switch and Controlled Cancer Cell Destruction

The development of fuel‐free light‐powered multi stimuli‐responsive microrobots is becoming a vital field in biomedical research. The challenge is to design biomedical robots with precise motion control and novel functionalities such that one day they will stand alongside medical staff as fully fledged partners in the delivery of advanced non‐invasive therapeutic procedures. In this study, a simple one‐step etching/polymerization procedure is used to fabricate crystalline metal‐organic framework structures surface‐coated with a conductive polypyrrole (PPy) layer and then enriched with Methylene Blue sensitizer molecules. Due to the PPy surface charge, the microrobots start to move when exposed to a visible light source, enabling the controllable accumulation of the microrobots at the focal point of the light beam. Furthermore, a self‐regulated motion is achieved by the PPy surface charge also providing a pH‐dependent switch capable of altering microrobot behavior. In vitro study is conducted to test microrobot efficiency against human cervix carcinoma HeLa cells. It is shown that the micromotors are able to penetrate and successfully destroy the cancer cells. The work provides proof‐of‐concept for a novel strategy in which such microrobots can be guided by an optical beam, can self‐regulate movement toward or away from each other, and can perform therapeutic functions with great efficiency.
Isomonodromic deformations and maximally stable bundles

We consider irreducible tracefree meromorphic rank 2 connections over compact Riemann surfaces. By deforming the curve, the position of the poles and the connection, we construct the universal isomonodromic deformation of such a connection. We prove that the underlying vector bundle is generically maximally stable along the deformation. For surfaces of genus greater than 1, we get a non-trivial result even for regular connections.
Palladium Cyclometallated Compounds: Evaluation of Their Catalytic Activity in Cross-Coupling Reactions

: Catalysts are substances that can increase the speed of a chemical reaction and are often used in the chemical industry. Palladium is one of the most widely used metal centers in metal-based catalysts, and a lot of palladium complexes have been extensively used in many reactions, particularly in cross-coupling reactions with a carbon − carbon bond formation. All their possible applications as catalysts, along with their uses in biological assays as anticancer agents, make these family of complexes very interesting and highly studied, allowing the modiﬁcation of the ligands around the metal and the extreme modulation of their properties. Herein we report the synthesis of several palladium cyclometallated compounds with thiosemicarbazone ligands and bis(diphenylphosphino)methane (dppm). Additionally, we evaluate their catalytic activity in a Suzuki − Miyaura cross-coupling reaction, using 4-bromoacetophenone and phenylboronic acid as reagents and following the reaction with 1 H-NMR spectroscopy. A ﬁnal comparison between the catalytic conversions and the complexes allows us to propose the best structure for a catalytic purpose in these conditions.
An improved multi-objective particle swarm optimization and its application in raw ore dispatching

An improved multi-objective particle swarm optimization with time-varying parameter and follower bee search is proposed in this article. In this algorithm, the weight of personal best solution decreases gradually as the iteration continues. This approach eliminates the effect caused by its poorer quality compared to global best solution so that the convergence ability of the algorithm is improved. Furthermore, the follower bee search in artificial bee colony algorithm is introduced to strengthen the randomness of the algorithm and discover more non-dominated solutions. A comparative simulation study is carried out using internal raw ore dispatching in an iron mining group that contains multiple stopes and concentrating mills. The results show that the proposed algorithm can significantly improve convergence and diversity.
Research on Fake News Detection Based on Diffusion Growth Rate

