On a conjecture of Ram\'{\i}rez Alfons\'{\i}n and Ska{\l}ba II

Let $1<c<d$ be two relatively prime integers and $g_{c,d}=cd-c-d$. We confirm, by employing the Hardy--Littlewood method, a 2020 conjecture of Ram\'{\i}rez Alfons\'{\i}n and Ska{\l}ba which states that #\left\{p\le g_{c,d}:p\in \mathcal{P}, ~p=cx+dy,~x,y\in \mathbb{Z}_{\geqslant0}\right\}\sim \frac{1}{2}\pi\left(g_{c,d}\right) \quad (\text{as}~c\rightarrow\infty), where $\mathcal{P}$ is the set of primes, $\mathbb{Z}_{\geqslant0}$ is the set of nonnegative integers and $\pi(t)$ denotes the number of primes not exceeding $t$

Distribution Characteristics of Geo-hazards in a Reservoir Area, South Gansu Province, China

233-240In the process of water storage, due to water level fluctuations and base level erosion, reservoirs also play an important role in the occurrence of geological disasters. Taking a reservoir valley type in South Gansu Province, China as a case study, we investigated in depth the development and distribution of geological hazards and their influencing factors. The geological environment had changed considerably after reservoir impoundment with an increase in geological disasters. Furthermore, the main types of geological disasters were also analyzed systematically. Slope angle, altitude, slope aspect, proximity to earthquake faults, reservoir water storage, slope body structure, rock mass structure, and their combination features influenced the development and distribution of geological disasters in reservoir area. Close proximity to rivers also increases the likelihood of geological disasters. Landslides and collapses are closely related to the geo-hazards and their triggers include earthquakes, torrential rainfall, and fluctuations in reservoir water level. We also identified 2 types of debris which flow into the reservoir: gulch development and slope liquefaction

Iron-binding activity of human iron-sulfur cluster assembly protein hIscA1

A human homologue of the iron-sulfur cluster assembly protein IscA (hIscA1) has been cloned and expressed in Escherichia coli cells. The UV-visible absorption and EPR (electron paramagnetic resonance) measurements reveal that hIscA1 purified from E. coli cells contains a mononuclear iron centre and that the iron binding in hIscA1 expressed in E. coli cells can be furthermodulated by the iron content in the cell growth medium. Additional studies show that purified hIscA1 binds iron with an iron association constant of approx. 2×1019 M-1, and that the iron-bound hIscA1 is able to provide the iron for the iron-sulfur cluster assembly in a proposed scaffold protein, IscU of E. coli, in vitro. The complementation experiments indicate that hIscA1 can partially substitute for IscA in restoring the cell growth of E. coli in the M9 minimal medium under aerobic conditions. The results suggest that hIscA1, like E. coli IscA, is an iron-binding protein that may act as an iron chaperone for biogenesis of iron-sulfur clusters. © The Authors

Environment Protection Strategies and Climate Change Adaption for Sustainable Development: An Overview of Bangladesh

Sustainable development can be achieved by developing the surrounding environment and by adapting climate change. This paper aims to explain the environmental protection and climate change adaption strategies taken by the Government of Bangladesh and the Bangladeshi nationalities in a different context to attain sustainable development. This paper based on empirical and theoretical data sources. Bangladesh significantly keeps on the good sign to achieve sustainable development by banning three-wheeler from controlling air pollution and by banning non-degradable polythene bags. If Bangladesh can overcome the challenges by implementing environment protection strategies the day is not so far when Bangladesh will be a developed country by becoming a role model for other developing countries

GLM-130B: An Open Bilingual Pre-trained Model

We introduce GLM-130B, a bilingual (English and Chinese) pre-trained language model with 130 billion parameters. It is an attempt to open-source a 100B-scale model at least as good as GPT-3 (davinci) and unveil how models of such a scale can be successfully pre-trained. Over the course of this effort, we face numerous unexpected technical and engineering challenges, particularly on loss spikes and divergence. In this paper, we introduce the training process of GLM-130B including its design choices, training strategies for both efficiency and stability, and engineering efforts. The resultant GLM-130B model offers significant outperformance over GPT-3 175B (davinci) on a wide range of popular English benchmarks while the performance advantage is not observed in OPT-175B and BLOOM-176B. It also consistently and significantly outperforms ERNIE TITAN 3.0 260B -- the largest Chinese language model -- across related benchmarks. Finally, we leverage a unique scaling property of GLM-130B to reach INT4 quantization without post training, with almost no performance loss, making it the first among 100B-scale models and more importantly, allowing its effective inference on 4$\times$RTX 3090 (24G) or 8$\times$RTX 2080 Ti (11G) GPUs, the most affordable GPUs required for using 100B-scale models. The GLM-130B model weights are publicly accessible and its code, training logs, related toolkit, and lessons learned are open-sourced at \url{https://github.com/THUDM/GLM-130B/}.Comment: Accepted to ICLR 202

High-performance infrared photodetectors based on InAs/InAsSb/AlAsSb superlattice for 3.5 µm cutoff wavelength spectra

High-performance infrared p-i-n photodetectors based on InAs/InAsSb/AlAsSb superlattices on GaSb substrate have been demonstrated at 300K. These photodetectors exhibit 50% and 100% cut-off wavelength of ∼3.2 µm and ∼3.5 µm, respectively. Under -130 mV bias voltage, the device exhibits a peak responsivity of 0.56 A/W, corresponding to a quantum efficiency (QE) of 28%. The dark current density at 0 mV and -130 mV bias voltage are 8.17 × 10−2 A/cm2 and 5.02 × 10−1 A/cm2, respectively. The device exhibits a saturated dark current shot noise limited specific detectivity (D*) of 3.43 × 109 cm·Hz1/2/W (at a peak responsivity of 2.5 µm) under -130 mV of applied bias

Phase change slurries for cooling and storage: an overview of research trends and gaps

Phase change slurries (PCSs) have great potential as both a heat transfer fluid and an energy storage medium for cooling processes, cold energy storage, and cold energy transportation due to desirable thermophysical properties. One of the major benefits of PCSs compared to pure phase change materials is their fluidity, thus making them cooled or heated by a heat exchanger, pumped through pipes, discharged, and stored directly in a thermal energy storage tank. The use of encapsulated phase change slurries and gas hydrate slurry has thus attracted considerable interest as reflected in the literature with a rising number of publications and institutions involved in the area. The use of bibliometric techniques has found a recent interest in the literature to define the progress of different scientific topics and inspire researchers to identify novelties. In this paper, bibliometric analysis and a detailed systematic review are carried out to show the state-of-the-art development of PCSs for cooling applications. Research gaps and hotspots are identified to help define future perspectives on this topic

Proteomic-based stratification of intermediate-risk prostate cancer patients

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management

DPHL: A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000