Social Media Analytics for Non-Governmental Organizations

Social media has provided promotion and communication channels for organizations to reach their target audience efficiently and cost-effectively. Despite wide social media analytics applications in different areas, scant studies focus on NGOs. This research analyzes the use of social media by a well-known NGO, the Hong Kong Generation Next Arts Limited (HKGNA), on its presence and user sentiment on Twitter and Facebook to evaluate the brand image, engagement conditions, and promotion effectiveness. These findings showed a low usage frequency of their Twitter channel. Despite the overall positive sentiment, there are some deviations from their charity mission. Yet, their Facebook channel serves well for publicity, and the interaction is relatively active. Thus, more measures are necessary to improve the digital relationship between HKGNA and its targeted audience. Moreover, this methodology for data analysis serves as an example for other NGOs to improve their communication

Nontoxic Carbon Dots Potently Inhibit Human Insulin Fibrillation

One prevention and therapeutic strategy for diseases associated with peptide or protein fibrillation is to inhibit or delay the fibrillation process. Carbon dots (C–Dots) have recently emerged as benign nanoparticles to replace toxic quantum dots and have attracted great attention because of their unique optical properties and potential applications in biological systems. However, the effect of C-Dots on peptide or protein fibrillation has not been explored. In this in vitro study, human insulin was selected as a model to investigate the effect of C-Dots on insulin fibrillation. Water-soluble fluorescent C-Dots with sizes less than 6 nm were prepared from carbon powder and characterized by UV–vis spectroscopy, fluorescence, Fourier transform infrared spectrophotometry, X-ray photoelectron spectrometry, transmission electron microscopy, and atomic force microscopy. These C-Dotswere able to efficiently inhibit insulin fibrillation in a concentration-dependent manner. Theinhibiting effect of C-Dots was even observed at 0.2 μg/mL. Importantly, 40 μg/mL of C-Dots prevent 0.2 mg/mL of human insulin from fibrillation for 5 days under 65 °C, whereas insulin denatures in 3 h under the same conditions without C-Dots. The inhibiting effect is likely due to the interaction between C-Dots and insulin species before elongation. Cytotoxicity study shows that these C-Dots have very low cytotoxicity. Therefore, these C-Dots have the potential to inhibit insulin fibrillation in biological systems and in the pharmaceutical industry for the processing and formulation of insulin

Dihydrolipoic Acid Conjugated Carbon Dots Accelerate Human Insulin Fibrillation

Protein fibrillation is believed to play an important role in the pathology and development of several human diseases, such as Alzheimer’s disease, Parkinson’s disease and type 2 diabetes. Carbon dots (CDs), as a new type of nanoparticle have recently been extensively studied for potential biological applications, but their effects on protein fibrillation remain unexplored. In reality, any application in biological systems will inevitably have “contact” between proteins and CDs. In this study, human insulin was selected as a model protein to study the effects of CDs on protein fibrillation, as proteins may share a common mechanism to form fibrils. Hydrophobic CDs were conjugated with dihydrolipoic acid (DHLA-CDs) to facilitate their water solubility. Characterizations from thioflavin T fluorescence, circular dichroism spectroscopy and atomic force microscopy demonstrate that the presence of DHLA-CDs results in a higher rate of human insulin fibrillation, accelerating the conformational changes of human insulin from α-helix to β-sheet. This promoting effect is likely associated with the locally increased concentration of human insulin adsorbed on the surface of DHLA-CDs

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

The rapid development of open-source large language models (LLMs) has been truly remarkable. However, the scaling law described in previous literature presents varying conclusions, which casts a dark cloud over scaling LLMs. We delve into the study of scaling laws and present our distinctive findings that facilitate scaling of large scale models in two commonly used open-source configurations, 7B and 67B. Guided by the scaling laws, we introduce DeepSeek LLM, a project dedicated to advancing open-source language models with a long-term perspective. To support the pre-training phase, we have developed a dataset that currently consists of 2 trillion tokens and is continuously expanding. We further conduct supervised fine-tuning (SFT) and Direct Preference Optimization (DPO) on DeepSeek LLM Base models, resulting in the creation of DeepSeek Chat models. Our evaluation results demonstrate that DeepSeek LLM 67B surpasses LLaMA-2 70B on various benchmarks, particularly in the domains of code, mathematics, and reasoning. Furthermore, open-ended evaluations reveal that DeepSeek LLM 67B Chat exhibits superior performance compared to GPT-3.5

Analysis of the Interactions between Graphene Oxide and Biomolecules and Protein Fibrillation Using Surface Chemistry and Spectroscopy