With the rapid development of the Internet, social media has become a convenient online platform for users to obtain information, express opinions, and communicate with each other. Users are keen to participate in discussions on hot topics and exchange opinions on social media. A lot of fake news has also arisen at this moment. However, existing fake news detection methods have the problem of relying too much on textual features. Textual features are easy to be tampered with and deceive the detector; thus, it is difficult to distinguish fake news only by relying on textual features. To address the challenge, we propose a fake news detection method based on the diffusion growth rate (Delta-G). To identify the real and fake news, Delta-G uses graph convolutional networks to extract the diffusion structure features and then adopts the long-short-term memory networks to extract the growth rate features on time series. In the experiments, Delta-G is verified on two news datasets, Twitter and Weibo. Compared with the three detection methods of decision tree classifier, support vector machines with a propagation tree kernel, and RvNN, the accuracy of the Delta-G on the two datasets is improved by an average of 5% or more, which is better than all the baselines.
Malware classification using word embeddings algorithms and long‐short term memory networks

The number of malicious software applications, or malware programs, increases every year. Their development becomes more sophisticated as new techniques are used to bypass program scanning software applications, such as antiviruses. Thereby, deep learning‐based methods emerge as a new promising way to identify these threats. Our main purpose and contribution in this work is proposing and implementing a successful approach to tackle both binary and multiclass malware classification problems. We used unsupervised word embedding algorithms for representing software applications to be analyzed and long‐short term memory for classifying the software applications. For evaluating our pipeline, we introduce a new dataset for binary and multiclass malware classification because we could not find large datasets containing sufficient samples of cleanware and the various malware types for multiclass classification that could be used to evaluate classification models. Our experimental results reached an accuracy of 88.94% for binary classification and 75.13% for multiclass classification. These results suggest that the proposed dataset is challenging, and using it can help in the training of better malware classifiers, improving security.
Preparation of an Environmentally Friendly Nano-Insecticide through Encapsulation in Polymeric Liposomes and Its Insecticidal Activities against the Fall Armyworm, Spodoptera frugiperda

Simple Summary Pests are an important factor that causes a heavy loss in corn yield and quality. The fall armyworm (FAW), Spodoptera frugiperda, is a newly invasive and extremely destructive pest, and it poses a major threat to agricultural production in China. While chemical pesticides are considered effective means for controlling the outbreak of destructive pests, pesticide delivery systems, such as microcapsules or nanoparticles, are an effective way to promote the utilization rate of traditional pesticides and to reduce environmental pollution. Therefore, the aim of this study is to design an environmentally friendly nano-insecticide that can enhance foliar retention and increase insecticidal activity. For this purpose, 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[amino(polyethylene glycol)-2000] (DSPE-PEG2000-NH2) was chosen to formulate the insecticide nanoparticles. The physicochemical properties were characterized and investigated in indoor and field efficacy trials. The results demonstrate that the nanoparticles hold promise for pest control. Abstract The insecticide emamectin benzoate (EB) was formulated with nanoparticles composed of DSPE-PEG2000-NH2 by the co-solvent method to determine its adverse impacts on the environment and to reinforce its dispersion, adhesion, and biocompatibility. A good encapsulation efficiency (70.5 ± 1.5%) of EB loaded in DSPE-PEG2000-NH2 polymeric liposomes was confirmed. Dynamic light scattering (DLS), transmission electron microscopy (TEM), and contact angle meter measurements revealed that the DSPE-EB nanoparticles had a regular distribution, spherical shape, and good leaf wettability. The contact angle on corn leaves was 47.26°, and the maximum retention was higher than that of the reference product. DSPE-EB nanoparticles had strong adhesion on maize foliage and a good, sustained release property. The efficacy trial showed that the DSPE-EB nanoparticles had a strong control effect on S. frugiperda larvae, with the LC50 of 0.046 mg/L against the third-instar S. furgiperda larve after 48 h treatment. All these results indicate that DSPE-EB nanoparticles can serve as an insecticide carrier with lower environmental impact, sustained release property, and effective control of pests.
Pembuatan Karbol Sereh untuk Pengembangan Wirausaha Karang Taruna Garuda 01 di Pondok Ungu Permai Sektor V Babelan Bekasi Utara

Karbol merupakan salah satu kebutuhan cairan pembersih dalam rumah tangga yang berfungsi untuk menghilangkan bau, serta untuk membunuh kuman dan mikroorganisme yang menempel di permukaan suatu benda. Karbol banyak diperuntukan sebagai pembersih kamar mandi, lantai dan bagian rumah lainnya yang berbau tidak sedap. Sereh sedang menjadi tren dalam varian wangi yang digunakan dalam penggunaan karbol. Hal ini dikarenakan sereh memiliki bau yang menenangkan dan banyak digunakan sebagai aroma terapi, sereh juga memiliki fungsi sebagai penangkal serangga. Bahan utama pembuatan karbol adalah surfaktan yang berfungsi sebagai pembentuk busa sehingga dapat membersihkan kotoran serta antimikroba yang berfungsi untuk membunuh bakteri dan jamur pada permukaan. Tujuan dari pengabdian kepada masyarakat ini adalah untuk memberikan ilmu kepada karang taruna dalam hal pembuatan karbol sereh untuk mengembangkan wirausaha Karang taruna di Ponduk Ungu Permai Sektor V, Babelan Bekasi Utara. Metode yang digunakan dalam kegiatan pengabdian kepada masyarakat ini adalah pemaparan, diskusi, sharing ilmu, dan praktik pembuatan karbol sereh. Hasil dari pengabdian kepada masyarakat ini berupa produk jadi karbol sereh sesuai dengan pemaparan yang diberikan.
Risk factors and diagnostic biomarkers for nonalcoholic fatty liver disease-associated hepatocellular carcinoma: Current evidence and future perspectives

High rates of excessive calorie intake diets and sedentary lifestyles have led to a global increase in nonalcoholic fatty liver disease (NAFLD). As a result, this condition has recently become one of the leading causes of hepatocellular carcinoma (HCC). Furthermore, the incidence of NAFLD-associated HCC (NAFLD-HCC) is expected to increase in the near future. Advanced liver fibrosis is the most common risk factor for NAFLD-HCC. However, up to 50% of NAFLD-HCC cases develop without underlying liver cirrhosis. Epidemiological studies have revealed many other risk factors for this condition; including diabetes, other metabolic traits, obesity, old age, male sex, Hispanic ethnicity, mild alcohol intake, and elevated liver enzymes. Specific gene variants, such as single-nucleotide polymorphisms of patatin-like phospholipase domain 3, transmembrane 6 superfamily member 2, and membrane-bound O-acyl-transferase domain-containing 7, are also associated with an increased risk of HCC in patients with NAFLD. This clinical and genetic information should be interpreted together for accurate risk prediction. Alpha-fetoprotein (AFP) is the only biomarker currently recommended for HCC screening. However, it is not sufficiently sensitive in addressing this diagnostic challenge. The GALAD score can be calculated based on sex, age, lectin-bound AFP, AFP, and des-carboxyprothrombin and is reported to show better diagnostic performance for HCC. In addition, emerging studies on genetic and epigenetic biomarkers have also yielded promising diagnostic potential. However, further research is needed to establish an effective surveillance program for the early diagnosis of NAFLD-HCC.
Early Signs of Microvascular Endothelial Dysfunction in Adolescents with Newly Diagnosed Essential Hypertension