Graphene oxide (GO), a novel 2−dimensional carbon based nanomaterial, has shown potential applications in biomedical and biological field, including drug and gene delivery, sensing, and bioimaging. However, one critical question needs to be addressed before any actual application: how does GO interact with biological molecules, such as amino acids, peptides, proteins, and biomembranes? In this study, spectroscopy, microscopy, and surface chemistry were applied to fundamentally understand the nature of interactions between these molecules and GO. GO was found to interact with amino acids, peptides, and proteins by fluorescence quenching. The main quenching mechanism between GO and Trp or Tyr was determined as static quenching, slightly combined with dynamic quenching. Both electrostatic interaction and hydrophobic interaction contributed to the interactions between GO and Trp or Tyr. Particularly, strong electrostatic interaction between GO and lysozyme was demonstrated and confirmed using fluorescence quenching, zeta potential, dynamic light scattering, and atomic force microscopy. This interaction was so strong that one was able to subsequently eliminate and separate lysozyme using GO. The strong electrostatic interaction also rendered the selective adsorption of lysozyme on GO from a mixture of proteins. As polymer Pluronic F127 (PF127) was used to disperse GO and block the hydrophobic interaction between GO and Trp or Tyr, the interaction and behavior between GO and PF127 were also characterized using Langmuir monolayer technique at the air–water interface. To study the nature and orientation of interaction between GO and lipid models, Langmuir monolayer technique was applied at the air−water/aqueous interface. Five lipids with the same 18–carbon alkyl chain but different head groups of charges were chosen to rationalize the possible interactions. Experimental results showed that the interaction was governed by electrostatic interaction between the polar head groups and GO. GO could incorporate into the monolayer of positively charged lipids DODAB and DSEPC, but not the neutrally or negatively charged lipids (DSPC, DSPA and SA). When GO was injected to the subphase underneath the monolayer of positively charged lipid DODAB and DSEPC, different behaviors of surface pressure were observed. An orientation model of GO was proposed to explain the different adsorption of GO. Another topic of this thesis is on protein fibrillation. Pathological conditions of human neurodegenerative diseases are now believed to be commonly associated with protein misfolding processes. Human insulin and human islet amyloid polypeptide (hIAPP) are two major hormones involved in diabetes. Fibrillation of insulin at various interfaces was summarized. The conformation and self−assembly of the hIAPP were studied at the air−aqueous interface using the Langmuir monolayer technique. Experimental results showed that hIAPP Langmuir monolayer was relatively stable and did not form aggregates when compressed. However, ongoing experiments showed there existed interaction between hIAPP and insulin, favoring the fibrillation between the two.</p

Theoretical Insight into Mechanisms of Natural and Artificial Metalloproteases

In this study, theoretical and computational approaches have been utilized to investigate the mechanisms of natural and artificial metalloproteases. The active sites of most natural metalloproteases contain a tetrahedral zinc center, coordinated by three amino acid residues combinated from His(N), Cys(S), Glu(O), and Asp(O) with a water molecule as the fourth ligand. However, the roles played by the ligands environment in the catalytic functions of enzyme are not clear. In this study, the effects of different ligand combinations (NS2, N2S, N2O, N3, S3, NO2 and NSO) in the mechanism were investigated energy barriers were compared. The machanism and energetics of the substrate bound artificial metalloproteases Ni(II)cyclen (cyclen: 1,4,7,10-tetraazacyclododecane) and Cd(II)cyclen have been investigated. In addition, the mechanism of hydrolysis of Phe-Phe peptide bond catalyzed by another artificial metalloprotease [Pd(H2O)4]2+ has also been studied

Probabilistic Plan Recognition for Multi-Agent Systems under Temporal Logic Tasks

This paper studies the plan recognition problem of multi-agent systems with temporal logic tasks. The high-level temporal tasks are represented as linear temporal logic (LTL). We present a probabilistic plan recognition algorithm to predict the future goals and identify the temporal logic tasks of the agent based on the observations of their states and actions. We subsequently build a plan library composed of Nondeterministic Bu¨chi Automation to model the temporal logic tasks. We also propose a Boolean matrix generation algorithm to map the plan library to multi-agent trajectories and a task recognition algorithm to parse the Boolean matrix. Then, the probability calculation formula is proposed to calculate the posterior goal probability distribution, and the cold start situation of the plan recognition is solved using the Bayes formula. Finally, we validate the proposed algorithm via extensive comparative simulations

Enhancing selectivity in spectrofluorimetric determination of tryptophan by using graphene oxide nanosheets

•A simple and clean method for l-Trp determination was developed using GO nanosheets.•Uptaking of l-Trp was achieved by reaction in presence of GO nanosheets.•Selectivity of l-Trp determination was highly improved using GO nanosheets. Reaction of formaldehyde with amino acids followed by oxidation with hydrogen peroxide to produce a fluorophore Norharman product is well known and was used for the spectrofluorimetric determination of l-tryptophan (Trp). This study aimed to use graphene oxide (GO) to enhance the selectivity and sensitivity of Trp in presence of other amino acids and possible interfering compounds. Different parameters such as pH, temperature, incubation time, and concentrations of formaldehyde, H2O2 and GO were studied to optimize the condition of determination. Experimental data showed that the maximum fluorescence intensity was achieved in pH 7.0–9.0 phosphate buffer mixed with 7–10% (v/v) formaldehyde and 1–2% (v/v) H2O2 as oxidizing agent at 60̊C for 1h. On the basis of calibration curve of various concentrations of Trp in the presence of 20μgmL−1 GO, the lower limit of detection (LOD) of Trp was determined as 0.092nmolmL−1 and the lower limit of quantification (LOQ) was 0.3nmolmL−1. The selectivity of Trp in presence of other amino acids and possible interfering compounds were studied with and without GO. The data obtained after inner filter effect corrections revealed that the selectivity of Trp in presence of amino acids and other possible interfering agents was improved in the range of 76–96%, compared with that in absence of GO. The enhancement of selectivity in the presence of GO indicates that the Trp and other amino acid and possible interfering compounds were adsorbed by GO, and the selective uptaking of Trp-by the reaction with formaldehyde followed by oxidation with H2O2 at 60̊C with high selectivity and sensitivity was achieved successfully