Endothelial dysfunction represents one of the key pathomechanisms in many diseases, including hypertension. Peripheral arterial tonometry (PAT) evaluates the functional status of microvascular endothelium and offers a biomarker of early, potentially reversible, vascular damage. This study aimed to assess endothelial function using conventional and novel indices of PAT in pediatric hypertensives. As such, 100 adolescents with normal blood pressure, and essential and white-coat hypertension were examined using EndoPAT 2000. Conventional reactive hyperemia index (RHI) and novel indices of hyperemic response, including the area under the curve of hyperemic response (AUC), were evaluated. AUC was the only parameter sensitive to the effect of hypertension, with significantly lower values in essential hypertensives compared to normotensives and white-coat hypertensives (p = 0.024, p = 0.032, respectively). AUC was the only parameter significantly correlating with mean ambulatory monitored blood pressure (r = −0.231, p = 0.021). AUC showed a significant negative association with age (p = 0.039), but a significant positive association with pubertal status indexed by plasma levels of dehydroepiandrosterone (p = 0.027). This is the first study reporting early signs of microvascular endothelial dysfunction evaluated using PAT in adolescents with newly diagnosed essential hypertension. Detailed analysis of hyperemic response using overall magnitude indexed by AUC provided a more robust method compared to the conventional evaluation of RHI.
Terrain Recognition Based on the Wheel Contact Angle Measurement using Laser Scanners for Six-Wheel Mobile Robot

This work presents a mobile robot for delivery services that use laser scanning sensors to recognize the local geometry of the terrain, using the contact angle parameter that gives information regarding the surface that the wheel touches the ground. Thus, the proposed method allows proper robot control to climb up and down safely in rigid terrains. We calculate the Jacobian matrix and its inverse to obtain the kinematic model of a wheeled robot that receives the contact angle measurement between wheel-ground and adjusts the velocity according to the terrain contact. A slip control is also implemented based on the slip ratio to guarantee the robot continues climbing. The simulation and experiment demonstrate the accuracy of the contact angle measurement between wheel-ground using laser sensors and the successful capability of the mobile robot to climb up and down.
The Democratic Values Included in Sixth Grade EFL Textbooks in Jordan: Analytical Study

- 81 - Abstract: This analytical study aimed at analyzing the democratic values existing in sixth-grade English textbooks in Jordan. The population of the study consisted of all content of sixth-grade EFL textbooks during the scholastic year 2021\2022. The researchers developed a content analysis card consisting of 37 democratic values distributed according to (4) fields: Political Principles, Cultural Rights, Human and Social relations, and Religious Values. The findings revealed that there are 1846 democratic values in the sixth-grade textbooks. The findings also indicated that the political principles are the most frequent value in the content of sixth-grade English textbooks while religious values are the least promoted within the textbooks.
RD strategy of small and medium enterprises in India: Trends and determinants

: The liberalization of economic policies in the last two decades and intensifying market competition tends to be a cause of policy concern for the survival of SMEs in emerging economies like India as these firms accounts for the largest chunk of industrial units and employment. Given their limited financial and intangible resources, the promotion of R&D among SMEs has become a very important policy parameter. The aim of this paper is to contribute to the literature on Indian R&D by analyzing the trends and patterns of R&D investment by Indian manufacturing SMEs during the period 1991 − 2008 and exploring various factors that determine their R&D behaviour. The results show that Indian SMEs have lowest incidence of doing in-house R&D and their R&D intensities have fallen in the last decade. A number of factors that play important role in determining SME R&D have been identified based on the three steps Censored Quantile Regression and some useful policy implications are suggested for enhancing R&D activities of small firms.
Short-wavelength light induces broiler’s behavioral and physiological syndrome through a misaligned eating rhythm

: Previous work shows that long-wavelength light has a robust circadian rhythmic pattern in the expression of clock genes of chickens, whereas short-wavelength light leads to an arrhythmic oscillation of some clock genes (e.g., cClock , cCry1 , cCry2 , cPer2 , and cPer3 ). However, knowledge about the consequences of LED lights on the physiological and behavioral phenotype was still not clear. This experiment hypothesizes that short-wavelength light disturbs chickens’ eating rhythm and leads to the wrong time to eat, resulting in metabolic syndrome. “Meihuang” broilers were housed in monochromatic LED blue light, green light, yellow light, red light, or white light with a very low dose (15 lx). Multiply physiological parameters were measured and the 24-h eating behavior was determined. The effects of LED light on physiological status and behavioral phenotype showed a wavelength-dependent manner. Short-wavelength light significantly decreased the level of total triglycerides and total cholesterol but increased triiodothyronine concentration. Inversely, long-wavelength light increased the triglycerides and total cholesterol and reduced the level of triiodothyronine. Further, it was found that short-wavelength light significantly boosted body weight compared with long-wavelength light, despite equivalent levels of food intake. Short-wavelength light-induced 23.4% and 14.1% of food consumption during subjective nights, but long-wavelength light did not. These results imply that when chickens eat matters, not just what they eat. Thus, low as 15 lx of blue light exposure during the typical dark period is sufficient to lead an individual to eat at the “wrong” time, causing metabolic dysfunction. Blue light should be cautiously considered to be used in the poultry breeding process. Short-wavelength light induces broiler’s behavioral and physiological through a misaligned Int J Agric & Biol Eng, 2022; 15(3): 47–54.
Image-graph-image auto-encoding: a conceptual study with symbolic shape classification

This work presents basic research on convolutional neural networks that learn to predict explainable scene graphs from input images without external supervision during training. Unlike existing approaches following a fully-supervised training paradigm, thereby requiring meticulous annotations, we are the first to present a self-supervised approach based on a fully differentiable auto-encoder in which the bottleneck is the graph that corresponds to the input image. To demonstrate the unique conceptual properties of our graph auto-encoder, we apply it to an example task that performs simple rule-based shape classification using only the information in the graph, and we show that our approach allows for the successful classification of shapes that are never seen during training. We report exploratory findings of our research in which the presented approach is applied to elementary line drawings depicting single shapes with limited complexity. We show that our approach exhibits comparable performance to a fully-supervised graph parser baseline, and generalizes significantly better than a conventional image classifier. Although extensive future research is needed to bring our approach to complex natural images, we believe it makes a valuable conceptual step in bridging deep neural networks with graph-based symbolic knowledge representations.
Quantum Gravity with Minimal Assumptions

The purpose is to construct the quantum field theory including gravity, based on physical assumptions as few as possible. Up to now, the work by Prof. Steven Weinberg probably suits this purpose the most. Though the purpose is difficult to reach, my recent preprint was interested in an exceptional case caused by singularity. Therefore, I'd like to explain the motivations and possible applications of the preprint.
Modeling Perspective-Dependent Ambiguity in Grounded Collaborative Dialogue

Errors in reference generation and resolution can occur if a dialogue agent reasons incorrectly about their partner’s perspective. We present, in a collaborative and visually grounded setting, a dialogue planner that infers its partner’s perspective to produce referring expressions that the partner resolves correctly. The dialogue planner models the partner perspective as a latent variable, embedded in a partner model that is used for both model-based planning and incorporating evidence from partner responses. We validate our approach on O NE C OMMON , a challenging dialogue game where players have large differences in their perspectives. In symbolic selfplay, where agents partner with a copy of themselves using symbolic communication, the dialogue planner has promising performance, winning 85.2% of games.
Designing E-Banking Cardless Transaction Services Framework Designing E-Banking Cardless Transaction Services Framework for Banking Sectors in Ethiopia for Banking Sectors in Ethiopia

: E-banking cardless technologies, enable to withdraw cash from ATM without virtual or any physical card. It increases enhanced utilization of ATM banking services and improve flexibility of services to customers. The purpose of this research was to develop cardless e-banking services. The study used design Science research methodology. The study uses requirement elicitation method to identify and analyze existing system challenges then to design E-banking cardless transaction services framework. Based on the proposed framework, the software was developed that allows customer to withdraw cash from ATM machine using their mobile phone. Based on the study result, card expiration, captured, dispute and forgotten were the main challenges to the exiting ATM based banking services. All of the respondents were used Mobile and ATM services. Domain experts were evaluated both the framework and the prototype, acceptable result was found from the evaluation. The integration of ATM and Mobile banking services and the ECTS framework development can enhance utilization of E-banking services.